Java67

Database Sharding 101: The One Topic You Must Nail in Every System Design Interview

2026-03-18T21:23:00.000-07:00

Hello friends, in this data driven world, the ability to efficiently handle vast amounts of data is crucial for businesses and organizations. Traditional monolithic databases often struggle to keep pace with the demands of modern applications and services and become performance bottleneck. This is where database sharding comes into play, offering a powerful solution for horizontally scaling your data. If you don't know what is Sharding? Well, Sharding is a database architecture technique that involves partitioning a large database into smaller, more manageable pieces, called "shards," which are distributed across multiple servers.

Each shard contains a subset of the data, and together they form the complete dataset. This approach enhances performance and scalability by distributing the workload, reducing latency, and enabling parallel processing.

Review - Is Educative Unlimited Plan Really Worth It in 2026?

2026-03-16T21:38:00.000-07:00

With the ever-growing demand for software development skills, online learning platforms like Educative.io have become popular choices for developers looking to upskill efficiently.

Among its offerings, the Educative Unlimited Subscription is a widely discussed plan that grants access to hundreds of courses, including popular ones like “Grokking the Coding Interview” and “ Grokking Modern System Design for Software Engineers & Managers

But is the Educative Unlimited Subscription worth it in 2026? In this article, we’ll analyze the platform’s strengths, drawbacks, pricing, course quality, and community feedback to help you decide if it’s the right investment for your learning journey.

What is Educative.io?

Educative.io is an interactive learning platform designed specifically for software developers and tech professionals.

Unlike video-based platforms such as s Udemy, or Coursera, Educative uses a text-based, hands-on coding approach where learners write and run code directly in the browser.

Key Features of Educative.io:

Interactive Coding Environment — No need for setup; code directly within the platform.
Comprehensive Course Library — Covers topics like coding interviews, system design, cloud computing, DevOps, and AI.
Self-Paced Learning — Move at your own speed and revisit concepts anytime.
Structured Learning Paths — Provides guided roadmaps for mastering different skills.
Regularly Updated Courses — Keeps content fresh and aligned with industry trends.

What is Educative Unlimited?

It’s a subscription plan similar to Coursera Plus or Udemy Personal Plan which give access to text-based interactive courses on Educative.io platform, an online website famous for its System Design and Coding Courses.

The Educative Unlimited Subscription gives learners full access to all courses on the platform. Instead of purchasing individual courses, subscribers can explore hundreds of courses under a single plan.

Pricing for Educative Unlimited

As of 2026, Educative offers two main pricing options:

Annual Plan — Costs $16.66/month (billed annually at $199.99).
Monthly Plan — Costs $59/month, making the annual plan the better deal.
Two Year Plan — The most popular premium plan cost $14/ month and billed every 2 years $314 while original price is $698.

Educative often offers discounts, so checking for promotional offers can help you get a better deal. For example, right now they are offering a huge 50% discount now.

Here is the link to get your discount — Educative Unlimited Subscription

Who Should Consider Educative Unlimited?

Educative Unlimited is best suited for:

Aspiring and experienced developers preparing for coding interviews (FAANG and other top tech companies).
Software engineers looking to level up in system design and scalability concepts.
Professionals transitioning into DevOps, Cloud Computing, or AI/ML.
Developers who prefer reading and interactive coding over watching videos.

If you fall into any of these categories, Educative.io can be a strong investment.

5 Best Courses on Educative.io (Included in Unlimited Subscription)

Here are some of the top-rated courses that make Educative Unlimited worth considering:

1. Grokking the Coding Interview

Why it’s worth it: Covers patterns for solving coding problems, making it easier to tackle LeetCode-style questions.
Ideal for: Software engineers preparing for FAANG coding interviews.

Grokking the Coding Interview Patterns — AI-Powered Course

Master 24 essential coding patterns to solve thousands of LeetCode-style questions. Efficiently prepare for coding…

www.educative.io

2. Grokking Modern System Design for Software Engineers & Managers

Why it’s worth it: Provides a structured framework for designing scalable systems like Twitter, Instagram, and Uber.
Ideal for: Developers preparing for system design interviews.

Grokking the Modern System Design Interview

The ultimate guide to System Design Interviews — developed by FAANG engineers. Master distributed system fundamentals &…

www.educative.io

3. Grokking the Machine Learning Interview

Why it’s worth it: Covers ML system design, a crucial topic for AI/ML engineers.
Ideal for: Machine learning engineers applying to top AI firms.

Grokking Coding Interview Patterns in Python

Level up your coding skills. No more passive learning. Interactive in-browser environments keep you engaged and test…

www.educative.io

4. Data Structures for Coding Interviews in Python

Why it’s worth it: Covers all key data structures in an interactive format, ideal for beginners.
Ideal for: Students and new developers looking to master DSA and senior developers preparing for coding interviews.

Data Structures for Coding Interviews in Python — AI-Powered Course

Explore proven strategies developed by FAANG engineers to ace coding interviews with a structured approach to data…

www.educative.io

5. Master AWS Certified Solutions Architect Associate SAA-C03 Exam

Why it’s worth it: Prepares learners for AWS Solutions Architect and DevOps certifications.
Ideal for: Cloud engineers and DevOps professionals.

AWS Solutions Architect Associate

Become an AWS pro with this course developed by AWS Solution Certified Architects. Get hands-on with secure, resilient…

www.educative.io

These courses alone justify the cost of Educative Unlimited, especially if you’re preparing for tech interviews or upskilling in cloud computing.

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Ready to level up your career? Lock in unlimited access to Educative’s entire library of 1200+ hands-on Courses…

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Pros and Cons of Educative Unlimited Subscription

Before you buy anything online its important to analyze its pros and cons and Educative subscription is no different but its ok if you make mistake on buying a product which is for learning but still knowing about pros and cons help you take right decision.

Pros: What Makes Educative.io Worth It?

Here are the main reasons for joining Educative.io for online learning in 2026:

1. Access to High-Quality Courses

Popular courses like “Grokking the Coding Interview” are used by thousands of FAANG interview candidates.
System design and cloud computing courses offer real-world case studies.

2. Hands-On Coding Without Setup

Unlike Udemy or Coursera, where you have to set up coding environments, Educative provides an interactive editor.
This feature saves time and makes learning smoother.

3. Great for Interview Preparation

Many Google, Meta, and Amazon engineers use Educative for interview prep.
The structured learning paths help streamline preparation.

4. Cost-Effective Compared to Buying Individual Courses

Single courses like Grokking the Coding Interview cost $79-$99.
With Educative Unlimited ($199/year), you get access to hundreds of courses, making it a better deal.

5. Frequent Updates and New Courses

Courses are updated regularly, ensuring content remains up-to-date with industry standards.

Cons: Where Educative.io Falls Short

Nothing is perfect and Educative.io is no exception, there are few things which you need to know before you pay for Educative.io subscription:

1. No Video-Based Learning

Some learners prefer video-based platforms like Udemy or Coursera.
If you enjoy watching instructors explain concepts, Educative might not be the best fit.

2. Expensive Monthly Plan

The monthly plan ($59/month) is not cost-effective compared to the annual plan ($199/year).
If you don’t plan to use the platform long-term, it may not be worth the high cost.

3. Limited Customer Support

Some users report slow response times when handling billing issues.
Make sure to cancel trials early if you don’t plan to continue.

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Learn new job skills in online courses from industry leaders like Google, IBM, & Meta. Advance your career with top…

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Community Feedback: What Are Other Developers Saying?

While I have positive experience learning on Educative.io and their System Design courses and Cloud labs have helped me a lot, I have also analyzed feedback from Reddit, Twitter, and tech forums to understand how developers feel about Educative Unlimited subscription.

Positive Reviews:

Reddit user (r/cscareerquestions):
“Grokking the System Design Interview is the best resource for system design prep. Worth every penny!”

Twitter review:
“Educative’s coding interview courses helped me land a job at a FAANG company. The interactive coding experience is a game-changer!”

Negative Reviews:

Reddit user (r/programming):
“The billing system is confusing. I got charged for an extra month even after canceling.”

Product Hunt user:
“Great for text-based learning, but I prefer video-based courses for complex topics like ML.”

Overall, most negative feedback revolves around billing issues and lack of video content, while positive feedback highlights the quality of interview prep courses.

Is Educative Unlimited Worth It in 2026?

Now that we have good knowledge of what to expect on getting a Educative Unlimited subscription, let’s analyze them one last time to find out whether Educative Unlimited subscription is worth it or not?

Educative.io is definitely worth It If:
✔️ You’re preparing for coding or system design interviews.
✔️ You prefer interactive coding exercises over watching videos.
✔️ You plan to learn multiple skills (DSA, system design, cloud, DevOps, ML).
✔️ You want a cost-effective way to access premium courses.

❌ Not Worth It If:
❌ You prefer video-based learning like Udemy or Coursera.
❌ You need only one or two courses (buying them separately might be cheaper).
❌ You don’t like text-heavy learning.

If you fall into the first category, Educative Unlimited is one of the best investments you can make for career growth in 2026. If you’re unsure, try the free trial before committing.

The best thing about Educative Unlimited is that they are offering 50% discount now which means you can join it for just hal price.

Educative Unlimited: Excel with AI-Powered Learning

Ready to level up your career? Lock in unlimited access to Educative’s entire library of 1200+ hands-on Courses…

www.educative.io

Where to Subscribe to Educative Unlimited

If you find these online courses and Educative platforms useful then you can also consider getting an Educative Subscription which gives you access to their 100+ courses for just $14.99 USD per month.

Sometimes you need this flexibility of joining a course you want instead of purchasing it. It’s also a better deal if you are going to attend more than a couple of courses on Educative in a year.

Here is the link to get 👉 Educative.io Subscription — Educative Unlimited

That’s all about review of Educative.io platform for developers and programmers preparing for coding interviews. If you ask me Educative Unlimited is definitely worth it not just for preparing coding interview but also to learn modern technology like AWS, Microservices, System Design, and Software architecture.

Other Educative Resources You may like to explore

Thank you for reading this article so far. All the best for your learning journey in 2026, if you have any doubts or questions, feel free to ask in the comments.

Final Tip: If you’re preparing for tech interviews, start with Grokking the Coding Interview and Grokking System Design Interviews — these two courses alone justify the subscription cost.

Educative Unlimited: Excel with AI-Powered Learning

Ready to level up your career? Lock in unlimited access to Educative’s entire library of 1200+ hands-on Courses…

www.educative.io

I Tried 30+ Software Architecture Courses Online: Here Are My Top 10 Recommendations for 2026

2026-03-13T08:18:00.000-07:00

Every Programmer wants to grow in their career, but it’s not easy, and if you don’t pay attention to your job, you will likely stay in the same position for many years.

The growth in the initial few years is generally fast. Still, once you reach the barrier of 5 years, you need to decide which direction you want to move like — people management, product management, or software architecture.

For tech guys, who don’t want to go on people and product management, software architecture or solution architecture is the final position, which is not surprising.

If you want to be close with coding and technical discussions, like to try new technologies and want to use them in your organization to solve a challenging problem, software architecture is an excellent position to be in.

Most of the Java developers I have met or interacted with wanted to become software architects, though only a few succeed, and most of them are still either technical leads or Senior Software developers.

But, the big question is, how does a senior developer become a software architect? What books or courses you can look forward to learning the skills a Software or Solution architect should have? It’s also one of the most common questions I receive from my reader, apart from how to prepare for Java interviews.

To help you with this question and to answer many such questions from my readers, I’ll share a few online courses you can take to learn more about Software Architecture and how to become a software architect.

In the past, I have shared a couple of books you can read to learn some software architecture skills, and these courses will supplement whatever you have learned from them. You can also use these courses and those books to get the best of both worlds.

Top 10 Courses to become Software Architect in 2026

As I have said, a Software architect position is not a comfortable position. The architect is responsible for all technology decisions in the project and also has a significant role.

You need to know a lot of things, not just the technology but also the business. You should not only be familiar with general software architecture, design, coding, and programming best practices, but also with the latest technologies, libraries, and framework and knows their pros and cons to choosing the right technology for your solution.

In these few courses, I have tried to include most of the things you need to learn in Software Architecture, but this list is by no means complete, and I am keen to get some suggestions from some of the experienced Software Architects who come across this article.

Anyway, without any further ado, here are the best online courses to learn Software Architecture and become a Solution Architect or Software Architect.

1. Certified Professional for Software Architecture (Top Developer Academy)

This is one of the most premium training program for anyone who want to become a tech lead or software architect, especially for senior software engineers and Java developers

Created by Michael Pogrebinsky, an experienced software engineer, software architect, and accredited iSAQB® CPSA-F® trainer and founder of Top Developer Academy, this comprehensive course and training program will give you practical, job-ready skills you need to become a Software architect.

Here are key skills you will learn in this training course:

How to design an effective software architecture for your system
Ensure the fulfillment of complex project requirements
Apply industry-proven design principles, patterns, and best practices
Evaluate and assess the quality of the software architecture
Document and communicate design decisions, interfaces, and cross-cutting concerns

This training also prepares you to pass the CPSA-F® exam from an iSAQB®-accredited certification body, giving you a globally recognized credential for your career.

Here is the link to join this course — Certified Professional for Software Architecture

2. Software Architecture on Coursera

When it comes to online learning, Coursera is one of the reputed websites and also one of my favorite places along with Udemy and Pluralsight. It has some of the best courses on machine learning, Algorithms, and Software Architecture, and this is one of them.

In this course, you will learn how to represent a software architecture using visual tools like UML, which is very important to communicate the architecture with shareholders as well as developers who will implement it.

You will also learn some of the standard architectures, their qualities, and their tradeoffs. The course also talks about how designs are evaluated, what makes a good architecture, and architecture can be improved.

And the best part of the course is that you will do some hands-on practice in the last module by documenting a Java-based Android application (Capstone Project) with UML diagrams and analyzing evaluate the application’s architecture using the Architecture Tradeoff Analysis Method (ATAM).

Here is the link to join this program — Software Architecture on Coursera

And, if you find Coursera courses useful, which they are because they are created by reputed companies and universities around the world, I suggest you join the Coursera Plus, a subscription plan from Coursera which gives you unlimited access to their most popular courses, specialization, professional certificate, and guided projects. It cost around $399/year but its complete worth of your money as you get unlimited certificates.

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3. How To Become An Outstanding Solution Architect (Udemy)

This is another excellent and must-take course for all the programmers who aspire to become software architect. In this course, instructor Mark Farragher will teach you all the skills you need to become an outstanding solution architect.

He will not only teach you how to create an excellent architecture design but also show you all the soft skills you will need to really shine in this role and make an impression on your peers.

This is extremely important as you need to do a lot of talking and probably need to interact with most of the people in the organization, including CEO and CTO.

This course also covers how a Software Architect or Solution Architect operates in an IT team, which soft skills are required to become an outstanding architect, and which extra responsibilities you can take on to really make an impression on your peers.

Here is the link to join this course — How To Become An Outstanding Solution Architect

Talking about technical skill, the course will teach you how to create high architectures, explain common architecture design patterns, and shows how to design these patterns in UML.

It also covers what to look at architecture, both high and low levels, like caching, exception management, and deployment scenarios. In short, an excellent course for all programmer and senior developer who wants to become Solution Architect.

4. Basics of Software Architecture & Design Patterns in Java

This course is a more low level than the previous two sessions and talks about software architecture and design patterns, somewhat more concrete things than abstract design.

The course uses Java programming language to solve problems, which is great for Java developers. Still, the theoretical background is language-independent and useful for all programmers irrespective of their programming languages.

I highly recommend coding out the implementations several times on your own to get a good grasp of them.

It also covers things like SOLID principles and design patterns, which are vital for any good architecture and robust application.

Here is the link to join this course — Basics of Software Architecture & Design Patterns in Java

5. Clean Architecture for Beginners: A Practical Guide

This is another excellent Udemy course on Software Architecture. In this course, you will learn about Clean Architecture, if you think what a clean architecture is, it’s nothing but a set of modern patterns, practices, and principles for creating a software architecture that is simple, understandable, flexible, testable, and maintainable.

There is a lot of focus on an organization to write Clean Code and create Clean Architecture, and this course will help you in that direction.

This is an introductory course, which means no prerequisites for this course. However, having essential experience with at least one the C like a programming language, and basic knowledge of software architecture is beneficial.

It’s totally different from the Clean Architecture book by Uncle Bob, which is also a worth reading book for programmers who wants to become software architect.

Here is the link to join this course — Clean Architecture for Beginners: A Practical Guide

6. Grokking the System Design Interview (Educative)

This is one of my favorite courses when it comes to learning Software Design or System design. It’s created to prepare you for the System design interview, but you can also use it to learn how to approach System design in general.

The Grokking the System Design Interview, is one of the first courses (or book) that describes the Large Scale Distributed System Design problems in detail.

Even if you’ve worked on Distributed Systems before, there are a lot of things that you can learn from this course.

The authors have created this course to provide you with design choices(including pros and cons) so that you can understand the requirement, compare approaches, and come up with the best solution for the problem at hand.

Here is the link to join this course — Grokking the System Design Interview

They are also mindful not to provide a solution at a granularity that’s appropriate for a 45-minute discussion. This makes the course very interesting.

Even if you are not preparing for Coding interviews, I suggest you take this course to improve your System design skills. Big thanks to The Educative Team and Fahim ul Haq for creating this awesome course.

7. Web Application & Software Architecture 101 (Educative)

This is another excellent course from Educative.io to learn about Web application architecture. In this course, you will learn about different architectural styles like monolith, microservices, client-server, 3-tier architecture, decentralized peer-to-peer architecture, and how requests and data move in web applications.

You will also learn about how to think big and think in terms of layers, performance, scalability, and high availability, which is a must for today’s application.

The course not only introduces the different architectural pattern but also explains the pros and cons of each approach and walk you through a different scenario where a particular architecture is more suitable than others.

Here is the link to join the course — Web Application & Software Architecture 101

To be honest with you, this is the best course for not only senior developers but also every software developer out there as it will expand your thinking process and will you make a more confident web developer.

There is a significant discount on the course now, and it’s available for just $44, the original price $79, it’s a bit expensive for them Udemy courses but worth it.

On the other hand, if you like Educative as a platform, you can also buy a subscription for just $17 per month (50% discount), I have one, and I highly recommend you to get one.

8. Master the Coding Interview: System Design + Architecture (ZTM)

If you are looking for a bootcamp style System Design course to quickly refresh all essential System design concepts then this course from ZTM academy is the best one to start with.

This is a comprehensive System Design course that aims to guide aspiring developers in advancing their careers and becoming Senior Software Engineers or Developers at top tech companies.

Taught by System Design Expert Yihua, who has real-world experience working for major tech companies, this online course offers invaluable insights and insider tips for mastering system design.

The course focuses on developing a mental framework to think like a Senior Software Engineer, enabling students to analyze their work from a system design perspective.

It covers various aspects, including evaluating different components and technologies in web applications, understanding considerations and trade-offs in building applications, and using the right system design and architecture to arrive at optimal solutions.

What sets Master the Coding Interview: System Design + Architecture course by Zero to Mastery apart from other system design courses is its emphasis on seeing the bigger picture and executing on it.

Overall, one of the best online course to not just master System design concepts but also crack coding interviews on top tech companies and also progress to become senior software engineer.

Here is the link to join this course — Master the Coding Interview: System Design + Architecture

It goes beyond low-level coding and encourages students to understand the broader system they are a part of, fostering a deeper comprehension of the “why” behind their work.

By providing a problem-solving framework and practical knowledge gained from Yihua’s industry experience, the course empowers students to become better problem solvers and programmers.

Btw, you would need a ZTM membership to watch this course which costs around $39 per month but also provides access to many super engaging and useful courses like this Python course. You can also use my code FRIENDS10 to get a 10% discount on any subscription you choose.

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9. Software Architecture & Design of Modern Large Scale Systems

If you are looking for an online course to learn about how to design modern large scale systems then this Udemy course is for you.

If you want to become a Software Architect or Technical Lead in 2026 then the “Software Architecture & Design of Modern Large Scale Systems” course is a great starting point.

Created by Michael Pogrebinsky, a Java and System design expert and a Software architect, this course is one of the Udemy bestseller and have a stellar rating of 4.7 out of 5 from 5,267 ratings, this course is curated for individuals aspiring to master software architecture, system design, and big data processing.

The course covers critical aspects such as designing large-scale systems capable of handling millions of requests daily, creating highly scalable and available software systems, and applying industry-proven architectural patterns and best practices.

Here is the link to join this course — Software Architecture & Design of Modern Large Scale Systems

10. Grokking the System Design Interview on Design Guru

System design is a critical component for software architecture and this is one of my favorite System design course which was earlier available on Educative but now its moved exclusively on Designgurus.io.

This site is created by Arslan Ahmad , a former software engineer @ Facebook, Microsoft, Hulu and writer.

This course not only give you solution of popular System design questions like how to design a chat system like WhatsApp or how to design a URL shortener but also a complete System Design template on how to approach and solve a system design problem.

Apart from that its an interactive course where you can practice online right on your browser and it also got community support, but the best thing I liked about this course is the real case studies on various system design problem That’s the real gem of this course.

It also helped that creator of this course is people have not only worked in FAANG companies but also have unique opportunity to be as a candidate as well as hiring manager so not only they know what to ask but also how to answer.

In short, its one of the best place to learn system design and if you want to crack your system design interview with confidence, you should checkout this course. Here is a also a nice system deign template or cheat sheet you can checkout from them

That’s all about some of the best online courses to learn Software architecture and become a Software Architect or Solution Architect. As I have said, the role of a Software architect is significant, and he also needs to do a lot of talking, hence not just subject matter and technologies, he also needs to be good at soft skills.

It’s a gratifying career, both in terms of pay and work, as you get a lot of limelight and get to talk to both higher and lower levels in your organization like from CEO to Developers, and know most of the things about your application and solution.

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Thanks for reading this article so far. If you found these courses useful in becoming a software architect or learning software architecture, please share them with your friends and colleagues. If you have any questions or feedback, then please drop a note. cc

P.S. — If you are looking for a free course to learn Java design patterns, which are also crucial for Software architects, then you can also check out Java Design Patterns and Architecture course on Udemy. It’s completely free and has loads of useful information on using design patterns for Java programmers.

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I Failed 4 FAANG Interviews Before Learning This - The Ultimate Tech Interview Guide Software Engineers

2026-03-12T21:14:00.000-07:00

Disclosure: This post includes affiliate links; I may receive compensation if you purchase products or services from the different links provided in this article.

Let me be honest with you: I bombed four FAANG interviews before I figured out what I was doing wrong. It wasn't that I couldn't code; I had years of professional experience. The problem was that I was preparing randomly. I'd grind LeetCode one day, watch system design videos the next, and panic-read about behavioral questions the night before interviews.

No structure. No strategy. Just chaos.

Everything changed when I stopped treating interview prep like a buffet and started following a systematic approach.

If you're drowning in data structures, algorithms, system design, and all the other topics people say you "must know" for coding interviews, you're in the right place.

This guide will give you a clear, step-by-step roadmap to cover all the bases without burning out.

And if you're looking for a one-stop shop to prepare comprehensively, DesignGurus.io is where I'd start. They have Grokking courses covering OOP Design, System Design, Dynamic Programming, and more.

You can also access all their courses with a significant discount through their All Courses Bundle. Use code GURU for 30% off.

How to Prepare for Coding Interviews in 2026: Your Step-by-Step Guide

Here's the systematic approach that took me from bombing interviews to landing offers. Follow this order — it matters.

1. Data Structures and Algorithms: Master the Foundation First

If you're serious about coding interviews in 2026, DSA isn't optional — it's the foundation everything else rests on. Here's how I'd approach it today if I were starting over:

Best Resources for DSA Preparation

1. AlgoMonster

This is where I'd start if I were doing it again. AlgoMonster is a streamlined, interactive platform designed by Google and Facebook engineers that teaches coding patterns fast — with visual explanations and zero fluff. Perfect for busy professionals who can't afford to waste time.

Why it works: Pattern recognition is the key to DSA success. AlgoMonster teaches you to see the patterns, not just memorize solutions.

2. Educative's 99 Coding Patterns

Available in both Python and Java, this course covers 26 essential patterns that appear repeatedly in interviews. The interactive, code-in-browser format makes it easy to practice and internalize concepts without context switching.

My experience: The two-pointer pattern alone helped me solve a dozen different interview problems I'd previously struggled with.

3. Blind 75 (Free)

The classic, no-nonsense list of 75 must-solve problems. If you're short on time, these are the problems you absolutely cannot skip. Widely recommended by engineers who've landed jobs at FAANG companies.

4. Grind 75 (Free)

Created by a former Meta engineer, Grind 75 improves on Blind 75 with better structure. It provides a 4- to 8-week plan tailored to your daily time availability, making it easier to stay consistent.

Pro tip: Choose Grind 75 over Blind 75 if you want a more structured approach with time-boxed milestones.

5. Master Your Language's Standard Library

Speed matters in interviews. Make sure you're fluent with C++ STL, Java Collections, or Python's built-in data structures. The right API knowledge can save precious minutes during your interview — and minutes matter.

Reality check: If you're a beginner, DSA requires more than 3 months of active practice. If you're rusty, start with top interview questions and coding patterns on sites like LeetCode and AlgoMonster.

Here's a helpful coding interview patterns cheat sheet from Educative.io showing which coding problems can be solved with which patterns:

2. System Design: Think Like an Architect, Not Just a Coder

System design interviews separate senior candidates from everyone else. Passive learning won't cut it here — you need to actively design systems and defend your choices.

Best Resources for System Design

1. System Design Interview books by Alex Xu (Volumes 1 & 2)

These are the gold standard for system design prep. The books break down real interview questions and walk you through design trade-offs and scaling strategies step by step.

Alternative: If you prefer online learning, the ByteByteGo course offers digital versions of both books plus complementary materials.

2. Best YouTube Channels for System Design

For visual learners, these channels cover key system design concepts with diagrams and real-world examples. Perfect for quick refreshers or deep dives into specific topics.

3. Active Practice: Design, Don't Just Read

It's tempting to read solutions and move on. Don't. Sketch out designs on a whiteboard. Write down trade-offs. Think through failure points as if you're in the interview room right now.

The mistake I made: I read dozens of system design solutions without ever designing anything myself. When I got to real interviews, I froze.

4. Mock Interviews on Pramp, bugfree.ai and Exponent

Practice live with peers or coaches. You'll get real-time feedback and experience thinking on your feet — critical for design interviews where there's no single "right" answer.

5. Codemia.io System Design Practice in LeetCode Style

Passive learning won't help. Codemia.io lets you practice system design problems like you'd practice coding questions. It's one of the few platforms built specifically for this — and they have the biggest collection of system design problems available.

3. Low-Level Design (LLD): The Hidden Interview Round

LLD interviews often catch candidates off guard. If your object-oriented design skills are rusty, here's how to sharpen them fast.

Best Resources for Low-Level Design

1. "Head First Design Patterns" (2nd edition)

Start here. This book explains core design patterns through simple, practical examples. It's approachable even if you're revisiting the material after years away.

2. Object-Oriented Design Interview: An Insider's Guide

Co-authored by Desmond Zhou, Fawaz Bokhari, and Alex Xu (yes, the System Design Interview author), this is one of the most current books on OOD interviews.

What makes it exceptional:

A no-nonsense 4-step framework for solving design problems
11 detailed examples with real interview scenarios
133 diagrams breaking down architectures and workflows

This book bridges the gap between theory and interview-ready skills better than anything else I've found.

3. OOP Concepts Must Be Crystal Clear

Brush up on fundamentals: virtual methods in C++, abstract classes vs interfaces, method overloading vs overriding, method hiding. These are building blocks interviewers expect you to know cold.

4. Practice Real Questions

Check out Awesome Low-Level Design by Ashish Pratap Singh. It's a curated list of top-notch LLD problems that'll push you to think critically. Subscribe to his AlgoMaster newsletter for ongoing tips.

5. Timebox Your Practice

When practicing, limit each design problem to 45 minutes. Simulating interview pressure helps you focus and sharpens your decision-making under constraints.

6. Study Detailed Solutions After Your Attempt

Explore this Low-Level Design playlist (credits to Soumyajit Bhattacharyay). Walk through solutions only after you've made your own attempt — don't short-circuit the learning.

4. Computer Science Fundamentals: The Overlooked Foundation

Many candidates skip CS fundamentals in interview prep — big mistake. A lot of interview questions are rooted here, and these topics give you confidence when explaining concepts under pressure.

What to Cover

1. Core CS Concepts with GateSmashers

Start here. Their free YouTube playlists cover data structures, algorithms, operating systems, DBMS, computer networks, and OOP. The explanations are beginner-friendly but thorough enough to refresh what you learned in school.

2. Operating Systems

OS concepts frequently appear in interviews at top tech companies. Make sure you understand:

Process management
Memory allocation
Deadlocks and threading
File systems and scheduling

Resource: Check out these 6 best operating system courses for structured learning.

3. Additional Fundamentals

Don't stop at OS. Cover:

Computer networks (HTTP, TCP/IP, WebSockets)
Database indexing and transactions
Basic compiler concepts

These areas pop up in system design and low-level design discussions more often than you'd expect.

4. Study Effectively

Treat CS fundamentals like system design: don't just read or watch. Take notes. Draw diagrams. Explain concepts out loud. Mock interviews often test how well you can articulate ideas, not just how well you understand them internally.

Here's a computer science fundamentals cheat sheet from Educative.io for quick refreshers:

5. Behavioral Interviews: The Round That Eliminates Strong Coders

Many candidates underestimate behavioral rounds. The truth is brutal: no matter how strong your coding or system design skills are, you won't clear the hiring bar without demonstrating strong communication, teamwork, and real-world problem-solving.

How to Prepare for Behavioral Interviews

1. Structure with the STAR Method

STAR (Situation, Task, Action, Result) isn't optional. It helps you present experiences clearly and logically. Interviewers don't want rambling stories — they want to see how you handled challenges, made decisions, and measured success.

2. Keep Responses Tight

Each example should fit into 4-5 sentences per STAR section. The goal is to respect the interviewer's time and stay focused. Brevity shows clarity of thought.

3. Prepare Both Long and Short Versions

Sometimes interviewers want a quick overview. Other times, they'll probe deep. Have both versions ready so you can adapt on the fly. This makes you sound polished and confident.

4. Don't Neglect Preparation

Behavioral rounds are deceptively tricky. You'll face questions about failure, conflict, leadership, ambiguity, and ethics.

Resource: The Grokking the Behavioral Interview course on Educative is a solid starting point. It provides frameworks, examples, and sample answers to help you build and polish your own stories.

5. Practice Out Loud

Writing down answers is good. Saying them out loud is essential. Record yourself, review how you sound, and refine. You'll be surprised how much smoother your answers become with just a few rounds of self-review.

6. Company-Specific Preparation: The Final Edge

Generic prep will only take you so far. Once you've covered the fundamentals, it's time to focus on company-specific patterns. Each company has quirks, preferred question types, and favored topics.

How to Prepare for Specific Companies

1. Use LeetCode Premium, AlgoMonster, or Codemia.io

AlgoMonster, Codemia.io, and LeetCode Premium's biggest advantage is their massive bank of company-tagged problems. Filter questions asked by Google, Amazon, Microsoft, or specific startups.

Focus on recent problems: Prioritize questions asked in the past 6-12 months — they reflect current hiring trends.

2. Dive into the LeetCode Explore Tab

The Explore tab offers guided learning paths covering everything from data structures to dynamic programming. These paths are structured to build skills progressively — use them when you want curriculum-style learning instead of random problem grinding.

3. Simulate Real Interviews with the LeetCode Interview Tab

Head to LeetCode's Interview tab. Select a company, choose the interview round (phone, onsite, etc.), and attempt a timed assessment that mirrors the actual interview experience.

Why this matters: This is the best way to experience solving problems under time pressure before the real thing.

4. Don't Stop at LeetCode

Explore company-specific forums on Glassdoor, Blind, or TeamBlind to read recent interview experiences. Many candidates share exact question patterns and system design prompts. You'll spot trends that give you an edge.

5. Mimic the Real Setting

When practicing, use a whiteboard or plain text editor — no autocomplete, no IDE. Set a timer and solve problems as if you're in an interview. The more realistic your practice, the calmer you'll be when it counts.

Book recommendation: For coding interview patterns, check out Coding Interview Patterns: Nail Your Next Coding Interview, particularly if you prefer reading books like I do.

The Complete Preparation Timeline

Here's a realistic timeline for comprehensive interview prep:

Phase	Focus	Duration
Foundation	DSA + Language Mastery	6-8 weeks
System Design	High-Level Architecture	3-4 weeks
Low-Level Design	OOP + Design Patterns	2-3 weeks
CS Fundamentals	OS, Networks, DBMS	2-3 weeks
Behavioral	STAR Stories + Practice	1-2 weeks
Company-Specific	Tagged Problems + Mocks	2-3 weeks

Total time: 16-24 weeks of consistent preparation

Conclusion

That's all about how to prepare for coding interviews in 2026. I know it's not easy to crack coding interviews in this competitive market, but following this systematic guide and preparing for all the important topics can significantly improve your chances.

My recommended path:

Start with either ByteByteGo (50% Off now) or DesignGurus.io All Courses Bundle for comprehensive coverage (use code GURU for 30% off)
Follow with AlgoMonster or Educative-99 for structured practice on 99 carefully selected problems
Supplement with company-specific prep on LeetCode or AlgoMonster

Additional Resources:

I hope these tips help you in your preparation. Feel free to reach out if you have any questions or need guidance.

Good luck on your interview journey!

P.S. — The difference between candidates who land offers and those who don't isn't talent. Its structure. Follow this guide, stay consistent, and trust the process. You've got this.

I Tested 20+ Python Courses on Udemy: Here are 5 Courses I Recommend for 2026

2026-03-11T07:58:00.000-07:00

Hello Devs, Python remains one of the most in-demand programming languages across industries --- whether you're automating workflows, analyzing data, building web apps, or diving into AI and machine learning. But learning Python effectively depends a lot on who teaches you or what kind of course you choose. Over the years, I've taken dozens of Python courses on Udemy, and I've learned that some instructors consistently stand out for their teaching clarity, project-based approach, and regular course updates. In this article, I'll introduce you to five of the best Udemy courses and their instructors to learn Python from in 2026.

Whether you're just getting started or looking to master advanced topics, these instructors and their courses have been tailored for every level.

Another key thing I want to share with you is that when you learn from multiple instructors, you learn better. Every instructor has their own way of explaining things, and for one reason or another, when you learn from multiple folks, eventually things fall in place.

That's why I prefer to join multiple courses and learn from more than one instructor, more often than not

I Tried 20+ Python Courses: These 5 Udemy Instructors Are Actually Worth It

Without any further ado, here are the top 5 teachers you can join to learn Python programming online in 2026. Most of these teachers offer Udemy courses, which you can join for an affordable price.

1. Dr. Angela Yu's 100 Days of Code: The Complete Python Pro Bootcamp for 2026

Angela Yu's 100 Days of Code with Python is one of the most popular and engaging Python courses on Udemy.

While many instructors focus on tutorials, Angela emphasizes real-world projects that simulate actual development work, such as building web apps, games, automation tools, and more.

Her pacing is perfect for both beginners and intermediate developers.

What I love most is how her teaching style encourages you to build things every single day, which keeps motivation high and improves retention.

If you want to learn from Angela Yu, you can join her100 Days of Code: The Complete Python Pro Bootcamp for 2026

2. Jose Portilla's Complete Python Bootcamp From Zero to Hero in Python

Jose Portilla is one of the most trusted names on Udemy when it comes to Python. His flagship Python Bootcamp is a top-rated bestseller with over 1.5 million students enrolled.

What makes Jose's teaching stand out is how he breaks down complex topics into manageable, engaging lessons.

He combines theory with hands-on exercises, quizzes, and mini-projects to help you internalize concepts.

Whether you're a total beginner or brushing up on fundamentals, Jose's clear explanations and practical teaching style make learning Python both fun and effective.

Here is the link to join Jose's Python course --- Complete Python Bootcamp From Zero to Hero in Python

3. Colt Steele' The Modern Python 3 Bootcamp

Colt Steele is known for creating comprehensive beginner-friendly courses, and his Python Bootcamp is no exception.

If you're intimidated by coding, Colt's approach will put you at ease.

He uses analogies, visuals, and step-by-step instructions to make even the most technical concepts accessible.

What sets his course apart is the focus on best practices, clean coding, and real-world tools like Git, virtual environments, and testing. It's a perfect starter course if you're transitioning into software development.

Here is the link to join Colt's Python course --- The Modern Python 3 Bootcamp

4. Ardit Sulce's Python Mega Course: Learn Python in 60 Days, Build 20 Apps

If you want to build practical applications while learning Python, Ardit Sulce's Python Mega Course is the way to go.

He takes you beyond just the basics by walking you through 20 projects, including web apps, data dashboards, web scrapers, and more.

Ardit's background in data science shows in the course's structure --- he emphasizes how to use Python to solve real problems.

His content is ideal for intermediate learners looking to sharpen their skills in web development and automation.

Here is the link to join Ardit's Python course --- Python Mega Course: Learn Python in 60 Days, Build 20 Apps

5. Tim Buchalka's Learn Python Programming Masterclass

Tim Buchalka brings decades of real-world experience into his teaching.

His Python Programming Masterclass covers not just syntax and logic but also dives into topics like object-oriented programming, error handling, and best practices for writing production-ready code.

What makes Tim's course valuable is the focus on software engineering principles --- perfect for those who want to transition into full-time programming roles.

He also keeps his courses well-maintained and updated with new features and tools.

Here is the link to join Tim's Python course --- Learn Python Programming Masterclass

Python Cheat Sheet for Beginners

And here is the Python cheat sheet I was talking about. Beginners can use this to learn key Python concepts quickly

Conclusion

There is no doubt that Udemy offers thousands of Python courses, but the instructor you choose can make all the difference.

The five folks have collectively taught the Python programming language to more than 5 million people, and they are among the most respected, experienced, and effective Python teachers on the platform.

Whether you're a complete beginner or an aspiring developer looking to level up, you'll find their courses engaging, practical, and career-focused.

Take some time to watch the previews, explore the course curricula, and pick the one that fits your learning style. With dedication and the right instructor, you'll be well on your way to mastering Python in 2026.

By the way, if you want to join multiple courses on Udemy, it may be worth getting a Udemy Personal Plan, which will give instant access to more than 11,000 top-quality Udemy courses for just $30 a month.

If you have a lot of time and want to save money, the Udemy Personal Plan will be perfect for you.

All the best with your Python journey !!

Top 10 Caching Strategies for System Design

2026-03-09T21:16:00.000-07:00

Disclosure: This post includes affiliate links; I may receive compensation if you purchase products or services from the different links provided in this article.

image_credit - ByteByteGo

Hello friends, In System design, efficiency and speed are paramount and in order to enhance performance and reduce response times, caching plays an important role. If you don't know what is caching? let me give you a brief overview first

Caching is a technique that involves storing copies of frequently accessed data in a location that allows for quicker retrieval.

For example, you can cache the most visited page of your website inside a CDN (Content Delivery Network) or similarly a trading engine can cache symbol table while processing orders.

In the past, I have shared several system design interview articles like API Gateway vs load balancer, Forward Proxy vs Reverse Proxy as well common System Design problem and in this article we will explore the fundamentals of caching in system design and delves into different caching strategies that are essential knowledge for technical interviews.

It's also one of the essential System design topics or concepts for programmers to know.

By the way, if you are preparing for System design interviews and want to learn System Design in depth then you can also checkout sites like ByteByteGo, InterviewKickStart, Design Guru, Exponent, Educative, Codemia.io, Bugfree.ai and Udemy which have many great System design courses

P.S. Keep reading until the end. I have a free bonus for you.

What is Caching in Software Design?

At its core, caching is a mechanism that stores copies of data in a location that can be accessed more quickly than the original source.

By keeping frequently accessed information readily available, systems can respond to user requests faster, improving overall performance and user experience.

In the context of system design, caching can occur at various levels, including:

Client-Side Caching
The client (user's device) stores copies of resources locally, such as images or scripts, to reduce the need for repeated requests to the server.
Server-Side Caching
The server stores copies of responses to requests so that it can quickly provide the same response if the same request is made again.
Database Caching
Frequently queried database results are stored in memory for faster retrieval, reducing the need to execute the same database queries repeatedly.

Here is a diagram which shows the client side and server side caching:

9 Caching Strategies for System Design Interviews

Understanding different caching strategies is crucial for acing technical interviews, especially for roles that involve designing scalable and performant systems. Here are some key caching strategies to know:

1. Least Recently Used (LRU)

This type of the cache is used to Removes the least recently used items first. You can easily implement this kind of cache by tracking the usage of each item and evicting the one that hasn't been used for the longest time.

If asked in interview, you can use doubly linked list to implement this kind of cache as shown in following diagram.

Though, in real world you don't need to create your own cache, you can use existing data structure like ConcurrentHashMap in Java for caching or other open source caching solution like EhCache.

2. Most Recently Used (MRU)

In this type of cache the most recently used item is removed first. Similar to LRU cache, it requires tracking the usage of each item and evicting the one that has been used most recently.

3. First-In-First-Out (FIFO)

This type of cache Evicts the oldest items first. If asked during interview, you can use use a queue data structure to maintain the order in which items were added to the cache.

4. Random Replacement

This type of cache randomly selects an item for eviction. While this type of cache is simpler to implement, but may not be optimal in all scenarios.

5. Write-Through Caching

In this type of caching, Data is written to both the cache and the underlying storage simultaneously. One advantage of this type of caching is that it ensures that the cache is always up-to-date.

On the flip side write latency is increased due to dual writes.

6. Write-Behind Caching (Write-Back)

In this type of caching, Data is written to the cache immediately, and the update to the underlying storage is deferred.

This also reduces write latency but the risk of data loss if the system fails before updates are written to the storage.

Here is how it works:

7. Cache-Aside (Lazy-Loading)

This means application code is responsible for loading data into the cache. It provides control over what data is cached but on the flip side it also requires additional logic to manage cache population.

Cache Invalidation

Along with caching and different caching strategies, this is another important concept which a Software engineer should be aware of.

Cache Invalidation removes or updates cache entries when the corresponding data in the underlying storage changes.

The biggest benefit of cache invalidation is that it ensures that cached data remains accurate, but at the same time it also introduces complexity in managing cache consistency.

And, here is a nice diagram from DeisgnGuru.io which explains various Cache Invalidation strategies for system design interviews

Global vs. Local Caching

In global caching, a single cache is shared across multiple instances. In local caching, each instance has its own cache. One of the advantage of Global caching is that it promotes data consistency and Local caching reduces contention and can improve performance.

Best System Design Interview Resources

And, here are curated list of the best system design books, online courses, and practice websites which you can check to better prepare for System design interviews. Most of these courses also answer questions I have shared here.

ByteByteGo: A live book and course by Alex Xu for System design interview preparation. It contains all the content of the System Design Interview book volumes 1 and 2, and will be updated with volume 3, which is coming soon.
Codemia.io: This is another great platform to practice System design problems for interviews. It has more than 120+ System design problems, many of which are free, and also a proper structure to solve them.
Bugfree.ai: Thisi is another popular platform for technical interview preparation. It contains AI-based mock interviews as well as Interview experience and more than 3200+ real questions on System Design, Machine Learning, and other topics for practice =.
DesignGuru's Grokking System Design Course: An interactive learning platform with hands-on exercises and real-world scenarios to strengthen your system design skills.
"System Design Interview" by Alex Xu: This book provides an in-depth exploration of system design concepts, strategies, and interview preparation tips.
"System Design Primer" on GitHub: A curated list of resources, including articles, books, and videos, to help you prepare for system design interviews.
Educative's System Design Course: An interactive learning platform with hands-on exercises and real-world scenarios to strengthen your system design skills.
High Scalability Blog: A blog that features articles and case studies on the architecture of high-traffic websites and scalable systems.
YouTube Channels: Check out channels like "Gaurav Sen" (ex-Google engineer and founder of InterviewReddy.io and "Tech Dummies" for insightful videos on system design concepts and interview preparation.
"Designing Data-Intensive Applications" by Martin Kleppmann: A comprehensive guide that covers the principles and practices for designing scalable and reliable systems.
Exponent: A specialized site for interview prep, especially for FAANG companies like Amazon and Google. They also have a great system design course and many other materials that can help you crack FAANG interviews.

image_credit - ByteByteGo

Conclusion:

That's all about caching and different types of cache a Software engineer should know. As I said, Caching is a fundamental concept in system design, and a solid understanding of caching strategies is crucial for success in technical interviews.

Whether you're optimizing for speed, minimizing latency, or ensuring data consistency, choosing the right caching strategy depends on the specific requirements of the system you're designing.

As you prepare for technical interviews, delve into these caching strategies, understand their trade-offs, and be ready to apply this knowledge to real-world scenarios.

Bonus
As promised, here is the bonus for you, a free book. I just found a new free book to learn Distributed System Design, you can also read it here on Microsoft --- https://info.microsoft.com/rs/157-GQE-382/images/EN-CNTNT-eBook-DesigningDistributedSystems.pdf

The 2026 Java Software Developer RoadMap (with Resources)

2026-03-08T00:50:00.000-08:00

Hello guys, if you want to become a professional Java developer or want to take your Java skill to the next level but are not sure which technology, tools, frameworks, and library you can learn then you have come to the right place.

Earlier, I have shared the best Java courses, books, and websites and in this article, I am going to share a complete Java programmer RoadMap, which will tell you what it takes to become a professional Java developer and provide a comprehensive overview of all the tools, libraries, frameworks and skills you need to become a complete Java programmer in 2026.

I have been sharing a lot of roadmaps like a Web developer RoadMap, DevOps engineer RoadMap, and React.js developer RoadMap and one of the requests I received from many of my readers was for creating a Java Developer Roadmap.

Since Java is my expertise, It wasn’t a problem to create a Java Developer Roadmap, but it took slightly longer for me to create one because of the limited time I had.

Anyway, I am finally ready to share my Java developer RoadMap with you. This Roadmap contains my years of experience and the unobstructed path of how to become a Java expert.

You will find that this Java roadmap answers many burning questions like which technologies a Java developer should learn. What tools make you a better Java developer? And, which framework a Java developer must absolutely learn.

One of the things I tried with this roadmap is to keep the exposure as short as possible, I have avoided mentioning many alternatives, particularly when it comes to libraries and tools, and stick with industry-standard tools and libraries.

I have kept it simple so that most of the people can follow it and only included the essential stuff, but if there is enough desire, I am thinking of posting The Java Developer RoadMap 2.0 to add some advanced things like JVM internals, Profiling, Java 9 Modules, Cloud Native Java, different cloud platforms like AWS, GCP, or Azure, and more advanced tools like Chef for DevOps and much more.

If you are interested, you can find a more exhaustive list of separate blog posts, which I have listed in the further learning section. Anyway, let’s go through this Java Developer RoadMap to understand how to become a Java developer in 2026.

Btw, you by no means need to understand everything on this roadmap to become a rockstar developer.

You don’t even need to take them that seriously if you don’t want to. Instead, use these maps as a starting point to help guide your learning as you go.

Mandatory skill for any Java developers

Now, let’s go through this Java developer RoadMap step by step and find out how you can learn the essential skills required to become a Java Developer in 2026:

1. Git & GitHub

One of the most popular version control systems. It’s just not possible to live without Git anymore.

As a programmer, you should be familiar with Git and Github, essential Git concepts like a branch, master, checkout, checking, push, and pull, as well essential Git commands like git diff, git commit, etc.

I highly recommend Java programmers to learn Git and Github and if you already worked with Git then you can also level up your Git skills If you need a resource then you can check out The Git Complete Guide on Udemy to start with.

2. Linux

Not just a web developer but for any programmer, the Linux command line is very, very important, and I strongly recommend you to spend some time learning them.

Since most Java applications are server-side, you will often find them running on Linux servers.

That’s why it’s imperative for Java developers to be familiar with essential Linux concepts and commands related to files, disk space checking, process management, as well as networking commands.

If you need a resource to level up your Linux skills, I recommend checking out Linux Mastery: Master the Linux Command Line in 11.5 Hours course on Udemy. This is a great course for anyone who wants to learn Linux commands from scratch.

If you need more resources then you can use these free Linux courses to start learning Linux.

3. Data Structures and Algorithms

These are the building blocks of any program, and a good knowledge of Algorithms and Data Structure is vital for your next job or doing well in your current situation.

You should at least be familiar with essential data structures like an array, linked list, hash table, binary tree, queue, stack, and graph as well as problem-solving techniques like dynamic programming.

If you know advanced data structures like Trie, B-Tree, and AVL tree, then it’s well and good. But, if you don’t know, then I suggest you join a comprehensive course like Data Structures and Algorithms: Deep Dive Using Java, which will teach you everything about all those fundamentals.

4. HTTP / HTTPS

The HTTP protocol is the backbone of the web, and a good knowledge of both HTTP and HTTPS is mandatory for a web developer.

At least you should know about how HTTP and HTTPS work and what are different HTTP methods and their purposes etc.

If you need resources, you can also see these HTTP, SSL, and TLS courses to start with/

5. Computer Science Fundamentals

If you are creating global applications that show information in many different languages across the world, then you should have a good knowledge of character encodings.

It basically tells your browser how to show your data. If you want to learn more about Computer Science, you can also check out Introduction to Computer Science and Programming Specialization by the University of London.

It’s a 3-part course on Computers, Programming, and Mathematics and essential for all kinds of programmers including Java developers. More than 39K people have already benefited from this program.

6. SQL

This is another common tech skill that every Java developer should learn as it will help you to troubleshoot back-end issues.

If you know SQL you can understand the stored procedure, query the database, and find out whether the issue is in the Java layer or the Database layer.

I highly recommend every Programmer whether a Java developer or a Python developer to learn SQL, it’s one of those skills that are easy to learn and serve you for a long time in your career as a programmer or developer.

If you need a resource, I suggest looking at the Complete SQL + Databases Bootcamp: Zero to Mastery course by Andrei Negaoie on ZTM Academy.

Complete SQL + Databases Bootcamp: Zero to Mastery

Most comprehensive resource online to learn SQL and Database Management & Design + exercises to give you real-world…

academy.zerotomastery.io

Btw, you would need a ZTM membership to join this course which costs around $39 per month but also provides access to many super engaging and useful courses like his Java Programming Bootcamp: Zero to Mastery, which is a great resource to learn Java in-depth. You can also use my code FRIENDS10 to get a 10% discount on any subscription you choose.

Java Bootcamp: Learn Java. Become a Backend Developer. Get Hired | Zero To Mastery

The only Java Bootcamp you need to go from complete programming beginner to learning Java from scratch and being able…

academy.zerotomastery.io

7. Design Patterns

There is no doubt that every programmer should know Git and Github as they are the standard in terms of version control and code repository.

If you want to learn and master Design Patterns, particularly OOP Design patterns then I suggest you join the Design Patterns in Java course by Dmitri Nestruk on Udemy.

This is a great course to learn the modern implementation of classic design patterns in Java.

If you need more resources, you can also check out my earlier articles about the best design patterns books, and courses to learn Object-Oriented Design patterns in depth.

The 2026 Java Developer RoadMap (with Resources)

Now, let’s explore this Java developer roadmap together and find out what tools, frameworks, libraries, APIs, tools, and skills you can learn to become a professional Java developer in 2026.

1. Tools

The tools section is divided into different sections. First, your IDE, which is your primary tool and can do almost everything you asked for like compile, run, debug, profile, test, compare files and code, refactoring, and much more.

1.1 IDEs

For Java Developers, there are two main IDES, Eclipse and IntelliJIDEA, you can choose any one of them as I have used Eclipse most of my life but I am currently working in IntelliJIDEA so I love both of them, but most Java developers I know they work in IDEA.

I suggest you master IDEA shortcuts, views, and all other features it offers to become a true Java Master and if you need a resource, I think IntelliJ IDEA Tricks to Boost Productivity for Java Devs is a great place to start with.

1.2 Build Tools

The second part is the build tool, which you need to build and deploy your projects like Maven and Gradle.

Any one of these would be enough. I have just listed ANT, but that’s for legacy projects.

For all new Java projects, prefer Gradle, it’s much more concise than Maven.

If you want to learn both Maven and Gradle, there are not many resources available. If you ask me, I recommend Apache Maven: Beginner to Guru by John Thompson on Udemy.

And, if you are keen to learn Gradle, I suggest you check out Gradle for Java Developers by another great Udemy instructor, Bharat Thippireddy.

1.3 Containers and DevOps Tools

And, the third and most crucial part includes containers like Docker and Kubernetes, CI/CD tools like Jenkins and TeamCity, and Infrastructure automation tools like Chef, Puppet, and Ansible.

Out of these Docker is the most important because it makes it easy to set up your development environment as well as it also makes the Deployment of Java Microservices easier.

Kubernetes is a next-level tool and not really needed for all Java developers, particularly if you are not in DevOps and managing things like scaling and deployment but it’s good to know from a knowledge perspective.

I suggest having good knowledge of Docker and basic knowledge of Kubernetes for Java developers and if you need resources, I recommend Maximillian SchwaurzMuller’s Docker & Kubernetes: The Practical Guide course on Udemy. You can learn both of these tools in one course.

If you are interested in learning about these tools, here are some useful courses to learn to build tools and IDEs

2. Java APIs

The next important thing to learn is JDK APIs, which are very, very important for any Java developer. This is quite a big section, and that’s why it’s divided into core areas like Java Collections framework, Java Concurrency, Java IO, and Java 8 APIs, let’s explore each of them

2.1 Java Collections Framework

This is one of the most essential Java APIs every Java developer should learn. This API provides implementations of standard data structures in Java-like linked lists, sets, stacks, queues, hash tables, priority queues, and others.

At least you should know about all everyday objects like ArrayList, HashMap, HashSet, LinkedHashSet, TreeSet, etc.

Each of them has its different properties, for example, ArrayList is a dynamic array that can grow, and HashMap is a standard implementation of the hash table and can be used to store key-value pairs.

Similarly, HashSetis a set implementation that doesn't allow duplicate elements. I strongly suggest you check the Java Fundamentals: Collections course to learn Java Collection Framework in depth.

2.2 Java Concurrency

After Java Collections, the next, most crucial API in Java is about multi-threading and concurrency, and I firmly believe that if you want to be a competent Java developer, you must have a solid understanding and command of Java Concurrency API.

You should not only have an in-depth understanding of fundamental concepts like Thread, Runnable, Object locking, and Synchronization, but you should also be familiar with concepts like deadlock, livelock, race conditions, and how to deal with them.

You should also learn about advanced Java concepts like synchronizers added on Java 5 and subsequent versions, I mean CyclicBarrier, CountDownLatch, Phaser, and CompleteableFuture, etc., along with Futures and how to perform the async operation in Java.

I know, it’s a lot of stuff, and that’s why I suggest you join an in-depth course like Java Concurrency in Practice bundle from Heinz Kabutz, a Java Champion, and authority when it comes to concurrency and design patterns. This course is a bit expensive, but you will learn a lot more concepts in-depth, which makes it completely worth your time and money.

On the other hand, if the price is an issue, you can also check this Udemy course — — Concurrency, Multithreading, and Parallel Computing in Java which won’t cost you more than $10 if you get it on Udemy flash sales which happens every month. This is also an excellent course to learn Java concurrency and multithreading in Java.

Java Concurrency in Practice Bundle

Courses relevant to concurrency

learning.javaspecialists.eu

2.3 Java IO

I have interviewed more than 100+ Java programmers, and I have noticed one pattern; they all have very little knowledge of Java IO and NIO APIs as compared to Java Collections and Java Multithreading API.

I can understand that many people spend a lot of time learning those two APIs, but you cannot leave behind these critical APIs.

If you have to code a real-world, core Java application, you will need to use classes like File, InputStream, OutputStream, Reader, Writerfrom the java.io package, which is the core of the Java IO API.

Similarly, you also need to know about ByteBuffer, FileChannel, Selector, and other critical classes from java.nio API, if you want to write a socket-based application.

Unfortunately, there are not many dedicated resources on teaching Java IO and Java NIO API, but The Complete Java Masterclass is a great resource to master this API. You will find a lot of essential concepts from this API in this course.

2.4 Java 8 Features

Now, the next and another necessary API, a Java programmer, should learn is the Java 8 features, which has completely changed the way Java is coded and programmed nowadays.

To become a Java developer in 2026, you must know how to use a Lambda expression, Stream API, Optional classes, and a new Date and Time API.

Without knowing these APIs, it would be very tough to write a Java application in 205.

Most of the libraries also now stop supporting versions lower than Java 8, which means you have to learn Java 8 features now rather than later. It’s already 5 years since Java 8 was released, so you literally have no excuse left.

When it comes to learning Java 8 features, there are a lot of excellent resources available in the market.

Still, if you already know Java, I suggest you choose a resource that only focuses on Java 8 features like the Java 8 for Experienced Developers: Lambdas, Stream API & Beyond course on Educative. This way, you can learn Java 8 in no time.

While Java 8 features are essential for Core Java developers, if you can, please learn all other new features introduced from Java 9 to Java 13 like Modules, varfor local variables, static factory methods for collections, Text Blocks, Strings in Switch, and many more.

If you need more resources, you can check out this list of courses to learn all the new Java features in 2026.

3. Frameworks

The best thing about Java is that it has a vibrant ecosystem, which means there are a lot of frameworks and libraries for almost anything.

Usually, I don’t suggest a Java developer learn a framework until he needs to use it in his project.

Still, there are some frameworks and libraries, which I believe every Java developer should know like Spring, Spring Boot, Hibernate, Log4j, JUnit, etc.

3.1 Spring Framework

If you want to become a Java developer in 2026, I strongly recommend you to learn Spring Framework first.

This is one of the most popular Java frameworks, and literally, almost every single Java application I have worked on in the last 5 years, uses this framework.

Spring Framework encourages writing clean code, which is easier to test and maintain by providing you with features like Dependency Injection and Inversion of Control.

It also has a rich API for most of the day-to-day tasks, and that’s why every Java developer should learn the Spring framework.

And, if you want to learn the Spring Framework, there is no better course than Spring Framework 6: Beginner to Guru. It covers Spring 6, the latest version of Spring 6, and teaches Spring in a more hands-on way than any other course.

3.2 Hibernate

The second framework that I recommend every Java developer to learn is Hibernate, which is based on JPA (Java Persistence API).

To be accurate, Hibernate came before JPA, but because JPA is a standard API to implement the persistence layer in Java, Hibernate implements it.

Now, why should you learn Hibernate? Well, because most of the Java applications you will work with will interact with databases, it’s excruciating to deal with databases in Java using JDBC and without a proper framework like Hibernate.

It provides some of the essential features like Caching and Transaction out-of-the-box, which means you have more time to focus on your application logic than implementing caching in your application.

This seriously improves the performance of Java applications, and so far, my most significant reason to use Hibernate.

Now, when it comes to learning Hibernate there are many great resources available in the market, but the Spring & Hibernate for Beginners course is my preferred one because you can kill two birds from one stone, you can learn both Spring and Hibernate in one class rather than joining separate courses for them.

Btw, if you truly want to master Hibernate or looking for an advanced Hibernate course then Vlad Mihalcea’s High-Performance Java Persistence book and the course are the best resources for anyone.

High-Performance Bundle

A high-performance data access layer must resonate with the underlying database system. Knowing the inner workings of a…

vladmihalceastore.teachable.com

3.3 Spring Boot

This is another framework I recommend every Java developer to learn in 2026 and going forward. Spring Boot took Spring’s philosophy of simplification and made it easy to work with Spring itself.

Just like Spring makes it easier to create a Java application, Spring Boot makes it easier to create a Spring-based Java application.

Features like auto-configuration take away most of the pain associated with configuring the Spring application. Similarly, starter POM features grouped commonly used dependencies into simple reusable POMs.

Now, if you want to learn Spring Boot, I strongly suggest you go through the Learn Spring Boot in 100 Steps course; it’s one of the best and most up-to-date and also provides step-by-step guides for everyday things a Spring Boot developer needs to know.

3.4 Java Microservice Frameworks — — MicroProfile, Micronaut, and Quarkus

While learning Spring Boot and Spring Cloud is sufficient for developing Microservices in Java, there are a couple of more advanced frameworks you can explore, like Eclipse’s Microprofile, Micronaut, and Quarkus.

3.4.1 Quarkus

Quarkus is one of the promising frameworks for Java developers. It’s a Kubernetes Native Java stack tailored for OpenJDK HotSpot and GraalVM, crafted from the best-of-breed Java libraries and standards.

Quarkus tailors your application for GraalVM and HotSpot to get Amazingly fast boot time and incredibly low RSS memory (not just heap size!).

It also provides instant scalability and high-density memory utilization in container orchestration platforms like Kubernetes using a technique called compile-time boot.

You can also use both the familiar imperative code and the non-blocking reactive style when developing applications for Quarkus.

In short, one of the best platforms for Java developers to create an application and something worth learning in 2026, and if you want to learn Quarkus and need a resource then Quarkus Backend development with Java and GraalVM is a great one to start with.

3.4.2 Eclipse Microprofile

It’s an initiative that aims to optimize Enterprise Java for Microservice Architecture. It’s driven by Eclipse, one of the leading organizations of Java, and the company behind the popular Eclipse IDE.

The goal of Eclipse of MicroProfile is to define standard APIs for building microservices and deliver portable applications across multiple MicroProfile runtimes.

The current version of Eclipse Microprofile is 7.0, and it’s a useful Java framework to learn in 2026.

Press enter or click to view image in full size

3.4.3 Micronaut

This is another Java framework you can learn in 2026. Micronaut is a modern, JVM-based, full-stack framework for building modular, easily testable microservice and serverless applications.

It’s a polyglot framework and allows you to create an application using Java, Kotlin, or Groovy. Some of the key talking points of Micronaut are reduced startup time, blazing-fast throughput, and minimal memory footprint.

If you want to learn more about MicroNaut, you can also check out Learn Micronaut — — cloud-native microservices with Java course on Udemy. There are not many courses but this one and MicroNaut documentation are sufficient to start developing applications with MicroNaut.

4. Testing

Testing is an essential skill for any Java developer, particularly unit testing, integration testing, and automation testing.

At the bare minimum, every Java developer should be familiar with JUnit and Mockito, two of the most popular Unit testing and Mock libraries.

If you know these two and know how to use them to effectively create a unit test, you will be a much better Java developer than without them.

There are more advanced libraries that also exist like Cucumber for Business-driven testing and Robot Framework for integration testing, but there is no substitute for JUnit, you will always need that.

When it comes to a mocking library, you have a couple of choices like PowerMock, Mockito, and EasyMock.

Still, I strongly suggest you learn Mockito because it’s a vast library, and also many Java developers and companies are doing that. It is slowly becoming the standard library for creating mock objects in Java.

If you want to learn JUnit and Mockito from scratch, then I also suggest you join Learn Java Unit Testing with Junit & Mockito in the 30 Steps course by In28Minutes on Udemy. It’s a practical and hands-on course to get started with both these libraries.

If you need more options than you I have already shared a lot of resources like books and courses, you can check those to learn more.

5. Utility Libraries

The real power of Java lies in its vibrant ecosystem of open-source libraries. You will find libraries to do almost anything in Java from logging to machine learning, from sending an HTTP request to parsing JSON, and much more.

Apart from that, Java is also lucky to have utility libraries like Apache Commons and Google Guava, these two libraries effectively complement JDK libraries. I have also shared a list of 20 Java APIs and libraries for Java developers.

I suggest you go through that list, chances are that you already have half of them but if you don’t learn them they are very, very useful and help you to write better Java programs and deliver faster.

6. Database

Database access is an important part of many Java applications and thankfully Java comes with JDBC (Java Database Connectivity) API Which provides a standard set of APIs for connecting to any relational database.

As an application developer, you just need to know the API as all vendors provide an implementation of those APIs. You just need to include their JAR file into the classpath and your code will work fine.

By the way, JDBC is not the only option to interact with the database, there are open-source libraries like JOOQ that can help you to write SQL queries in Java.

jOOQ generates Java code from your database and lets you build type-safe SQL queries through its fluent API

7. Desktop and Frontend

Java offers great APIs like Swing and Java FX for developing GUI clients. Swing was popular a couple of years back but C# has now taken the lead Java FX is another popular Java API for developing GUI applications in Java.

If you want to develop a GUI application like NetBeans, one of the famous Java editors which are also written in Java then you can learn Java FX in 2026.

I wouldn’t advise learning Swing unless you are working for a bank that is paying you thousands of dollars per month maintaining their Swing-based trading GUI.

If you want to learn Java FX in 2026 and need a resource then you can also check out the Java FX Concepts Bootcamp 2026 course on Udemy.

You can also build and deploy Java FX applications on Raspberry PI, one of the small but powerful computers. If you are interested in that,Frank Delporte has a great course Use Java and Java FX on a Raspberry PI for beginners. You can take a look at that course to start with.

Best Resources to Learn Java Programming in 2026

Now that we know in depth what individual skills, tools, and libraries are used in the Java world and what you can learn to become a professional Java developer, it is now time for the most important thing in this RoadMap, the resources to actually learn Java programming.

So, here are the best resources which include, online courses, books, and online platforms you can join to learn Java programming in depth.

1. Best Java Online Courses

Online Courses are one of the best ways to start learning any new technology or programming language and Java is no exception.

There are thousands of Java courses available online but not everything is good. Many of them are outdated or don’t cover Java in enough depth.

So, I have shortlisted the following Java programming courses anyone can join to start with Java programming language, it includes courses from popular learning platforms like Udemy, Coursera, Educative, Zero to Mastery Academy, and more:

Now that we have seen all the important online Java courses, it’s time to check the books as they also play an important role in shaping a Java developer’s career.

Btw, if you need more references, you can also see this list of free Java courses and best places to learn Java, both have useful references for Java developers

Java Programming and Software Engineering Fundamentals

Offered by Duke University. Explore a Career as a Software Engineer. Learn the basics of programming and software…

coursera.pxf.io

2. Best Java Books for Beginners and Experienced

When I started learning Java, I started with books that were very hard to read, lengthy, and boring but they had computer programs that I could copy and run.

At that time, I mean during the 1990s and early 2000s that’s probably the best way to learn Java but nowadays you have access to so many resources like interactive coding websites and courses which I have shared in the previous section so you don’t need to read those boring books.

Instead, you can pick interesting books to learn and master Java like the one I have shared below:

That’s all about the 2026 Java Programmer and Developer Roadmap. This is an excellent resource to learn Java in 2026 and become a better Java developer. I have kept it simple so that most people can follow it and only included the important stuff.

Java is vast and still, there are a couple of areas that I haven’t touched like messaging but if there is enough desire, I am thinking to post The Java Developer RoadMap 2.0 to add some advanced things like JVM internals, Profiling, Modules, Cloud Native Java, Containers, Messaging, JNI, and much more.
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All the best for your Java Development Journey !!

P. S. — If you are a complete beginner in Java and looking for a free online course to learn Java online then you can also check out the Java Tutorial for Complete Beginners(FREE) course on Udemy. It’s completely free and more than 1.2 million people have joined this course to learn Java online.

And, if you are not a subscriber, you can also subscribe to our substack Newsletter here.

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The Ultimate DevOps Engineer RoadMap

2026-03-06T06:48:00.000-08:00

image_credit — educative

Hello guys, DevOps and SRE are really hot at the moment and most of my friends, colleagues, and senior developers I know are working hard to become a DevOps engineers and project themselves as DevOps champion in their organization.

While I truly acknowledge the benefits of DevOps, which is directly linked to improved software development and deployment, from my limited experience I can say that it’s not an easy job. It’s very difficult to choose the right path in the middle of so many tools and practices.

Being a Java blogger, many of my readers often ask me questions like how to become a DevOps engineer, which tools should I learn? which practices should I follow?

does learning Maven and Jenkins must be for a DevOps guy? how about Docker and Kubernetes? Does the infrastructure automation part of DevOps? should I learn Chef, Puppet, or Ansible are just some of those questions which keep coming to me.

I have tried hard to answer those with my minimal experience but I couldn’t jot them down in a manner that is simply awesome and reusable, but, not to worry.

Today I am going to share with you an awesome resource that will help you to become the DevOps Engineer you always wanted to be, The 2026 DevOps RoadMap.

I was casually surfing through the internet yesterday when I come across this excellent GitHub page by Kamranahmedse, which shows a couple of useful roadmaps to become a front-end developer, back-end developer, a full-stack web developer, and last but not the least, the DevOps Engineer.

This RoadMap is awesome in any sense as it does not only highlight what is the role of a DevOps engineer but also tells which tools and technologies you need to learn to cover that area.

On top of that, it’s visually appealing with nice colors(don’t you like yellow and cream with blue lines?), so you can just take a printout and stick in your desk for easier reference.

Though the roadmap is good in the sense that it tells you what to learn but it doesn’t tell you how to learn and where to learn. In order to complete the roadmap, I have shared some useful online DevOps courses, both free and paid, so that you can learn and improve the tools or areas you want.

The 2026 DevOps RoadMap for Developers

Anyway, here is the 2026 DevOps RoadMap I am talking about:

Image by kamranahmedse (https://github.com/kamranahmedse/developer-roadmap)

Now, let’s go through the RoadMap step by step and find out how you can learn the essential skills required to become a DevOps guru in 2026:

1. Learn a Programming Language

Obviously and I assume you guys definitely know one of the three main programming languages i.e. Java, Python, or JavaScript.

If you didn’t, don’t worry you can take a look at the below courses to learn your choice of language, though I strongly suggest you learn at least one of these three major general-purpose programming languages.

1.1 Java

If you want to learn Java then The Complete Java MasterClass is a great course, which is also recently updated for Java 10.

1.2 Python

If you want to learn Python, then The Complete Python BootCamp is my favorite resource, which will teach you Python 3, the most popular version of Python.

1.3 JavaScript

And, if you want to learn JavaScript then you should not look beyond Mosh Hamdani’s JavaScript Basics for Beginners course on Udemy.

If you need more choices and don’t mind learning from free resources then you can always take a look at my list of free Java, Python, and JavaScript courses.

2. Understand different OS concepts

This is where the Ops part came in, earlier it was solely supported by guys and sysadmin people who were responsible for knowing about OS and hardware, but with DevOps, now the developer also needs to know them.

You at least need to know about Process Management, Threads and Concurrency, Sockets, I/O Management, Virtualization, Memory storage, and File systems as suggested in the roadmap.

Since most of us work in Linux, I suggest you go through the Linux Administration BootCamp course on Udemy to learn and understand Linux OS better.

If you need more choices and you don’t mind learning from freely available resources then you can also take a look at this list of free Linux courses.

3. Learn to Live in terminal

For a DevOps guy, it’s important to have good command in the command line, particularly if he is working in Linux.

Knowing some Linux shell like Bash, or Ksh and tools like find, grep, awk, sed, lsof, and networking commands like nslookup and netstat is mandatory.

If you feel you need to refresh these commands and tools then you should join the Tools of the Trade: Linux and SQL course from Google on Coursera, its free to audit.

By the way, If you are planning to join multiple specializations, then consider taking a Coursera Plus subscription which provides you unlimited access to their most popular courses, specialization, professional certificate, and guided projects.

Btw, If you need more choices and want to become a master of shell scripting, you can also take a look at my list of best courses to learn shell scripting.

4. Networking and Security

Gone are the days of isolation, in today’s world, everything is connected to everything which makes networking and security very important.

In order to become a good DevOps engineer, you must know about basic networking and security concepts like DNS, OSI Model, HTTP, HTTPS, FTP, SSL, TLS, etc.

In order to refresh this concept, you can take a look at TCP/IP and Networking Fundamentals for IT Pros By Ed Liberman course on Pluralsight.

If you need more choices, you can also check out these Udemy courses like for Networking, The Complete Networking Fundamentals is a nice course and for Security, you can also check The Complete Cyber Security Course: Network Security!.

5. What is and how to setup

As a DevOps champion, you should know what is set up in your machine and how you can set that up, only that you can think about automating it.

In general, a DevOps engineer should know how to set up a Web Server like IIS, Apache, and Tomcat.

He should also know about Caching Server, Load balancer, Reverse Proxy, and Firewall, etc.

If you are new into the web development space, I suggest you to also check out the Web Developer Bootcamp by Colt Steele

6. Learn Infrastructure as code

This is probably the most important thing for a DevOps engineer and this is a very vast area as well.

As a DevOps engineer, you should know about containers like Docker and Kubernetes, Configuration management tools like Ansible, Chef, Salt, and Puppet, Infrastructure Provisioning like Terraform and Cloud formation.

Here are some of my recommended courses to learn these tools.

If you want to learn Docker then the Docker Mastery: The Complete ToolsetFrom a Docker Captain course on Udemy is the best course to start with. It provides comprehensive coverage of all the tools a DevOps engineer will need.

If you want to learn Kubernetes then I suggest you join the Learn DevOps: The Complete Kubernetes course. This will teach you how to build, deploy, and manage Kubernetes.

And, if you want to learn Chef then there is no better course then Chef Fundamentals: A Recipe for Automating Infrastructure on Udemy. Probably the best course to learn Chef at this moment.

If you need more choices on Docker, you can explore this list of 10 essential courses for DevOps engineers.

Similarly, if you want to learn Ansible then I would recommend you to checkout the Ansible for the Absolute Beginner — Hands-On DevOps course on Udemy.

This course is very hands-on and not just teach you how to read Ansible playbooks but also how to write them using YAML. You will learn how to specify key value pair and much more.

Similarly for Terraform, I would recommend Hashicorp Certified — Terraform Associate course on Udemy. In this course you will not just learn Terraform but also prepare for Hashicorp Terraform Associate exam which is not just a great way to learn Terraform in depth but also to earn a certification which is valued in DevOps world.

7. Learn some Continuous Integration and Delivery (CI/CD) tools

This is another very important thing for DevOps gurus and champions, i.e. to set up a pipeline for continuous integration and delivery. There are a lot of tools in the CI/CD area e.g. Jenkins, TeamCity, Drone, etc.

But, I strongly recommend learning at least Jenkins, as it’s the most widely used and probably the most mature CI/CD tool in the market. If you don’t know Jenkins then this course is best to start with.

If you want to learn Jenkins, then there is no better course than the classic Learn DevOps: CI/CD with Jenkins using Pipelines and Docker on Udemy. It’s simply the best course and I have also learned most of my Jenkins skills from this course.

Btw, if you need more choices and don’t mind learning from free resources then you can also check my list of 6 free Jenkins and Maven courses for Java developers.

8. Learn to monitor software and infrastructure

Apart from setup and deployment, monitoring is another important aspect of DevOps and that’s why it’s important for a DevOps engineer to learn about Infrastructure and application monitoring.

There are a lot of tools in this space e.g. Nagios, Icing, Datadog, Zabbix, Monit, AppDynanic, New Relic, etc.

You can choose some of them depending on which one is used in your company like AppDynamic and Nagios.

If you want to learn more about AppDynamic in 2026 and need a resource then I highly recommend you to check out Cisco AppDynamics Application Performance Management (APM) course on Udemy. This is a great course to learn this useful tool to monitor your software and infrastructure.

9. Learn about Cloud Providers

Cloud is the next big thing and sooner or later you have to move your application to the cloud, hence it’s important for a DevOps engineer to at least know about some of the popular Cloud Providers and their basics.

While AWS is clearly the leader in the cloud it’s not alone, Google Cloud and Azure are slowly catching up and then we have some other players like Heroku, Cloud Foundry, and Digital Ocean.

To start with I strongly suggest joining the classic AWS Serverless APIs & Apps — — A Complete Introduction course in Udemy, which is simply the best.

Btw, if you need more choices and don’t mind learning from free resources then you can also check my list of free AWS courses for developers and DevOps guys.

Other Programming Articles you may like
The 2026 Java Developer RoadMap
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10 Tips to become a better Java Developer in 2026
Top 5 Java Frameworks to Learn in 2026
10 Testing Libraries Every Java Developer Should Know
10 DevOps Courses for Experienced Developers
20 DevOps Tools You Can Learn in 2026
Top 5 Courses to learn Docker and Kubernetes in 2026

Closing Notes

Thanks for reading this article so far. You might be thinking that there is so much stuff to learn, so many courses to join, but you don’t need to worry.

There is a good chance that you may already know most of the stuff, and there are also a lot of useful free DevOps resources which you can use, I have also linked them here and there along with the best resources, which are certainly not free, but worth of money.

I am a particular fan of Udemy courses as they are very affordable and provide a lot of value in a very small amount, but you are free to choose the course you want.

At the end of the day, you should have enough knowledge and experience about the things mentioned here.

Good luck with your DevOps journey! It’s certainly not going to be easy, but by following this roadmap and guide, you are one step closer to becoming the DevOps engineer, you always wanted to be

P.S. — If you just want to start with one course to learn DevOps, I think the Learn DevOps: CI/CD with Jenkins using Pipelines and Docker is the best one to start with.

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System Design Basics - GraphQL-vs REST vs gRPC

2026-03-03T06:38:00.000-08:00

Disclosure: This post includes affiliate links; I may receive compensation if you purchase products or services from the different links provided in this article.

image_credit - DesignGuru

Hello devs, if you are preparing for Coding interviews interviews the along with System Design, and Microsrvices, you should also prepare about things like REST, GraphQL, and gRPC like what is difference between REST, GraphQL, and gRPC?, which is also one of the popular questions on programming interviews.

Earlier, I have talked about difference between API Gateway vs Load Balancer and Horizontal vs Vertical Scaling, Forward proxy vs reverse proxy and difference between JWT, OAuth, and SAML and in this article, I am going to share my thoughts on REST, GraphQL, and gRPC, three popular communication protocols used for building web APIs.

They are used to allow different software components to communicate with each other over a network, for example Microservices can use REST for synchronous communication between them.

Each of these protocols has its own set of advantages and disadvantages, and understanding the differences between them is not just important from tech interview point of view but also important for choosing the right one for your project.

In this article, you will learn about the differences between REST, GraphQL, and gRPC. You will learn the core concepts behind each protocol, their strengths and weaknesses, and provide some use cases for when to use each one.

By the end of this article, you should have a better understanding of which protocol is best suited for your project's requirements.

By the way, if you are preparing for System design interviews and want to learn System Design in depth then you can also checkout sites like ByteByteGo, Design Guru, Exponent, Educative, Codemia.io, Bugfree.ai and Udemy which have many great System design courses

We will first start with some introduction then we will deep dive into each of them and then again revisit the difference so that you have clear understanding of their strength and weakness and when to use them.

REST stands for Representational State Transfer and it is a popular protocol used for creating web services that expose data and functionality over HTTP.

It is based on HTTP protocol and a set of constraints that define how resources are identified and addressed, and how operations can be performed on those resources.

On the other hand, GraphQL is a query language for APIs that was developed by Facebook. It allows clients to specify exactly what data they need, and the server responds with only that data.

GraphQL was created to address shortcomings and limitation of REST, hence it provides a more flexible and efficient way of fetching data from a server, as clients can request multiple resources in a single request.

And, gRPC is a high-performance, open-source protocol used for creating APIs. It uses Google's Protocol Buffers as a data format and provides support for streaming and bi-directional communication.

gRPC is often used in microservice architectures because of its performance and support for multiple programming languages.

Now that we know what they are let's deep dive into each of them.

What is REST? When to use it?

As I said, REST (Representational State Transfer) is an architectural style for designing distributed applications, particularly web-based APIs.

RESTful APIs use HTTP methods (such as GET, POST, PUT, DELETE) to perform CRUD (Create, Read, Update, Delete) operations on resources identified by a URL (Uniform Resource Locator).

If you know HTTP you know REST.

REST also relies on a stateless client-server architecture, where each request from the client contains all the information necessary for the server to fulfill the request, without needing to maintain session state.

Here are some scenarios when REST is a good choice:

When you need to expose data and services via an API because REST is a popular and well-established protocol for creating APIs that can be easily consumed by other applications and services.
When you need to support multiple platforms and programming languages because REST relies on standard HTTP methods and data formats, it can be used by a wide variety of programming languages and platforms.
When you need to support caching because REST supports caching, which can improve performance and reduce network traffic.
When you need to build simple, lightweight APIs
When you need to support a large number of resources

Also, understanding of HTTP methods are very important for designing a REST API. You can further see REST API Design, Development & Management course to learn about REST API design, development, and management.

Overall, REST is a flexible and widely adopted protocol that is a good choice for many types of APIs.

However, it may not be the best choice for all scenarios, particularly those that require real-time updates or more complex querying and data manipulation.

In those cases, other protocols such as GraphQL or gRPC may be more appropriate.

What is GraphQL? When to use it?

GraphQL is a query language for APIs that was developed by Facebook in 2012 and released as an open-source project in 2015. It was originally created to address limitation and shortcomings of REST.

GraphQL allows clients to define the structure of the data they need, and servers to respond with exactly that data, without any unnecessary data.

It's often used as an alternative to RESTful APIs, particularly for scenarios where the client needs fine-grained control over the data that's returned.

Here are some scenarios when GraphQL is a good choice:

When you want to reduce network traffic as GraphQL allows clients to specify exactly what data they need, which can reduce the amount of unnecessary data that's transmitted over the network.
When you need to support a wide variety of clients because GraphQL supports strongly-typed queries, which can be used to ensure that clients receive the correct data in a format they understand.
When you need to support real-time updates as GraphQL supports real-time updates via subscriptions, which allow clients to receive updates as soon as they're available.
When you need to support complex queries and data manipulation: because GraphQL allows clients to perform complex queries and data manipulation operations, such as filtering, sorting, and aggregation, with a simple syntax.
When you need to support versioning because GraphQL supports versioning by allowing clients to specify the version of the schema they're using in their requests, which can make it easier to maintain backward compatibility as the schema evolves over time.

Overall, GraphQL is a powerful and flexible protocol that can be a good choice for scenarios where fine-grained control over data and real-time updates are important.

However, it may require more setup and configuration than RESTful APIs, particularly if you're working with multiple programming languages or platforms.

You can further see GraphQL by Example and GraphQL with React: The Complete Developers Guide to learn more about GraphQL and how to use it.

and Here is also a nice diagram highlighting the difference between REST and GraphQL queries:

What is gRPC? When to use it?

Now let's see what is gRPC and what does it offer? Well, gRPC is a high-performance, open-source framework for remote procedure calls (RPC) developed by Google.

It uses Protocol Buffers as the interface description language and supports a wide range of programming languages, making it easy to build distributed systems that work across different platforms and environments.

Here are some scenarios when gRPC is a good choice:

When you require high performance and efficiency because gRPC uses a binary protocol and supports streaming, which can make it much faster and more efficient than other protocols, particularly over high-latency or low-bandwidth connections.
When you require to support a wide range of programming languages because gRPC supports many programming languages, including Java, C++, Python, and Go, making it easy to build distributed systems that work across different platforms and environments.
When you need to support real-time updates because gRPC supports bidirectional streaming, which allows servers to send updates to clients in real-time.
When you need to work with large amounts of data since gRPC uses Protocol Buffers, which are more efficient and compact than other data formats like JSON or XML, making it a good choice for working with large amounts of data.
When you need to build microservices or distributed systems because gRPC provides a powerful and flexible framework for building microservices and distributed systems that can scale horizontally and handle large volumes of traffic.

Overall, gRPC is a powerful and efficient protocol that can be a good choice for scenarios where performance, efficiency, and real-time updates are important.

However, it may require more setup and configuration than other protocols like RESTful APIs, particularly if you're working with multiple programming languages or platforms.

You can further see Complete Guide to Protocol Buffers 3 [Java, Golang, Python] and gRPC [Java] Master Class: Build Modern API & Microservices to learn more about gRPC and Google Protocol buffer.

Here is a nice diagram which highlights the difference between REST, gRPC and GraphQL request as well

image_credit --- https://medium.com/@LadyNoBug/grpc-v-s-rest-v-s-others-5d8b6eaa61df

Difference between GraphQL, REST and, gRPC

Now that you know what is REST, gRPC, and GraphQL and how they work, here are the key differences between REST, GraphQL, and gRPC in point format remember their key characteristic and when to use each of them in your project:

REST:

Stands for Representational State Transfer
Uses HTTP methods (GET, POST, PUT, DELETE) to perform CRUD operations
Sends data in a structured format, usually JSON or XML
Can have multiple endpoints for different resources
Clients receive all the data specified in the response, even if they don't need it all
Caching is supported, but can be complex to manage
Well-established and widely adopted, with extensive tooling and documentation available

GraphQL:

Allows clients to specify exactly what data they need, and receives only that data
Uses a single endpoint to access multiple resources
Has its own query language that allows for complex data fetching and manipulation
Can support real-time updates via subscriptions
Can be more efficient than REST in certain situations, particularly for mobile devices with limited bandwidth
Caching can be more fine-grained and easier to manage than with REST
Requires more setup and configuration than REST, and may require more expertise to use effectively

gRPC:

Stands for Remote Procedure Call (RPC) with Google's Protocol Buffers
Uses binary data for communication instead of HTTP
Supports streaming data for real-time updates
Uses protocol buffers for serialization, which can be more efficient than JSON or XML
Can be used across different programming languages
Designed for high-performance, low-latency communication between microservices
Requires more setup and configuration than REST, and may require more expertise to use effectively
Can be less interoperable than REST or GraphQL, since it is not based on HTTP

Here is also a nice table which highlight the difference between REST, GraphQL, and gRPC, you can use it for quick revision:

It's also worth noting that these protocols are not mutually exclusive, and it's possible to use them in combination to take advantage of their different strengths.

For example, you might use REST for most of your API, but use GraphQL for certain resource-intensive queries, or use gRPC for communication between microservices while using REST or GraphQL for external API clients.

System Design Interviews Resources:

And, if you are preparing for System design interview then here are curated list of best system design books, online courses, and practice websites which you can check to better prepare for System design interviews.

ByteByteGo: A live book and course by Alex Xu for System design interview preparation. It contains all the content of the System Design Interview book volumes 1 and 2, and will be updated with volume 3, which is coming soon.
Exponent: A specialized site for interview prep, especially for FAANG companies like Amazon and Google. They also have a great system design course and many other materials that can help you crack FAAN interviews.
DesignGuru's Grokking System Design Course: An interactive learning platform with hands-on exercises and real-world scenarios to strengthen your system design skills.
Bugfree.ai: LeetCode for System design, a popular platform for technical interview preparation. It includes a variety of questions to practice.
"System Design Primer" on GitHub: A curated list of resources, including articles, books, and videos, to help you prepare for system design interviews.
Educative's System Design Course: An interactive learning platform with hands-on exercises and real-world scenarios to strengthen your system design skills.
High Scalability Blog: A blog that features articles and case studies on the architecture of high-traffic websites and scalable systems.
YouTube Channels: Check out channels like "Gaurav Sen" and "Tech Dummies" for insightful videos on system design concepts and interview preparation.
"System Design Interview" by Alex Xu: This book provides an in-depth exploration of system design concepts, strategies, and interview preparation tips.
"Designing Data-Intensive Applications" by Martin Kleppmann: A comprehensive guide that covers the principles and practices for designing scalable and reliable systems.

image_credit - ByteByteGo

Conclusion

That's all about difference between REST, GraphQL, and gRPC technology. In short, REST is a popular protocol used for creating web services, inspired by HTTP and take full advantages of what HTTP offers, while GraphQL is a query language that allows clients to specify exactly what data they need from a server.

It was created to address shortcoming of REST, so its definitely a viable option if you are struggling to maintain your REST APIs.

On the other hand, gRPC is a high-performance, open-source protocol that is often used in microservice architectures.

Each of these protocols serves a different purpose, and they can all be used together to provide a comprehensive and efficient communication system for web applications.

Top 5 Skills Developer Should Learn in 2026 Apart from AI

2026-02-28T06:29:00.000-08:00

Disclosure: This post includes affiliate links; I may receive compensation if you purchase products or services from the different links provided in this article.

image_credit - Exponent

Hello devs, if you have been doing programming and software development, then you know that there is only one constant in our field, and that is "Change".

We always need to learn new tools, technologies, frameworks, and skills to do our job, and there is no end to it. If you don't learn, you will be left behind with others; that's why I always look for new skills to learn.

In this article, I am going to share 5 skills programmers and developers can learn in 2026 to become better at their job and also become more efficient.

In the past, I talked about difference between API Gateway vs Load Balancer and Horizontal vs Vertical Scaling, Forward proxy vs reverse proxy, which you guys liked a lot and in this article I am going to share top five developer skills that are set to take center stage in 2026.

P.S. Keep reading until the end. I have a bonus for you.

These skills include both new and old but essential skills like prompt engineering, coding, cloud computing realms, system design, and Python; these skills are in demand and essential for any software developer.

Whether you're an experienced developer looking to upgrade yourself or an intermediate developer who wants to enhance their profile, these skills will certainly help you.

5 Skills Software Engineers Should Learn in 2026

In the ever-evolving landscape of technology, staying ahead of the curve is essential for developers seeking to thrive in 2026 and beyond.

As we navigate through the dynamic realms of software development, certain skills have emerged as indispensable for the modern developer, and that's what you are going to learn in this article.

Let's deep dive into the top five developer skills that are poised to make a significant impact in 2026.

1. System Design

In 2026, developers need to go beyond traditional coding practices and embrace modern system design principles. This involves understanding distributed systems, microservices architecture, and designing scalable and resilient applications.

Developers who can navigate complexities in system design are better equipped to create robust solutions that can handle the demands of a rapidly evolving technological landscape.

If you want to learn System Design in depth, then you can also check out sites like ByteByteGo, Design Guru, Exponent, Educative, Bugfree.ai and Udemy which have many great System design courses

If you need more resources, then here is a list of System design books, courses, and websites to learn and master Software design and architecture in 2026.

2. Prompt Engineering

In this era of AI tools, Software development is not untouched, and more and more AI tools are coming to help you with Coding, debugging, and testing, but you need prompt engineering to make effective use of these tools.

In other words, Prompt engineering has become a crucial skill for developers aiming to deliver high-quality products quickly.

This involves not only writing efficient and concise code but also adopting agile methodologies and tools to streamline the entire development process.

Developers proficient in prompt engineering can rapidly respond to changing requirements, ensuring their software remains adaptable and resilient in the face of evolving market demands.

If you need a resource to learn ChatGPT and Prompt Engineering, then I suggest you see ChatGPT Prompt Engineering for Developers course on Coursera.

If you need more options, then you can also see these ChatGPT and Prompt Engineering courses to learn more.

3. Coding

While coding might seem like an obvious skill, its significance cannot be overstated. Mastery in coding goes beyond writing functional programs; it involves writing clean, maintainable, and scalable code.

Developers should focus on enhancing their proficiency in programming languages, understanding algorithms, and implementing best practices.

A solid foundation in coding forms the bedrock for success in any development endeavor. And, if you need a resource, you can check out The Complete JavaScript Course 2026: Build Real Projects to start with.

If you need more choices, you can also check out these Programming and Coding courses

4. Cloud Computing

Cloud computing has transcended from being a buzzword to an essential skill for developers. With the increasing reliance on cloud services, developers must be well-versed in deploying, managing, and optimizing applications in cloud environments.

Platforms like AWS, Azure, and Google Cloud are integral to modern development, and developers proficient in cloud computing can create scalable and cost-effective solutions.

And, if you need resources, you can see these articles where you can find highly recommended resources to learn Cloud Computing

And, if you need more choices, you can also see this article where you can find highly recommended AWS Fundamentals Specialization on Coursera. This program is created by AWS itself.

5. Python

Python continues to assert its dominance as a versatile and powerful programming language. From web development to data science, machine learning, and artificial intelligence, Python is at the forefront of innovation.

Developers in 2026 should invest in mastering Python, as it not only facilitates rapid development but also provides a gateway to a plethora of cutting-edge technologies shaping the future of the industry.

If you want to learn and master Python in 2026, you can start with this Python course 100 Days of Code: The Complete Python Pro Bootcamp for 2026, which I am also using to learn Python nowadays.

If you need more resources, you can also see these Python books, courses, and websites to learn Python in depth.

That's all about the top 5 developer skills you can learn in 2026. In conclusion, the top developer skills for 2026 reflect the industry's demand for agility, adaptability, and technical excellence.

Whether you are a seasoned developer or just starting your coding journey, honing these skills will undoubtedly position you as a valuable asset in the ever-evolving world of software development.

Embrace the challenges, stay curious, and embark on a journey of continuous learning to thrive in the dynamic landscape of 2026 and beyond.

Bonus

As promised, here is the bonus for you, a free book which you can read to learn Distributed System Design. You can either download the Free PDF or read online on Microsoft --- https://info.microsoft.com/rs/157-GQE-382/images/EN-CNTNT-eBook-DesigningDistributedSystems.pdf

And let me know in the comments which skills you are learning in 2026? I am always eager to learn skills that can enhance my profile as a software developer.

Thank you

System Design Basics - Apache Kafka vs RabbitMQ vs ActiveMQ

2026-02-24T06:36:00.000-08:00

Disclosure: This post includes affiliate links; I may receive compensation if you purchase products or services from the different links provided in this article.

image_credit - Design Guru

Hello devs, if you are preparing for System Design interviews then along with popular software design questions like API Gateway vs Load Balancer and Horizontal vs Vertical Scaling, Forward proxy vs reverse proxy, you should also prepare about things like messaging brokers, kafka, rabbitmq, and activemq like what is difference between Kafka, RabbitMQ, and ActiveMQ?, which is also one of the popular questions on Java interviews.

In my last article, I shared about 50 System Design Interview Questions and REST vs GraphQL vs gRPC, and in this article, I am going to share my thoughts on Kafka, RabbitMQ, and ActiveMQ, three popular message brokers used for asynchronous communication.

Messaging systems and Message brokers play a crucial role in modern distributed architectures, where applications and services communicate with each other over a network.

The messaging systems allow decoupling of the sender and receiver, thereby enabling asynchronous communication. RabbitMQ, Apache Kafka, and ActiveMQ are three popular messaging systems used in the industry.

In this article, we will discuss the differences between RabbitMQ, Apache Kafka, and ActiveMQ.

By the way, If you are preparing for System design interviews and want to learn System Design in depth then you can also checkout sites like ByteByteGo, Design Guru, Exponent, Educative , bugfree.ai, and Udemy which have many great System design courses and if you need free system design courses you can also see the below article.

And, if you are in a hurry, here is a table from ByteByteGo which compares Kafka with RabbitMQ on different parameters like architecture, structure, working, etc

Rabbit MQ vs Kafka

What is Apache Kafka and where is it used?

Apache Kafka is an open-source distributed event streaming platform that was originally developed by LinkedIn. Kafka is written in Scala and Java and is designed to handle large-scale streaming data flows.

Kafka uses a publish/subscribe messaging model and is optimized for high throughput, low latency, and fault-tolerance.

Kafka has a durable messaging model, which means that messages are stored on disk and can be replayed multiple times.

If you want to learn more about Kafka, particularly from a system design point of view, you can also join ByteByteGo, a great platform to learn essential system design concepts

What is RabbitMQ and where is it used?

RabbitMQ is an open-source message broker that implements the Advanced Message Queuing Protocol (AMQP) standard.

It is written in Erlang and has a pluggable architecture that allows for easy extensibility.

RabbitMQ supports multiple messaging patterns such as publish/subscribe, request/reply, and point-to-point, and it has a robust set of features such as message acknowledgment, routing, and queuing.

Arslan Ahmend has explained about RabbitMQ in his classic Grokking the System design interview course, if you are preparing for a tech interview, you can also see that resource for better preparation.

What is ActiveMQ? where does it used?

Apache ActiveMQ is an open-source message broker that implements the Java Message Service (JMS) API. ActiveMQ is written in Java and has a pluggable architecture that allows for easy extensibility.

ActiveMQ supports multiple messaging patterns such as point-to-point, publish/subscribe, and request/reply, and it has a robust set of features such as message acknowledgment, routing, and queuing.

Differences between RabbitMQ, Apache Kafka, and ActiveMQ?

Now that you have a fair idea of what is RabbitMQ, ActiveMQ, and Apache Kafka, it's time to find out the difference between them from messaging model to performance.Here are key differences between Apache Kafka, RabbitMQ and ActiveMQ:

1. Messaging Model

RabbitMQ and ActiveMQ both support the JMS API, which means that they follow a traditional messaging model where messages are sent to a queue or a topic and consumed by one or more consumers.

On the other hand, Kafka uses a publish/subscribe messaging model, where messages are published to a topic and consumed by one or more subscribers.

The traditional messaging model used by RabbitMQ and ActiveMQ is well-suited for applications that require strict ordering and reliable delivery of messages.

On the other hand, the publish/subscribe messaging model used by Kafka is better suited for streaming data scenarios, where real-time processing of data is required.

Here is a nice diagram which highlight the architecture difference between Kafka and RabbitMQ

2. Scalability

Scalability is an essential requirement for messaging systems, especially when dealing with large volumes of data. RabbitMQ and ActiveMQ are both designed to be scalable, but they have different approaches to achieving scalability.

RabbitMQ uses a clustering approach to achieve scalability, where multiple RabbitMQ brokers are connected to form a cluster. Messages are distributed across the cluster, and consumers can connect to any broker in the cluster to consume messages.

RabbitMQ also supports federation, which allows multiple RabbitMQ clusters to be connected together.

ActiveMQ uses a network of brokers approach to achieve scalability, where multiple ActiveMQ brokers are connected to form a network.

Messages are distributed across the network, and consumers can connect to any broker in the network to consume messages. ActiveMQ also supports master/slave replication, which provides high availability for the message broker.

Kafka, on the other hand, is designed to be highly scalable out of the box. Kafka uses a partitioning approach to achieve scalability, where messages are partitioned across multiple Kafka brokers.

Each partition is replicated across multiple brokers for fault tolerance. This approach allows Kafka to handle large volumes of data while maintaining low latency and high throughput.

3. Performance

Performance is another critical factor to consider when choosing a messaging system. RabbitMQ, Kafka, and ActiveMQ all have different performance characteristics.

RabbitMQ is designed to be a reliable messaging system, which means that it prioritizes message delivery over performance.

RabbitMQ can handle moderate message rates and is suitable for applications that require strict ordering and reliable delivery of messages.

Kafka, on the other hand, is designed for high-performance and can handle large volumes of data with low latency. Kafka achieves this performance by using a distributed architecture and optimizing for sequential I/O.

ActiveMQ is also designed for high-performance and can handle high message rates. ActiveMQ achieves this performance by using an asynchronous architecture and optimizing for message batching.

Here is a chart from confluent which compares performance of Apache Kafka, Pulsar and RabbitMQ

Benchmarking Apache Kafka, Apache Pulsar, and RabbitMQ: Which is the Fastest?

4. Data Persistence

Data persistence is an important feature of messaging systems, as it allows messages to be stored and retrieved even if the messaging system goes down. RabbitMQ, Kafka, and ActiveMQ all have different approaches to data persistence.

RabbitMQ stores messages on disk by default, which allows messages to be persisted even if the broker goes down.

RabbitMQ also supports different storage backends, including in-memory storage, which provides better performance at the cost of data durability.

Kafka stores messages on disk by default and uses a log-based architecture to achieve high durability and reliability. Kafka retains messages for a configurable period, which allows messages to be replayed if necessary.

ActiveMQ also stores messages on disk by default and supports different storage backends, including JDBC and file-based storage. ActiveMQ can store messages in a database, which provides better data durability at the cost of performance.

Here is a nice diagram from IBM that shows a Kafka architecture:

image --- https://ibm-cloud-architecture.github.io/refarch-eda/technology/kafka-overview/

5. Integration with Other Systems

Integration with other systems is an important factor to consider when choosing a messaging system. RabbitMQ, Kafka, and ActiveMQ all have different integration capabilities.

RabbitMQ integrates well with different programming languages, including Java, Python, Ruby, and .NET. RabbitMQ also has plugins that allow it to integrate with different systems, including databases, web servers, and message brokers.

Kafka integrates well with different data processing systems, including Apache Spark, Apache Storm, and Apache Flink. Kafka also has a connector framework that allows it to integrate with different databases and data sources.

ActiveMQ integrates well with different JMS clients, including Java, .NET, and C++. ActiveMQ also has plugins that allow it to integrate with different systems, including Apache Camel and Apache CXF.

Here is also a nice table to highlight the difference between Kafka, RabbitMQ, and ActiveMQ

System Design Interviews Resources:

ByteByteGo: A live book and course by Alex Xu for System design interview preparation. It contains all the content of the System Design Interview book volumes 1 and 2, and will be updated with volume 3, which is coming soon.
Codemia.io: This is another great platform to practice System design problems for interviews. It has more than 120+ System design problems, many of which are free and also a proper structure to solve them.
Bugfree.ai: Bugfree.ai is a popular platform for technical interview preparation. The System Design sections and interview experience include a variety of questions to practice.
Exponent: A specialized site for interview pre,p especially for FAANG companies like Amazon and Google. They also have a great system design course and many other materials that can help you crack FAAN interviews.
Educative's System Design Course: An interactive learning platform with hands-on exercises and real-world scenarios to strengthen your system design skills.
DesignGuru's Grokking System Design Course: An interactive learning platform with hands-on exercises and real-world scenarios to strengthen your system design skills.
"System Design Interview" book by Alex Xu: This book provides an in-depth exploration of system design concepts, strategies, and interview preparation tips.
"Designing Data-Intensive Applications" by Martin Kleppmann: A comprehensive guide that covers the principles and practices for designing scalable and reliable systems.
"System Design Primer" on GitHub: A curated list of resources, including articles, books, and videos, to help you prepare for system design interviews.
High Scalability Blog: A blog that features articles and case studies on the architecture of high-traffic websites and scalable systems.
YouTube Channels: Check out channels like "Gaurav Sen" and "Tech Dummies" for insightful videos on system design concepts and interview preparation.

image_credit - ByteByteGo

Remember to combine theoretical knowledge with practical application by working on real-world projects and participating in mock interviews.

Conclusion

That's all about the difference between Apache Kafka, RabbitMQ, and ActiveMQ. RabbitMQ, Apache Kafka, and ActiveMQ are three popular messaging systems that have different features and capabilities.

RabbitMQ and ActiveMQ follow a traditional messaging model, while Kafka uses a publish/subscribe messaging model.

RabbitMQ and ActiveMQ use clustering and a network of brokers approach to achieve scalability, while Kafka uses partitioning. RabbitMQ prioritizes message delivery over performance, while Kafka and ActiveMQ prioritize performance. RabbitMQ, Kafka, and ActiveMQ all have different data persistence and integration capabilities.

When choosing a messaging system, it is essential to consider the specific requirements of the application or system.

RabbitMQ and ActiveMQ are suitable for applications that require strict ordering and reliable delivery of messages, while Kafka is suitable for streaming data scenarios.

RabbitMQ and ActiveMQ are suitable for applications that require moderate to high message rates, while Kafka is suitable for applications that require high message rates.

Similarly, RabbitMQ and ActiveMQ are suitable for applications that require high data durability, while Kafka is suitable for applications that require high performance.

Top 10 Essential Tools for DevOps Engineers to Learn in 2026

2026-02-23T06:56:00.000-08:00

Disclosure: This post includes affiliate links; I may receive compensation if you purchase products or services from the different links provided in this article.

Hello friends, In the last few articles, I talked about System Design interview questions, and WHERE vs HAVING in SQL, and today, I will talk about essential DevOps tools that both developers and DevOps should know.

In today's fast-paced software development landscape, DevOps practices and tools have become essential for efficient Software development and delivery.

DevOps is all about breaking down the traditional silos between development and operations teams, fostering collaboration, and automating key processes.

To achieve these goals, a wide array of DevOps tools and technologies has emerged, each addressing specific aspects of the software delivery lifecycle.

In this article, I am going to share the top 10 DevOps tools that play an important role in the way organizations build, test, deploy, and monitor software.

These tools span a range of categories, from version control and continuous integration to container orchestration and monitoring.

Whether you're a DevOps Engineer or a Senior developer looking to expand your toolkit or an organization seeking to adopt DevOps practices, these tools can help streamline your software development and operations processes.

10 Essential DevOps Tools You Can Learn in 2026

Let's dive into the world of DevOps and discover the top 10 tools that can empower your team to achieve faster, more reliable software delivery.

1. Git

Git revolutionized version control, making it one of the foundational tools in DevOps. It allows developers to track changes in their codebase, collaborate seamlessly, and manage multiple code branches effectively.

Git hosts like GitHub, GitLab, and Bitbucket have further enhanced their capabilities, providing a platform for distributed version control, code review, and project management.

And if you want to learn Git, you can start with Git Complete: The definitive, step-by-step guide to Git, one of the most comprehensive courses on Udemy.

If you need more choices, then you can also see these best Git online courses for beginners in 2026. It contains git courses and tutorials for both beginners and experienced DevOps engineers.

2. Jenkins: Continuous Integration and Continuous Delivery (CI/CD)

Jenkins is an open-source automation server that plays a crucial role in automating the CI/CD pipeline. It allows developers to build, test, and deploy code continuously, ensuring that changes are integrated smoothly and errors are detected early in the development process.

With a vast library of plugins, Jenkins can be customized to suit the specific needs of your development environment.

And if you want to learn Jenkins in depth then you can start with Jenkins, From Zero To Hero: Become a DevOps Jenkins Master course, its a nice course to learn Jenkins.

If you need more choices, then you can also see these best Jenkins courses for 2026.

3. Docker: Containerization for Portability

Docker has revolutionized how applications are packaged and deployed. With Docker containers, you can bundle your application and its dependencies into a single, lightweight unit that runs consistently across different environments.

This portability and isolation make Docker a key tool for DevOps teams aiming to achieve consistency from development to production.

And if you want to learn Docker in 2026, you can start with Docker and Kubernetes: The Complete Guide course, it's a nice course to learn Docker from scratch.

If you need more choices, then you can also see these best Docker courses for beginners in 2026 to start with.

4. Kubernetes

Kubernetes has emerged as the de facto standard for container orchestration. It simplifies the management of containerized applications, automating tasks such as scaling, load balancing, and fault tolerance.

Kubernetes provides the foundation for building resilient, Microservices-based applications, and it's a must-have tool for modern DevOps teams.

And if you want to learn Kubernetes in depth, you can start with this beginner-level hands-on course Kubernetes for the Absolute Beginners --- Hands-on by Mumshad Mannambeth on Udemy.

If you need more choices, here are the best Kubernetes courses for DevOps Engineers to join in 2026.

5. Ansible

Ansible is a powerful open-source tool for automating configuration management and application deployment. It allows you to define infrastructure as code, making it easier to provision and manage servers and services.

Ansible's simplicity and agentless architecture make it a favorite among DevOps professionals for automating repetitive tasks.

And if you want to learn Ansible in depth, you can start with the Ansible for the Absolute Beginner — Hands-On — DevOps course by KodeCloud Training on Udemy. It's a nice hands-on course to learn Ansible.

If you need more options, you can always check these best Ansible online courses in 2026. It contains Ansible courses for both beginner and intermediate DevOps engineers.

6. Terraform

Terraform is another key tool for infrastructure as code. It enables you to define and provision infrastructure resources across various cloud providers and on-premises environments.

Terraform's declarative syntax and modular design make it a versatile choice for managing infrastructure at scale.

And if you want to learn Terraform in depth, then you can start with the Terraform for the Absolute Beginners with Labs course by Kodecloud training.

If you need more choices, then you can also check out these best Terraform courses for 2026.

7. Prometheus

Prometheus is an open-source monitoring and alerting toolkit designed for reliability and scalability. It can collect metrics from various sources, allowing you to gain insight into the health and performance of your applications and infrastructure.

With its flexible query language and robust alerting capabilities, Prometheus empowers DevOps teams to proactively identify and address issues.

If you need a course to learn Prometheus, you can start with Prometheus | The Complete Hands-On for Monitoring & Alerting course on Udemy. I took this course last month, its quite nice.

8. ELK Stack

The ELK Stack, which consists of Elasticsearch, Logstash, and Kibana, provides a comprehensive solution for log management and analysis, particularly in the microservices world.

It allows DevOps teams to collect, parse, store, and visualize log data from various sources.

This stack is invaluable for troubleshooting, performance optimization, and security monitoring.

And, if you want to learn more about the ELK stack, you can start with the Complete Elasticsearch Masterclass with Logstash and Kibana course from Udemy. It's a nice beginner-level course for the ELK stack.

And, if you need more choices, you can always take a look at these best ELK stack courses for Beginners in 2026

9. Jenkins X

Jenkins X is a Kubernetes-native CI/CD solution that brings automation and GitOps principles to the forefront. It simplifies the process of building, testing, and deploying cloud-native applications on Kubernetes clusters.

Jenkins X streamlines the development workflow and promotes best practices for containerized applications.

10. Grafana

Grafana is a popular open-source platform for data visualization and monitoring. It can integrate with various data sources, including Prometheus, to create dynamic dashboards and alerts.

DevOps teams use Grafana to gain real-time insights into application and infrastructure performance, facilitating data-driven decision-making. If you want to learn Grafana in depth, you can start with the Grafana course on Udemy. It's a nice course to learn Grafana from scratch.

If you need more choices, then you can also check out these best Grafana online courses in 2026.

That's all about the 10 essential tools DevOps can learn in 2026. The DevOps landscape is continually evolving, and the tools mentioned above are just a snapshot of the vast ecosystem available to DevOps practitioners.

Each tool plays a crucial role in different aspects of the software delivery pipeline, from version control and continuous integration to container orchestration and monitoring.

The key to successful DevOps adoption is selecting the right tools that align with your organization's needs and goals.

By embracing these DevOps tools, your organization can streamline its development and operations processes, reduce manual effort, improve collaboration, and deliver high-quality software at a faster pace.

Top 50 Easy, Medium, and Hard System Design Interview Questions for 2026

2026-02-21T20:40:00.000-08:00

Disclosure: This post includes affiliate links; I may receive compensation if you purchase products or services from the different links provided in this article.

image_credit - Exponent

Hello friends, if you are preparing for Tech interviews, then you must prepare for System design questions because this is where most of the people struggle.

Even experienced programmers struggle to solve common questions like how to design WhatsApp or YouTube, or answer the difference between API Gateway vs Load Balancer and Horizontal vs Vertical Scaling, Forward proxy vs reverse proxy.

In today's increasingly distributed world, the ability to architect robust and scalable systems is a fundamental skill sought after by top-tier tech companies.

System design interviews have become a crucial component in evaluating a candidate's capacity to solve real-world challenges, assess trade-offs, and design systems that can handle complex requirements.

In the past, I have also shared about Database Sharding, System design topics, Microservice Architecture, and System design algorithms, and today, I am going to share system design questions for interviews.

In this article, I have 50+ system design interview questions carefully crafted to guide candidates from the foundational concepts to intricate design scenarios.

Whether you're a beginner aiming to grasp the essentials or an experienced engineer seeking to refine your skills, these questions will not only prepare you for interviews but also improve your knowledge about system design and software architecture.

P.S. Keep reading until the end. I have a free bonus for you.

50 System Design Interview Questions for 2026

Here is a list of 50 popular System design interview questions for beginners and experienced developers, which you can solve to start your preparation.

In this list, I have not only shared easy, medium, and hard system design problems but also concept-based questions like API Gateway vs Load Balancer or Microservice vs Monolithic. You can practice these system design problems and questions for interviews.

System Design Concept-based Questions

1. What is the difference between API Gateway and Load Balancer? [solution]
2. What is the difference between Reverse Proxy and Forward Proxy? (answer)
3. What is the difference between Horizontal scaling and vertical scaling? (answer)
4. What is difference between Microservices and Monolithic architecture? (Answer)
5. What is difference between vertical and horizontal partitioning ?
6. What is Rate Limiter? How does it work? (answer)
7. How does Single Sign On (SSO) works? (answer)
8. How does Apache Kafka works? why it so fast? (answer)
9. Difference between Kafka, ActiveMQ, and RabbitMQ? (answer)
10. Difference between JWT, OAuth, and SAML? (answer)

Here is a nice diagram from DesignGuru.io which explains difference between vertical and horizontal database partition

𝐄𝐚𝐬𝐲 System Design Problems

Now, let's jump into easy system design problems. These are common question where you need to design small utility which is used everywhere like URL shortner:

1. How to Design URL Shortener like TinyURL [solution]
2. How to Design Text Storage Service like Pastebin? [solution]
3. Design Content Delivery Network (CDN) ? [solution]
4. Design Parking Garage [solution]
5. Design Vending Machine [solution]
6. How to Design Distributed Key-Value Store
7. Design Distributed Cache
8. Design Distributed Job Scheduler
9. How to Design Authentication System
10. How to Design Unified Payments Interface (UPI)

And, here is a high level design of YouTube from Educative.io for your reference:

𝐌𝐞𝐝𝐢𝐮𝐦 System Design Problems

Now, is the time to see medium difficulty of System design problems. These questions are neither easy nor very tough but you need good knowledge of various software architecture component and system design concepts to answer them.

11. Design Instagram [solution]
12. How to Design Tinder
13. Design WhatsApp (solution)
14. How to Design Facebook
15. Design Twitter
16. Design Reddit
17. Design Netflix [solution]
18. Design Youtube [solution]
19. Design Google Search
20. Design E-commerce Store like Amazon
21. Design Spotify
22. Design TikTok
23. Design Shopify
24. Design Airbnb
25. Design Autocomplete for Search Engines
26. Design Rate Limiter
27. Design Distributed Message Queue like Kafka
28. Design Flight Booking System
29. Design Online Code Editor
30. Design Stock Exchange System
31. Design an Analytics Platform (Metrics & Logging)
32. Design Notification Service
33. Design Payment System

And, here is a high level system design of Netflix from DesignGurus, one of my favorite place for learning system design

𝐇𝐚𝐫𝐝 System Design Problems

Now, let's see some hard questions which demand more effort from you. You may feel uncomfortable solving these questions but by doing this you become better.

34. How to Design Location Based Service like Yelp
35. Design Uber
36. Design Food Delivery App like Doordash
37. Design Google Docs
38. How to Design Google Maps
39. Design Zoom
40. How to Design File Sharing System like Dropbox
41. How to Design Ticket Booking System like BookMyShow
42. Design Distributed Web Crawler
43. How to Design Code Deployment System
44. Design Distributed Cloud Storage like S3
45. How to Design Distributed Locking Service

Here is high level design of Google Map by Educative.io

And, if you need solutions then they are available in this GitHub repository by @ Ashish Pratap Singh: https://github.com/ashishps1/awesome-system-design-resources/blob/main/README.md#system-design-interview-problems

And, now see a few more resources for System design interview preparation

Best System Design Interview Resources

ByteByteGo: A live book and course by Alex Xu for System design interview preparation. It contains all the content of the System Design Interview book volumes 1 and 2, and will be updated with volume 3, which is coming soon.
Codemia.io: This is another great platform to practice System design problems for interviews. It has more than 120+ System design problems, many of which are free, and also a proper structure to solve them.
Bugfree.ai: This is another popular platform for technical interview preparation. It contains AI-based mock interviews as well as Interview experience and more than 3200+ real questions on System Design, Machine Learning, and other topics for practice =.
DesignGuru's Grokking System Design Course: An interactive learning platform with hands-on exercises and real-world scenarios to strengthen your system design skills.
"System Design Interview" book by Alex Xu: This book provides an in-depth exploration of system design concepts, strategies, and interview preparation tips.
"System Design Primer" on GitHub: A curated list of resources, including articles, books, and videos, to help you prepare for system design interviews.
Educative's System Design Course: An interactive learning platform with hands-on exercises and real-world scenarios to strengthen your system design skills.
High Scalability Blog: A blog that features articles and case studies on the architecture of high-traffic websites and scalable systems.
YouTube Channels: Check out channels like "Gaurav Sen" (ex-Google engineer and founder of InterviewReddy.io and "Tech Dummies" for insightful videos on system design concepts and interview preparation.
"Designing Data-Intensive Applications" by Martin Kleppmann: A comprehensive guide that covers the principles and practices for designing scalable and reliable systems.
Exponent: A specialized site for interview prep, especially for FAANG companies like Amazon and Google. They also have a great system design course and many other materials that can help you crack FAANG interviews.

image_credit - ByteByteGo

Remember to combine theoretical knowledge with practical application by working on real-world projects and participating in mock interviews. Continuous practice and learning will undoubtedly enhance your proficiency in system design interviews.

That's all about 50 System design interview questions for 2026. If you are preparing for technical interviews, then most likely you can solve these questions, but if you struggle, you can see the answer links, which go to free tutorials and YouTube videos, as well as the online courses and books I have shared.

Whether you're a candidate preparing for a technical interview or a seasoned professional looking to refine your skills, mastering system design is a pivotal step in advancing your career in the ever-evolving tech industry, and these questions will help you.

Bonus

As promised, here is the bonus for you, a free book. I just found a new free book to learn Distributed System Design, you can also read it here on Microsoft --- https://info.microsoft.com/rs/157-GQE-382/images/EN-CNTNT-eBook-DesigningDistributedSystems.pdf

Difference between WHERE vs HAVING Clause in SQL

2026-02-20T07:07:00.000-08:00

Disclosure: This post includes affiliate links; I may receive compensation if you purchase products or services from the different links provided in this article.

Hello friends, SQL questions are quite common on programming interviews and one of the popular SQL question is "WHERE vs HAVING clause"? When it comes to filtering records in SQL query, there are two main options, either by using WHERE clause or by using HAVING clause.

While both WHERE and HAVING are used for filtering rows, condition in WHERE clause is applied before grouping of data and condition on HAVING is applied after grouping

I mean, the main difference between them is that you can use WHERE if you want to filter data before grouping, I mean before you group records using GROUP BY clause and use HAVING when you want to filter groups.

This distinction is made by Query Engine on most of popular database like MySQL, Microsoft SQL Server, Oracle, and PostgreSQL

For example,


SELECT *
FROM BOOK
WHERE author="Joshua Bloch"

will only show books where author is "Joshua Bloch", here we have used WHERE clause because there is no grouping.

In case, we need grouping like authors with number of books we can use group by and having clause together and it will print only authors which have more than one book.



SELECT author, count(*) as NumberOfBooks
FROM BOOK
GROUP BY author
HAVING NumberOfBooks > 1

You can also use WHERE and HAVING clause together in one query and in that case WHERE clause will filter before grouping and HAVING clause will filter after grouping as shown in following example:



SELECT author, count(*) as NumberOfBooks
FROM BOOK
WHERE title like '%SQL%'
GROUP BY author
HAVING NumberOfBooks > 1

This will only print author which have multiple books with title 'SQL in them.

By the way, if you are new to SQL, then you can also use websites like Udemy, Coursera, Educative, ZTM Academy, freeCodeCamp, and VladMihalcea' SQL course to learn SQL in depth.

Difference between WHERE and HAVING clause in SQL?

Now that you know what is WHERE and HAVING clause in SQL and what the do, here are more useful difference between WHERE and HAVING clause in SQL :

1. WHERE clause can be used with SELECT, UPDATE and DELETE statements and clauses but HAVING clause can only be used with SELECT statements.

e.g.



SELECT * FROM Employee WHERE EmployeeId=3

This query will print details of employee with id = 3.

Similarly,



SELECT EmployeeName, COUNT(EmployeeName) AS NumberOfEmployee
FROM Employee
HAVING COUNT(EmployeeName) > 2;

this query will print duplicate employees from table.

2. We can't use aggregate functions in the where clause unless it is in a sub query contained in a HAVING clause whereas we can use aggregate function in Having clause. We can use column name in Having clause but the column must be contained in the group by clause.

3. WHERE clause is used on the individual records whereas Having Clause in conjunction with Group By Clause work on the record sets ( group of records ).

And, if you need more SQL questions like this then you can also see, Grokking the SQL Interview book which covers key topics for SQL interviews

That's all about difference between WHERE and HAVING clause in SQL. This is one of the important SQL questions and if you are preparing for Java developer interview, you should know the answer of this question.
While its a very common concept and we used it on daily basis, not many people can answer it correctly on interview.

Mentioning about keywords like filtering and before and after grouping is key here.

By the way, this is also a common SQL question on Java interviews and if you are preparing for Java interviews, you can also see my earlier articles like 35 Java Questions, 15 Spring Framework Questions and 6 System Design Problem to prepare other topics.

All the best !!

Top 10 Data Structures and Algorithms for System Design Interviews

2026-02-19T05:31:00.000-08:00

Disclosure: This post includes affiliate links; I may receive compensation if you purchase products or services from the different links provided in this article.

Hi there, if you are preparing for a System Design Interview, then one thing you should focus on is learning different System Design Algorithms and what problems they solve in Distributed Systems and Microservices.

In the past, I have shared 6 System Design Problems and 10 Essential System Design topics and in this article, I am going to tell you 10 System Design algorithms and distributed data structures which every developer should learn.

Without any further ado, here are the 10 System Design algorithms and distributed Data Structures you can use to solve large-scale distributed system problems:

Consistent Hashing
MapReduce
Distributed Hash Tables (DHT)
Bloom Filters
Two-phase commit (2PC)
Paxos
Raft
Gossip protocol
Chord:
CAP theorem

These algorithms and distributed data structures are just a few examples of the many techniques that can be used to solve large-scale distributed system problems.

By the way, if you are preparing for System design interviews and want to learn System Design in depth then you can also checkout sites like ByteByteGo, Design Guru, Exponent, Educative, Codemia.io, bugfree.ai and Udemy which have many great System design courses, and these popular System design YouTube channels, which have many great System design courses and tutorials.

10 Distributed Data Structure and System Design Algorithms for Programmers

It's important to have a good understanding of these algorithms and how to apply them effectively in different scenarios.

So, let's deep dive into each of them and find out what they are, how they work, and when to use them.

1. Consistent Hashing

Consistent hashing is a technique used in distributed systems to efficiently distribute data among multiple nodes.

It is used to minimize the amount of data that needs to be transferred between nodes when a node is added or removed from the system.

The basic idea behind consistent hashing is to use a hash function to map each piece of data to a node in the system. Each node is assigned a range of hash values, and any data that maps to a hash value within that range is assigned to that node.

When a node is added or removed from the system, only the data that was assigned to that node needs to be transferred to another node. This is achieved by using a concept called virtual nodes.

Instead of assigning each physical node a range of hash values, multiple virtual nodes are assigned to each physical node.

Each virtual node is assigned a unique range of hash values, and any data that maps to a hash value within that range is assigned to the corresponding physical node.

When a node is added or removed from the system, only the virtual nodes that are affected need to be reassigned, and any data that was assigned to those virtual nodes is transferred to another node.

This allows the system to scale dynamically and efficiently, without requiring a full redistribution of data each time a node is added or removed.

Overall, consistent hashing provides a simple and efficient way to distribute data among multiple nodes in a distributed system. It is commonly used in large-scale distributed systems, such as content delivery networks and distributed databases, to provide high availability and scalability.

2. Map reduce

MapReduce is a programming model and framework for processing large datasets in a distributed system. It was originally developed by Google and is now widely used in many big data processing systems, such as Apache Hadoop.

The basic idea behind MapReduce is to break a large dataset into smaller chunks, distribute them across multiple nodes in a cluster, and process them in parallel. The processing is divided into two phases: a Map phase and a Reduce phase.

In the Map phase, the input dataset is processed by a set of Map functions in parallel. Each Map function takes a key-value pair as input and produces a set of intermediate key-value pairs as output.

These intermediate key-value pairs are then sorted and partitioned by key, and sent to the Reduce phase.

In the Reduce phase, the intermediate key-value pairs are processed by a set of Reduce functions in parallel. Each Reduce function takes a key and a set of values as input, and produces a set of output key-value pairs.

Here is an example of how MapReduce can be used to count the frequency of words in a large text file:

Map phase: Each Map function reads a chunk of the input file and outputs a set of intermediate key-value pairs, where the key is a word and the value is the number of occurrences of that word in the chunk.
Shuffle phase: The intermediate key-value pairs are sorted and partitioned by key, so that all the occurrences of each word are grouped together.
Reduce phase: Each Reduce function takes a word and a set of occurrences as input, and outputs a key-value pair where the key is the word and the value is the total number of occurrences of that word in the input file.

The MapReduce framework takes care of the parallel processing, distribution, and fault tolerance of the computation. This allows it to process large datasets efficiently and reliably, even on clusters of commodity hardware.

3. Distributed Hash Tables (DHT)

A Distributed Hash Table (DHT) is a distributed system that provides a decentralized key-value store. It is used in peer-to-peer (P2P) networks to store and retrieve information in a scalable and fault-tolerant manner.

In a DHT, each participating node stores a subset of the key-value pairs, and a mapping function is used to assign keys to nodes.

This allows nodes to locate the value associated with a given key by querying only a small subset of nodes, typically those responsible for keys close to the given key in the mapping space.

DHTs provide several desirable properties, such as self-organization, fault-tolerance, load-balancing, and efficient routing. They are commonly used in P2P file sharing systems, content distribution networks, and distributed databases.

One popular DHT algorithm is the Chord protocol, which uses a ring-based topology and a consistent hashing function to assign keys to nodes. Another widely used DHT is the Kademlia protocol, which uses a binary tree-like structure to locate nodes responsible for a given key.

4. Bloom Filters

Bloom Filters are a probabilistic data structure used for efficient set membership tests. They were introduced by Burton Howard Bloom in 1970.

A Bloom Filter is a space-efficient probabilistic data structure that is used to test whether an element is a member of a set or not. It uses a bit array and a set of hash functions to store and check for the presence of an element in a set.

The process of adding an element to a Bloom Filter involves passing the element through a set of hash functions which returns a set of indices in the bit array. These indices are then set to 1 in the bit array.

To check whether an element is present in the set or not, the same hash functions are applied to the element and the resulting indices are checked in the bit array.

If all the bits at the indices are set to 1, then the element is considered to be present in the set. However, if any of the bits are not set, the element is considered to be absent from the set.

Since Bloom Filters use hash functions to index the bit array, there is a possibility of false positives, i.e., the filter may incorrectly indicate that an element is present in the set when it is not.

However, the probability of a false positive can be controlled by adjusting the size of the bit array and the number of hash functions used.

The false negative rate, i.e., the probability of a Bloom filter failing to identify an element that is actually present in the set, is zero.

Bloom Filters are widely used in various fields such as networking, databases, and web caching to perform efficient set membership tests.

5. 2 Phase Commit

Two-phase commit (2PC) is a protocol used to ensure the atomicity and consistency of transactions in distributed systems. It is a way to guarantee that all nodes participating in a transaction either commit or rollback together.

The two-phase commit protocol works in two phases:

Prepare Phase: In the prepare phase, the coordinator node sends a message to all participating nodes, asking them to prepare to commit the transaction.

Each participant responds with a message indicating whether it is prepared to commit or not. If any participant cannot prepare, it responds with a message indicating that it cannot participate in the transaction.

Commit Phase: If all participants are prepared to commit, the coordinator sends a message to all nodes asking them to commit. Each participant commits the transaction and sends an acknowledgement to the coordinator.

If any participant cannot commit, it rolls back the transaction and sends a message to the coordinator indicating that it has rolled back.

If the coordinator receives acknowledgements from all participants, it sends a message to all nodes indicating that the transaction has been committed.

If the coordinator receives a rollback message from any participant, it sends a message to all nodes indicating that the transaction has been rolled back.

The two-phase commit protocol ensures that all nodes in a distributed system agree on the outcome of a transaction, even in the presence of failures.

However, it has some drawbacks, including increased latency and the possibility of deadlock. Additionally, it requires a coordinator node, which can be a single point of failure.

6. Paxos

Paxos is a distributed consensus algorithm that allows a group of nodes to agree on a common value, even in the presence of failures. It was introduced by Leslie Lamport in 1998 and has become a fundamental algorithm for distributed systems.

The Paxos algorithm is designed to handle a variety of failure scenarios, including message loss, duplication, reordering, and node failures.

The algorithm proceeds in two phases: the prepare phase and the accept phase. In the prepare phase, a node sends a prepare message to all other nodes, asking them to promise not to accept any proposal with a number less than a certain value.

Once a majority of nodes have responded with promises, the node can proceed to the accept phase. In the accept phase, the node sends an accept message to all other nodes, proposing a certain value.

If a majority of nodes respond with an acceptance message, the value is considered accepted.

Paxos is a complex algorithm, and there are several variations and optimizations of it, such as Multi-Paxos, Fast Paxos, and others.

These variations aim to reduce the number of messages exchanged, optimize the latency of the algorithm, and reduce the number of nodes that need to participate in the consensus. Paxos is widely used in distributed databases, file systems, and other distributed systems where a high degree of fault tolerance is required.

7. Raft

Raft is a consensus algorithm designed to ensure fault-tolerance in distributed systems. It is used to maintain a replicated log that stores a sequence of state changes across multiple nodes in a cluster.

Raft achieves consensus by electing a leader, which coordinates the communication among the nodes and ensures that the log is consistent across the cluster.

The Raft algorithm consists of three main components: leader election, log replication, and safety. In the leader election phase, nodes in the cluster elect a leader using a randomized timeout mechanism.

The leader then coordinates the log replication by receiving state changes from clients and replicating them across the nodes in the cluster. Nodes can also request entries from the leader to ensure consistency across the cluster.

The safety component of Raft ensures that the algorithm is resilient to failures and ensures that the log is consistent across the cluster.

Raft achieves safety by ensuring that only one node can be the leader at any given time and by enforcing a strict ordering of log entries across the cluster.

Raft is widely used in distributed systems to provide fault-tolerance and high availability. It is often used in systems that require strong consistency guarantees, such as distributed databases and key-value stores.

8. Gossip

The gossip protocol is a peer-to-peer communication protocol used in distributed systems to disseminate information quickly and efficiently.

It is a probabilistic protocol that allows nodes to exchange information about their state with their neighbors in a decentralized manner.

The protocol gets its name from the way it spreads information like a rumor or gossip.

In a gossip protocol, nodes randomly select a set of other nodes to exchange information with. When a node receives information from another node, it then forwards that information to a subset of its neighbors, and the process continues.

Over time, the entire network becomes aware of the information as it spreads from node to node.

One of the key benefits of the gossip protocol is its fault-tolerance. Since the protocol relies on probabilistic communication rather than a central authority, it can continue to function even if some nodes fail or drop out of the network.

This makes it a useful tool in distributed systems where reliability is a critical concern.

Gossip protocols have been used in a variety of applications, including distributed databases, peer-to-peer file sharing networks, and large-scale sensor networks.

They are particularly well-suited to applications that require fast and efficient dissemination of information across a large number of nodes.

9. Chrod

Chord is a distributed hash table (DHT) protocol used for decentralized peer-to-peer (P2P) systems. It provides an efficient way to locate a node (or a set of nodes) in a P2P network given its identifier.

Chord allows P2P systems to scale to very large numbers of nodes while maintaining low overhead.

In a Chord network, each node is assigned an identifier, which can be any m-bit number. The nodes are arranged in a ring, where the nodes are ordered based on their identifiers in a clockwise direction.

Each node is responsible for a set of keys, which can be any value in the range of 0 to 2^m-1.

To find a key in the network, a node first calculates its hash value and then contacts the node whose identifier is the first clockwise successor of that hash value.

If the successor node does not have the desired key, it forwards the request to its successor, and so on, until the key is found. This process is known as a finger lookup, and it typically requires a logarithmic number of messages to find the desired node.

To maintain the consistency of the network, Chord uses a protocol called finger tables, which store information about other nodes in the network.

Each node maintains a finger table that contains the identifiers of its successors at increasing distances in the ring. This allows nodes to efficiently locate other nodes in the network without having to maintain a complete list of all nodes.

Chord also provides mechanisms for maintaining consistency when nodes join or leave the network. When a node joins the network, it notifies its immediate successor, which updates its finger table accordingly.

When a node leaves the network, its keys are transferred to its successor node, and the successor node updates its finger table to reflect the departure.

Overall, Chord provides an efficient and scalable way to locate nodes in a P2P network using a simple and decentralized protocol.

10. CAP Theorem

The CAP theorem, also known as Brewer's theorem, is a fundamental concept in distributed systems that states that it is impossible for a distributed system to simultaneously guarantee all of the following three properties:

Consistency: Every read receives the most recent write or an error.
Availability: Every request receives a response, without guarantee that it contains the most recent version of the information.
Partition tolerance: The system continues to function and provide consistent and available services even when network partitions occur.

In other words, a distributed system can only provide two out of the three properties mentioned above.

This theorem implies that in the event of a network partition, a distributed system must choose between consistency and availability.

For example, in a partitioned system, if one node cannot communicate with another node, it must either return an error or provide a potentially stale response.

The CAP theorem has significant implications for designing distributed systems, as it requires developers to make trade-offs between consistency, availability, and partition tolerance.

Conclusion

That's all about the essential System Design Data Structure, Algorithms and Protocol You can learn in 2023. In conclusion, system design is an essential skill for software engineers, especially those working on large-scale distributed systems.

These ten algorithms, data structure, and protocols provide a solid foundation for tackling complex problems and building scalable, reliable systems. By understanding these algorithms and their trade-offs, you can make informed decisions when designing and implementing systems.

Additionally, learning these algorithms can help you prepare for system design interviews and improve their problem-solving skills. However, it's important to note that these algorithms are just a starting point, and you should continue to learn and adapt as technology evolves.

By the way, if you are preparing for System design interviews and want to learn System Design in depth then you can also checkout sites like ByteByteGo, Design Guru, Exponent, Educative, Codemia.io, bugfree.ai and Udemy which have many great System design courses, and these popular System design YouTube channels, which have many great System design courses and tutorials.

Also, here is a nice System design template from DesignGuru which you can use to answer any System design question on interviews. It highlights key software architecture components and allows you to express your knowledge well.

All the best for your System design interviews!!

50+ Core Java Interview Questions for 1 to 3 Years Experienced Developers

2026-02-18T03:32:00.000-08:00

Disclosure: This post includes affiliate links; I may receive compensation if you purchase products or services from the different links provided in this article.

Hello devs, are you preparing for Java developer interviews? If Yes, here is a list of some useful Java interview questions for experienced Java programmers having experience in range of 2 to 5 years.

As an experienced developer you are expected to learn about OOP concepts, Java basics, Java Collection framework, Multi-threading and Concurrency utilities introduced in Java 5 and 6, Debugging Java application, Algorithm and Data structure, Some questions on design patterns, JVM and Garbage collection and couple of puzzles.

Actually its mix of everything you do in your day to day work.

If you are going for Java developer with some exposure on web development you will also be asked about popular Java frameworks like Spring, Hibernate, Struts 2.0 and others.

If you have more than 5 years of experience you can also expect questions about build tools like Maven, ANT and Gradle, Java best practices, Unit testing and JUnit and your experience about solving production issues.

One of the most common question I have faced is talking about the last production problem you have faced and how did you solved it.

If you are asked same question, give them step by step detail, right from analyzing problem to tactical fix to strategic solution.

In this article, I am going to share my list of Java Interview question for Java guys having 2 to 5 years of experience. Since I had similar experience couple of year ago, I know what questions are asked and keeping a list for your own always helps when you start looking for new challenge in your career.

I am not providing answers of these question in this post due to two reasons, questions are quite simple and you guys probably know the answer, second providing answer means I cannot use this post for my own preparation later, which is more important.

Though, I could write another article answering all these question if anyone request or I feel people need it.

By the way, if you are new to Java programming language or want to improve Java skills then you can also checkout sites like CodeGym, ZTM and karpado to learn Java by building Games and projects.

Java Interview Questions for 1 to 2 years Experienced

This list contains questions from different topics e.g. OOP concepts, multi-threading and concurrency, Java collections, Web services, Spring, Hibernate, Database and JDBC, it doesn't cover all topics you need to prepare.

I will add few more topics later when I have some time, for now, try to answer these questions without doing Google :)

Java Interview questions on OOP Concepts

Here are a couple of questions on OOP design, SOLID principle and baseic programming concepts

1. What is the difference between loose coupling and tight coupling?
Loose coupling allows components to interact with each other with minimal dependencies, while tight coupling creates strong dependencies between components.

2. What is the difference between cohesion and coupling?
Cohesion refers to the degree to which elements within a module belong together, while coupling refers to the degree of interdependence between modules.

3. What is Liskov Substitution principle? Can you explain with an example?
Liskov Substitution principle states that objects of a superclass should be replaceable with objects of its subclasses without affecting the correctness of the program.

For example, if you have a class hierarchy with a superclass "Shape" and subclasses "Circle" and "Square", any method that works with Shape should also work with Circle or Square without causing errors.

4. What is the difference between abstract class and interface in Java?
Abstract classes can have both abstract and concrete methods, while interfaces can only have abstract methods. Additionally, a class can implement multiple interfaces but can only extend one abstract class.

5. What is the difference between composition, aggregation, and association?
Composition implies a strong ownership relationship where the lifetime of the contained object is dependent on the container.

Aggregation implies a weaker relationship where the contained object can exist independently of the container. Association implies a relationship between two classes without any ownership or lifecycle dependency.

Java Interview questions on Collections

Now, let's see a few questions form Collections and Stream

1. Difference between List, Set, and Map in Java?
Lists maintain elements in sequential order and allow duplicates (e.g., ArrayList, LinkedList). Sets do not allow duplicates and do not guarantee order (e.g., HashSet, TreeSet). Maps store key-value pairs and do not allow duplicate keys (e.g., HashMap, TreeMap).

2. Difference between synchronized and concurrent collection in Java?
Synchronized collections use explicit locking to achieve thread-safety, allowing only one thread to modify the collection at a time. Concurrent collections use non-blocking algorithms and are designed for high concurrency, allowing multiple threads to modify the collection concurrently without explicit locking.

3. How does the get method of HashMap work in Java?
The get method of HashMap calculates the hash code of the provided key, determines the index in the underlying array based on the hash code, and then searches for the key at that index. If found, it returns the corresponding value; otherwise, it returns null.

4. How is ConcurrentHashMap different from Hashtable? How does it achieve thread-safety?
ConcurrentHashMap allows concurrent access to the map without blocking, while Hashtable uses synchronized methods to achieve thread-safety, resulting in potential performance bottlenecks. ConcurrentHashMap achieves thread-safety by dividing the map into segments, each with its lock, allowing multiple threads to modify different segments concurrently.

5. When to use LinkedList over ArrayList in Java?
Use LinkedList when frequent insertion and deletion operations are required, as LinkedList provides constant-time insertion and deletion at any position. Use ArrayList when random access and iteration are frequent, as ArrayList provides constant-time access by index.

Java Interview questions on Concurrency and Threads

Now, its time to see questions from Java multithreading and concurrency concepts:

1. How do notify and notifyAll work, and what's the difference between them? Why prefer notifyAll to notify?
Both notify and notifyAll are methods in Java used to wake up threads waiting on a monitor (i.e., waiting to acquire an object's lock). notify wakes up one randomly selected thread, while notifyAll wakes up all waiting threads. notifyAll is preferred because it ensures that all waiting threads are notified, preventing potential indefinite waiting and improving system responsiveness.

2. What is a race condition and how do you avoid it?
A race condition occurs when the outcome of a program depends on the timing or interleaving of multiple threads. To avoid race conditions, you can use synchronization mechanisms like locks, semaphores, or atomic operations to ensure that critical sections of code are executed atomically or only by one thread at a time.

3. What is a deadlock and how do you avoid it?
Deadlock occurs when two or more threads are stuck waiting for each other to release resources that they need to proceed. To avoid deadlock, you can use techniques such as resource ordering, avoiding nested locks, or using timeouts for acquiring locks. Additionally, designing code with a clear and consistent locking order can help prevent deadlocks.

4. What are some of the high-level concurrency classes provided by java.util.concurrent and how do they work?
Some high-level concurrency classes provided by java.util.concurrent include ExecutorService, ThreadPoolExecutor, CountDownLatch, Semaphore, CyclicBarrier, BlockingQueue, and ConcurrentHashMap. These classes provide thread-safe implementations of common concurrency patterns and mechanisms like thread pools, synchronization primitives, and concurrent data structures.

5. Can you implement a producer-consumer solution in Java?
Yes, here is the code:



import java.util.concurrent.ArrayBlockingQueue;

class Producer implements Runnable {
    private final ArrayBlockingQueue<Integer> queue;
    private int count = 0;

    Producer(ArrayBlockingQueue<Integer> queue) {
        this.queue = queue;
    }

    public void run() {
        try {
            while (true) {
                queue.put(produce());
                Thread.sleep(1000); // Simulate some work
            }
        } catch (InterruptedException e) {
            Thread.currentThread().interrupt();
        }
    }

    private int produce() {
        System.out.println("Producing: " + count);
        return count++;
    }
}

class Consumer implements Runnable {
    private final ArrayBlockingQueue<Integer> queue;

    Consumer(ArrayBlockingQueue<Integer> queue) {
        this.queue = queue;
    }

    public void run() {
        try {
            while (true) {
                consume(queue.take());
            }
        } catch (InterruptedException e) {
            Thread.currentThread().interrupt();
        }
    }

    private void consume(int item) {
        System.out.println("Consuming: " + item);
    }
}

public class Main {
    public static void main(String[] args) {
        ArrayBlockingQueue<Integer> queue = new ArrayBlockingQueue<>(10);
        Producer producer = new Producer(queue);
        Consumer consumer = new Consumer(queue);

        Thread producerThread = new Thread(producer);
        Thread consumerThread = new Thread(consumer);

        producerThread.start();
        consumerThread.start();
    }
}

Java Interview questions on Database, SQL, and JDBC

JDBC is used for connecting database from Java program, let's ee a few questions on Database and JDBC
1. How do you prevent SQL injection attacks?
To prevent SQL injection attacks, use parameterized queries (prepared statements) with bound parameters, input validation, and escape characters. Avoid dynamic SQL queries constructed by concatenating user input.

2. What is the difference between WHERE and HAVING clause? The WHERE clause filters rows before the grouping and aggregation process, while the HAVING clause filters aggregated data after the grouping process based on specified conditions.

3. What are transactions? What is ACID?
Transactions are a set of SQL statements that are executed as a single unit of work. ACID is an acronym for Atomicity, Consistency, Isolation, and Durability, which are properties that ensure the reliability of transactions in a database system.

4. Difference between truncate, delete, and drop clause in SQL?

TRUNCATE: Removes all rows from a table but retains the table structure and any associated constraints or indexes.
DELETE: Removes specific rows from a table based on a condition, but retains the table structure and associated constraints.
DROP: Deletes an entire table, including its structure, data, and associated constraints and indexes.

5. What are window functions? How do they work?
Window functions perform calculations across a set of rows related to the current row within a query result set. They allow you to perform aggregate functions (such as SUM, AVG, COUNT) over a specified window or subset of rows, defined by the OVER clause. Window functions operate on a set of rows and return a single value for each row based on that set of rows. They are often used for tasks such as ranking, aggregation, and calculating running totals.

See, Grokking the SQL Interview book if you need more questions on Database and SQL

Java Interview questions on Hibernate

Now, its time to see questions from Hibernate, one of the popular Java framework:

1. When is it better to use plain SQL instead of ORM?
It's better to use plain SQL when:

Complex queries need to be optimized for performance.
The database schema or query requirements are not well-supported by the ORM framework.
Direct control over SQL statements, database connections, or transactions is required.

2. Difference between sorted and ordered collection?
In Java, a sorted collection maintains elements in a specific order defined by a comparator or by the natural ordering of elements, while an ordered collection maintains elements in the order they were inserted.

3. How does second level cache work?
Second level cache in Hibernate stores objects in a shared cache region, typically across multiple sessions. When an entity is queried for the first time, it is fetched from the database and stored in the second level cache. Subsequent queries for the same entity can then be satisfied from the cache instead of hitting the database, improving performance.

4. What is the difference between save() and persist() in Hibernate?
Both save() and persist() methods in Hibernate are used to save an entity to the database. However, save() returns the generated identifier immediately, while persist() doesn't guarantee immediate execution of the SQL INSERT statement; it may be executed later during flush time. Additionally, persist() is part of the JPA specification, while save() is specific to Hibernate.

5. What is the difference between Hibernate and MyBatis?

Hibernate is a full-fledged ORM framework that maps Java objects to database tables, manages database connections, and provides various querying mechanisms. MyBatis, on the other hand, is a lightweight persistence framework that uses SQL mapping files to map Java objects to SQL queries.
Hibernate is typically used for domain-driven development, where object-oriented modeling is prominent, while MyBatis is often preferred for projects where direct control over SQL queries is required, such as legacy database systems or complex SQL scenarios.
Hibernate provides caching mechanisms, automatic dirty checking, and transaction management, while MyBatis offers more control over SQL queries and mappings, allowing developers to write SQL queries directly.

Java Interview questions on Web Services and Microservices

Now, let's see questions form Microservice architecture and REST web services

1. Difference between SOAP-based and REST-based web services? SOAP is protocol-based with rigid structure, while REST is architectural style based on stateless communication with flexible endpoints.

2. What is SOAP Envelope?
It encapsulates the entire SOAP message and defines its structure.

3. How to implement security in RESTful web service?
Implement SSL/TLS for encryption and authentication.

4. What is Payload in REST?
It's the data transmitted in the body of the HTTP request or response.

5. What is Microservices? It's an architectural style where applications are composed of small, independent services.

6. What is the difference between Microservices and REST? Microservices refer to architectural design, while REST is an architectural style for networked applications.

7. What is the difference between Monolithic and Microservices?
Monolithic has single codebase, while Microservices have multiple, independent components; Monolithic can have higher latency.

8. What problem does SAGA pattern solve?
It manages distributed transactions in Microservices architecture.

9. What is service discovery in Microservices?
It's the mechanism for locating services dynamically within a Microservices architecture.

10. What are common Microservices Patterns you have used in your project?
Service Registry, Circuit Breaker, API Gateway.

Java and Spring Interview Preparation Material

Before any Java and Spring Developer interview, I always read the Grokking the Java Interview and Grokking the Spring boot Interviw

Here are few more questions from these books:

and,

And, if you are new to Java then you can also checkout sites like CodeGym, ZTM and karpado to learn Java by building Games and projects.

Thank you guys for now. You can find the answers in web easily but if there are enough interest, I can also update the post. Let me know if you have also asked these questions before. If anyone knows answer, can also post as comment.

Good luck for your Java Interview.

By the way, if you are new to Java programming language or want to improve Java skills then you can also checkout following best Java courses to get better:

Microservices vs Monolithic Architecture for System Design Interview

2026-02-16T23:44:00.000-08:00

image_credit - DesignGuru

Hello friends, if you are preparing for a System design interview, then you must have come across questions on Microservices architecture.

In the last few articles, I have answered popular System design questions like API Gateway vs Load Balancer and Horizontal vs Vertical Scaling, Forward proxy vs reverse proxy, and today, I will answer another interesting System design question, *"difference between monolith and Micro service architecture?".

With the growing popularity of Microservices, I am seeing more and more questions from Microservices on System Design Interviews, and this is one of the starter questions.

In system design interviews, understanding the difference between microservices and monolithic applications is crucial. While monolithic architectures offer simplicity and ease of development, microservices provide scalability, flexibility, and resilience through their distributed nature and modular design.

For example, in the case of monolith architecture, your entire application is packaged and deployed together, while in the case of Microservices architecture, an application is broken into a collection of small, independent services that communicate with each other over a network, mostly over HTTP.**

Each service is responsible for a specific business capability and can be developed, deployed, and scaled independently. This makes it easier to make changes to the application without affecting other parts of the system.

Microservices also enable applications to be developed and deployed faster, and they are better suited to large and complex applications where different parts of the application may need to evolve at different speeds.

By the way, Microservices are not a silver bullet, there are debugging and troubleshooting issues with Microservices because application log files are scattered across multiple services.

Also, for a latency-sensitive application, Microservices is not a good choice because it increases latency.

Now that we are familiar with the basic idea of Microservices and Monolithic architecture, it's time to dive deep and see the pros and cons of both software architectures.

By the way, if you are in a hurry, then the diagram from DesignGurus.io, one of the best resources for system design interviews and creator of Grokking the System Design Interview nicely explains it; he even added a comparison to serverless architecture:

And, if you are preparing for a System design interview, along with Design Guru, Educative, ByteByteGo, and Exponent are great resources to further improve your preparation.

Difference between Monolithic vs Microservices Architecture

Now that you have a basic idea of what Microservices offer in terms of Monolithic applications, it makes sense to deep dive and find out more technical differences between these two architecture style to build software applications.

Here are the key differences, advantages, and disadvantages of Monolithic and Microservices architecture:

1. Deployment and Management

Monolithic applications are simple to deploy and manage, since all components are included in a single package, but Microservices are complex to deploy and manage, since each service is deployed independently and must communicate with other services over a network.

Microservice architecture also have increased operational overhead, as each service must be deployed, monitored, and managed individually.

2. Easy to Understand

In the case of Monolithic architecture its easy to understand the entire system, since all components are integrated tightly, while its difficult to understand the flow in Microservices because of multiple services.

3. Debugging

Monolithic applications are easier to debug as compared to Microservices because the entire application runs in a single process, while Debugging can be more difficult in Microservice architecture, since issues can span multiple services.

For example, if data is updated in one service it can have origin in some other service like authentication or authorization

4. Development

Microservices promote flexible development and are better suited to large and complex applications where different parts of the application may need to evolve at different speeds.

While Microservices are better suited for small, latency sensitive application. In short, Microservices enable faster development and deployment, since services can be developed and deployed independently.

5. Coupling

In the case of Monolithic architecture, components are tightly coupled, which makes it difficult to make changes to the application without causing unintended consequences, while microservices promote low coupling.

It's also easier to make changes to the application, since each service is responsible for a specific business capability.

6. Maintainence

Monolithic applications are easier to start but difficult to maintain. As the application grows, the code base becomes larger and more complex, making it harder to maintain.

On the other hand, Microservices are easier to maintain as you can make changes in one service without deploying other services.

7. Performance and Scalability

Microservice architecture allows for better scalability and performance improvement, since each service can be scaled independently, while performance bottlenecks can easily happen in a monolithic application, since all components share the same resources.

In short, while monolithic architectures offer simplicity and ease of development, microservices provide scalability, flexibility, and resilience through their distributed nature and modular design. So both have their places.

And, here is also a nice diagram to highlight the difference between API Gateway and Load Balancer from ByteByteGo, one of the best places to prepare for System design interviews

That's all about difference between Microservices and monolithic architecture and applications. As I said, monolithic architecture is simpler and easier to deploy and manage, but is less flexible and harder to change. Microservices architecture is more flexible and easier to change, but is more complex and harder to deploy and manage.

While Microservices is latest trend in Software development, and a well-designed microservices architecture can provide benefits such as scalability and faster development, especially on the cloud, it requires a more complex deployment and management infrastructure.

On the other hand, a well-designed monolithic architecture can provide benefits such as simpler deployment and easier debugging, but can become more difficult to change as the application grows.

This is a really useful concept for System design interviews, especially Microservice architecture, and you shouldn't miss out on that. For better preparation, I also suggest checking out sites like DesignGurus, Educative, ByteByteGo, and Exponent, all of which are great resources for tech interview preparation, particularly System design.

Forward Proxy vs Reverse Proxy in System design

2026-02-13T23:01:00.000-08:00

Disclosure: This post includes affiliate links; I may receive compensation if you purchase products or services from the different links provided in this article.

image_credit - DesignGurus.io

Hello folks, in last few article, I was answering popular System design questions like API Gateway vs Load Balancer and Horizontal vs Vertical Scaling, and today, we are going to take a look at another interesting System design question, Reverse Proxy vs Forward Proxy.

These questions are different than system design problems like how to design WhatsApp and YouTube but they are equally important and if you have knowledge of them you can mention in most of the system design problems.

Now coming back to the topic, In network architecture world, proxies play a pivotal role in managing and securing communication between clients and servers.

There are two common types of proxies, forward and reverse proxies, they serve distinct purposes and operate at different layers of the networking stack. Forward proxies are used to shield clients from external networks while Reverse proxy acts as a frontend Facade for backend Servers, much like API Gatewawy and load balancers.

Let's go deep into the intricacies of forward and reverse proxies to know their differences and understand their respective roles in system design.

By the way, if you are in hurry then below diagram from DesignGuru.io, one of the best resource for system design interviews and creator of Grokking the System Design Interview nicely explain it:

What is Forward Proxy?

A forward proxy, also known as an outbound proxy, acts as an intermediary between clients and external servers, intercepting outbound requests from clients and forwarding them to their intended destinations.

Here is what forward proxies do for you:

Client-Side Proxying
Forward proxies are typically deployed on the client side of a network, serving as a gateway for outbound traffic. Clients configure their network settings to route traffic through the forward proxy, which then forwards requests to external servers on behalf of the clients.
Anonymity and Privacy
Forward proxies can enhance user privacy and anonymity by masking the IP addresses of clients. External servers only see the IP address of the forward proxy, making it difficult to trace the origin of requests back to individual clients.
Content Filtering and Caching
Forward proxies can implement content filtering policies to restrict access to certain websites or content categories based on predefined rules. Additionally, they can cache frequently accessed content, reducing bandwidth usage and improving performance for subsequent requests.
Security and Access Control
Forward proxies can also enforce security policies and access controls, allowing organizations to regulate access to external resources, block malicious websites, and inspect outbound traffic for threats or policy violations.

You can see in the diagram below that the forward proxy routes user requests to back-end servers

By the way, if you are preparing for System design interviews and want to learn System Design in depth then you can also checkout sites like ByteByteGo, Design Guru, Exponent, Educative, Codemia.io, bugfree.ai and Udemy which have many great System design courses

Now that we know what a forward proxy is let's take a look at a reverse proxy and what services it provides:

What is a Reverse Proxy?

A reverse proxy, also known as an inbound proxy, operates on the server side of a network, serving as a front-end facade for backend servers.

It intercepts incoming requests from clients and forwards them to the appropriate back-end servers based on predefined rules.

Key aspects of reverse proxies include:

Server-Side Proxying
Reverse proxies are deployed on the server side of a network, typically in front of backend web servers or application servers. They accept incoming requests from clients on behalf of backend servers and forward them internally.
Load Balancing and Traffic Distribution
Reverse proxies can distribute incoming traffic across multiple backend servers to improve scalability, reliability, and performance. They use algorithms such as round-robin, least connections, or weighted distribution to evenly distribute requests.
SSL Termination and Encryption
Reverse proxies can handle SSL/TLS termination, offloading the encryption and decryption process from backend servers. This simplifies management of SSL certificates and improves performance by reducing the computational overhead on backend servers.
Content Delivery and Optimization
Reverse proxies can cache static content, compress data, and optimize delivery to clients, reducing latency and bandwidth usage. They can also perform content rewriting or transformation to adapt content for different client devices or browsers.

Here is also a nice diagram which shows how reverse proxy work which is quite useful for system design interview, and if you are preparing for one, Educative.io's Modern System Design Guide is another awesome resource I recommend.

Difference between Forward and Reverse Proxies and Use Cases

While both forward and reverse proxies act as intermediaries in network communication, their primary objectives and deployment scenarios differ:

For example, Forward proxy is primarily used to shield clients from external networks, enhance privacy and security, and enforce access controls and it's ideal for individual users, organizations, or networks requiring outbound traffic management and anonymity.

On the other hand, Reverse Proxy is primarily used to front-end backend servers, improve scalability and performance, and provide centralized management of incoming traffic.

It is ideal for web servers, application servers, or microservices architectures requiring load balancing, SSL termination, and content optimization.

And, here is a nice diagram which highlights the difference between Forward Proxy and Reverse Proxy from ByteByteGo, one of the best places to learn System Design for interviews. If you are preparing for a system design interview, you should definitely check it out. They also have an awesome YouTube channel.

Conclusion

In conclusion, both forward and reverse proxies are indispensable components in modern network architectures, each serving unique purposes and offering distinct capabilities.

While forward proxies focus on client-side traffic management and security, reverse proxies excel at server-side load balancing, scalability, and optimization.

Understanding their differences is essential for designing resilient, efficient, and secure systems that meet the diverse needs of modern applications and services.

And, if you are preparing for a system design interview, then you may also like my previous articles

Thank you !!

Difference between API Gateway vs Load Balancer in Software Design / Microservices Architecture

2026-02-12T06:52:00.000-08:00

Disclosure: This post includes affiliate links; I may receive compensation if you purchase products or services from the different links provided in this article.
image_credit - DesignGurus ,

Hello folks, if you are preparing for System design interviews then you must have come across popular questions like difference between API Gateway vs Load Balancer, horizontal scalability vs vertical scaling, and Reverse Proxy vs Forward Proxy.

Earlier, I have shared popular System design interview problems and in this article, I will answer the first question so that you not only can answer this question on interviews but also learn this important concept well.

In the web services world and network infrastructure, two crucial components often come into play: API gateways and load balancers.

While they both play critical roles in managing and optimizing traffic flow, they serve distinct purposes and operate at different layers of the technology stack.

Understanding the difference between these two components is not just important for System design interview but also essential for designing robust and scalable architectures. Let's delve into the nuances of API gateways and load balancers to demystify their differences.

But, let's first see what is API Gateway?

Btw, here is also a nice diagram from DesignGurus ,, one of the best place to prepare for system design interviews. This diagram highlights the key difference between API Gateway and Load balancer

By the way, If you are preparing for System design interviews and want to learn System Design in depth then you can also checkout sites like ByteByteGo, DesignGurus , Exponent, Educative , bugfree.ai and Udemy which have many great System design courses.

What is API Gateway? How does it work?

An API gateway acts as a middleware component that sits between clients and backend services, providing a centralized entry point for accessing various endpoints and functionalities.

Its primary function is to facilitate communication, security, and management of APIs. Here are key aspects of API gateways:

API Management
API gateways offer features for managing APIs, including authentication, authorization, rate limiting, and caching. They serve as a control point for enforcing security policies and access control measures.
Protocol Transformation
API gateways can handle protocol translation, allowing clients to communicate with backend services using different protocols or message formats. This capability enhances interoperability in heterogeneous environments.
Routing and Versioning
With an API gateway, requests can be routed to the appropriate backend service based on predefined rules and configurations.

Additionally, versioning support enables the coexistence of multiple API versions, ensuring backward compatibility and smooth migrations.

Analytics and Monitoring API gateways provide insights into API usage, performance metrics, and error tracking. This visibility enables operators to monitor the health of APIs, identify bottlenecks, and optimize resource utilization.

Here is a nice diagram of how API Gateway looks like:

What is Load Balancer? How it works?

A load balancer acts as a traffic distributor, evenly distributing incoming requests across multiple backend servers or instances to optimize resource utilization, improve availability, and enhance performance. Here are key aspects of load balancers:

Traffic Distribution
Load balancers distribute incoming traffic across multiple backend servers or instances based on predefined algorithms such as round-robin, least connections, or weighted distribution. This ensures efficient utilization of resources and prevents overloading of individual servers.
High Availability
Load balancers enhance the availability of services by intelligently routing traffic away from unhealthy or overloaded servers. They perform health checks to monitor the status of backend instances and dynamically adjust traffic routing accordingly.
Session Persistence
In scenarios where maintaining session state is crucial, load balancers support session persistence or sticky sessions, ensuring that subsequent requests from the same client are directed to the same backend server. This ensures consistency and avoids session-related issues.
SSL Termination
Load balancers can offload SSL/TLS encryption and decryption, relieving backend servers from the computational overhead associated with SSL processing. This improves performance and simplifies management of SSL certificates.

Here is how a load balancer look like and how it works:

Difference between API Gateway and Load Balancer?

While API gateways and load balancers share some similarities in terms of traffic management, their primary objectives and functionalities differ:

API Gateway: Focuses on API management, security, protocol transformation, and analytics. Ideal for exposing and managing APIs to external clients, enforcing access control policies, and providing a unified interface for diverse backend services.
Load Balancer: Primarily concerned with traffic distribution, high availability, and scalability. Suitable for distributing incoming traffic across multiple backend servers or instances to improve performance, reliability, and fault tolerance.

Here is also a nice diagram to highlight the difference between API Gateway and Load Balancer from ByteByteGo, one of the best place to prepare for System design interviews

System Design Interview Preparation Resources

If you are preparing for System design interviews and want to learn System Design in depth then you can also checkout sites like ByteByteGo, DesignGurus , Exponent, Educative , bugfree.ai and Udemy which have many great System design courses.

And, If you need free system design courses you can also see this article which is full of free system design courses

Conclusion

In summary, both API gateways and load balancers are fundamental components in modern network architectures, each serving distinct purposes and offering unique capabilities.

While API gateways specialize in API management and security, load balancers excel at distributing traffic for improved availability and scalability.

Understanding their differences is essential for designing resilient and efficient systems that meet the evolving demands of modern applications and services.

Difference between Horizontal scaling vs Vertical Scaling in System Design ?

2026-02-10T06:54:00.000-08:00

image_credit - DesignGuru.io

Hello friends, one question which I have been asked repeatedly on many System design and Java Developer interviews are how do you scale your system? In particular how do you scale your Microservices?

This is a great question to ask any experienced developers because its open ended and its gives an opportunity to candidate to express themselves and also interviewers to know more about their knowledge, experience, and thought process.

Thanks to my habit of reading blogs and articles, I feel I am little bit more familiar with new concepts and terms compared to my competition.

So, when I was first asked this question on senior Java developer role and I mentioned that there are two ways to scale your application either horizontally or vertically then the interviewer was really impressed because he himself have never heard about the term, even though he may be familiar with the concept and process.

Now, you can say that I got lucky which is true but I was able to make an impression because I read blogs and articles and I can use buzz words and demonstrate that I understand them.

In this article, I will tell you the exact difference between horizontal and vertical scaling and when to use one over other so that you can impress your interviews.

Also, In past few articles I have been sharing my experience on Microservices like 50 Microservices Interview questions, 10 Microservice design principles, and 10 Microservice Patterns which I shared earlier as well my article about SAGA Design Pattern and Monolithic vs Microservices architecture.

Now, coming back to the topic, Horizontal scalability and vertical scalability are two approaches to scale any system including Microservices to handle increased load or to meet performance requirements.

The main difference between them lies in how they achieve scaling.**

Horizontal scalability, also known as scale-out, scale your system by adding more nodes or servers to distribute the load across them.

Horizontal scaling is achieved by adding more identical machines to the existing system, which allows for better distribution of load and improved redundancy.

This was tough say 5 to 10 years ago when you have to manually acquire server and install all the software, create new configuration and deploy your application but now in this age of Cloud Computing and tools like Terraform, Ansible, and Puppet, you can easily add more machine for your application without much fuss.

On the other hand, vertical scalability, also known as scale-up, involves adding more resources (such as CPU, RAM, or storage) to a single node or server to handle increased load.

This approach allows for an increase in the capacity of an existing node, which can handle more requests.

So, that was the basic difference, I will show you more difference in a while but if you are preparing for Microservice interview, this is one concept I like you to learn and learn better.

You can also use system design cheat sheets like this one from Exponent for quick revision of key System design concepts for interviews.

Difference between Horizontal and Vertical Scaling in System Design

Here are some additional points that differentiate horizontal scalability from vertical scalability:

1. Scale up vs Scale out

Vertical scaling means adding more resources to single server while horizontal scaling means adding more instances that's why vertical scaling is now as scale up and horizontal scaling is known as scale out.

2. Load Balancer

Horizontal scalability requires the use of load balancers to distribute incoming requests across multiple servers, while vertical scalability does not, which is often a deciding factor. If your architecture doesn't permit load balancing then you only have to scale vertically.

3. Higher Scalability

Horizontal scalability can achieve higher levels of scalability as the number of nodes can be increased almost indefinitely, while vertical scalability has limitations due to the maximum capacity of a single node or server.

4. Architecture Preference

Horizontal scalability is commonly associated with distributed systems, while vertical scalability is usually associated with monolithic systems.

5. Handling Load

Horizontal scalability is more suitable for handling unpredictable or varying loads, while vertical scalability is more suitable for handling predictable loads.

6. Complexity

Horizontal scalability involves adding more nodes or servers to a system in order to handle increased load or traffic. However, horizontal scalability can be more complex to implement than vertical scalability, as it often requires more sophisticated load balancing and coordination mechanisms between nodes.

Additionally, horizontal scalability may not always result in a linear increase in performance, since additional nodes may introduce more overhead or communication delays.

On the other hand, Vertical scalability involves increasing the resources (such as CPU, RAM, or storage) available to a single server or instance in order to handle increased load or traffic.

The main advantage of vertical scalability is that it is often easier and less complex to implement than horizontal scalability, since it involves simply adding more resources to an existing system.

However, vertical scalability may be limited by the physical capacity of the hardware running the system, and may not be able to scale indefinitely.

Additionally, vertical scalability can be more expensive than horizontal scalability, since it often involves upgrading to more powerful or specialized hardware.

7. Example

An example of horizontal scalability is a web application that utilizes a load balancer to distribute incoming requests across multiple web servers. As traffic to the application increases, additional servers can be added to the cluster to handle the additional load.

Similarly, one example of vertical scalability is a database system that uses sharding to partition data across multiple disks or storage devices within a single server.

As the size of the database grows, additional storage devices can be added to the server to accommodate the additional data.

Horizontal or Vertical Scaling? Which one is better for Microservices in Cloud?

In general, horizontal scaling is considered better for microservices in the cloud because it allows you to add more instances of the service to handle increased load.

With horizontal scaling, you can distribute the workload across multiple instances, which helps to ensure that the service remains available even if one instance goes down.

Additionally, horizontal scaling is more cost-effective because it allows you to add resources on an as-needed basis, rather than requiring you to invest in more powerful hardware upfront.

Vertical scaling, on the other hand, can be more expensive and less flexible because it requires upgrading the resources on a single instance to handle increased load.

This approach can result in downtime if the instance needs to be taken offline for maintenance or upgrades, and it may not be sufficient to handle sudden spikes in traffic.

However, vertical scaling can be appropriate in certain situations where the workload is predictable and consistent, and it may be more straightforward to manage a single, more powerful instance than multiple smaller instances.

System Design Interview Preparation Resources

And, If you need free system design courses you can also see this article which is full of free system design courses.

image_credit - DesignGuru.io

That's all about difference between horizontal and vertical scaling in context of System design and Microservices. Overall, both horizontal and vertical scalability have their own advantages and disadvantages, and choosing the right one depends on the specific requirements and constraints of the system being developed.

It is often a good idea to start with horizontal scaling and add more instances as needed, while keeping an eye on performance and costs.

Is ByteByteGo Good Platform for System Design Interview? Review

2026-02-04T06:55:00.000-08:00

Credit - ByteByteGo

Hello guys, if you are preparing for System Design Interview in 2025 then you may have most likely come across names like ByteByteGo, Alex Xu or System Design Interview - An Insider Guide by Alex Xu, and if you are wondering what they are or you know about them but thinking whether ByteByteGo is worth it or not for System Design and Coding interview preparation then you are not alone?

If you ask me, Yes, ByteByteGo is indeed worth considering for your System Design Interview preparation, because it was created by Alex Xu, an expert with FAANG interview experience and someone who has the privilege to be on both sides of the table.

10 Must Know Topics for System Design Interviews

2026-02-03T07:20:00.000-08:00

Disclosure: This post includes affiliate links; I may receive compensation if you purchase products or services from the different links provided in this article.

image_credit - DesignGuru.io

Hello devs, if you have attended technical interviews, then you may know thatthe System Design part is one of the toughest to crack. I think, why so? And the answer I found was that most of the developers are not really familiar with essential System design topics or concepts, and that's what I am going to share in this article.

As I have said before, System design interviews are a crucial part of the hiring process for software engineers and developers, and you must prepare for them; leaving it to chance is not a good idea.

Difference between @Controller vs @RestController in Spring Boot

2026-02-02T06:40:00.000-08:00

Hello friends, if you are preparing for Java and Spring Developer interview then you may have come across "difference between @Controller and @RestController annotation" in Spring Boot and Spring Framework in general. It's one of the popular spring question which I have also mentioned in my list of 25 Spring Framework questions earlier

6 Best Udemy Courses to Learn Agentic AI from Scratch in 2026

2026-01-31T23:03:00.000-08:00

credit — Pault Iustzin of LLM Engineer’sHandbook

Hello guys, Agentic AI is quickly becoming one of the most important shifts in modern software development. Instead of single-prompt AI systems, we’re now building autonomous agents that can plan, reason, use tools, collaborate with other agents, and execute multi-step tasks reliably.

In 2026, knowing how to build AI agents with Python is no longer optional for AI engineers, backend developers, or full-stack engineers working with AI-driven products.

Java67

Database Sharding 101: The One Topic You Must Nail in Every System Design Interview

Review - Is Educative Unlimited Plan Really Worth It in 2026?

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5 Best Courses on Educative.io (Included in Unlimited Subscription)

1. Grokking the Coding Interview

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2. Grokking Modern System Design for Software Engineers & Managers

Grokking the Modern System Design Interview

The ultimate guide to System Design Interviews — developed by FAANG engineers. Master distributed system fundamentals &…

3. Grokking the Machine Learning Interview

Grokking Coding Interview Patterns in Python

Level up your coding skills. No more passive learning. Interactive in-browser environments keep you engaged and test…

4. Data Structures for Coding Interviews in Python

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Explore proven strategies developed by FAANG engineers to ace coding interviews with a structured approach to data…

5. Master AWS Certified Solutions Architect Associate SAA-C03 Exam

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Pros and Cons of Educative Unlimited Subscription

Pros: What Makes Educative.io Worth It?

1. Access to High-Quality Courses

2. Hands-On Coding Without Setup

3. Great for Interview Preparation

4. Cost-Effective Compared to Buying Individual Courses

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Coursera | Degrees, Certificates, & Free Online Courses

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Is Educative Unlimited Worth It in 2026?

Educative Unlimited: Excel with AI-Powered Learning

Ready to level up your career? Lock in unlimited access to Educative’s entire library of 1200+ hands-on Courses…

Where to Subscribe to Educative Unlimited

Educative Unlimited: Excel with AI-Powered Learning

Ready to level up your career? Lock in unlimited access to Educative’s entire library of 1200+ hands-on Courses…

I Tried 30+ Software Architecture Courses Online: Here Are My Top 10 Recommendations for 2026

Top 10 Courses to become Software Architect in 2026

1. Certified Professional for Software Architecture (Top Developer Academy)

2. Software Architecture on Coursera

Coursera Plus | Unlimited Access to 7,000+ Online Courses

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3. How To Become An Outstanding Solution Architect (Udemy)

4. Basics of Software Architecture & Design Patterns in Java

5. Clean Architecture for Beginners: A Practical Guide

6. Grokking the System Design Interview (Educative)

7. Web Application & Software Architecture 101 (Educative)

8. Master the Coding Interview: System Design + Architecture (ZTM)

Learn In-Demand Skills. Get Hired. Advance Your Career. | Zero To Mastery

Stop wasting time on boring, outdated tutorials. Join 1,000,000+ students learning in-demand skills & getting hired at…

9. Software Architecture & Design of Modern Large Scale Systems

10. Grokking the System Design Interview on Design Guru

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How to Prepare for Coding Interviews in 2026: Your Step-by-Step Guide

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