This project simulates a simplified Twitter-like application using a microservice architecture. Each microservice handles specific features of the application, such as user management, tweet creation, and newsfeed updates. The services communicate asynchronously using Kafka for event-driven messaging, and MongoDB is used for persistent data storage. Elasticsearch is used for searching tweets efficiently.

• Manages user profiles and follower relationships.
• Allows users to follow/unfollow other users.
• Provides endpoints to fetch user details and their following list.
• Uses PostgreSQL for storing user information and follower data.

• Allows users to post new tweets.
• Stores tweet data in MongoDB, which includes details like tweetId, content, authorId, and createdAt.
• Publishes the tweet-created event to Kafka when a new tweet is created.
• Performs user validation through an API call to the User Service.

• Listens to the tweet-created event from Kafka.
• Updates the newsfeed for users who follow the author of the new tweet.
• Stores the newsfeed data in MongoDB, associating each newsfeed entry with userId, tweetId, and createdAt.
• Retrieves newsfeed data for a given user, showing tweets from users they follow.

• Indexes all new tweets in Elasticsearch for efficient searching.
• Subscribes to the tweet-created topic from Kafka to index tweets as they are created.
• Provides an API to search tweets based on content, author, or timestamp.
• Uses Elasticsearch for full-text search, allowing users to search tweets quickly and effectively.

• When a tweet is created in the Tweet Service, the tweet details (such as tweetId, authorId, content, and createdAt) are published as a message to the tweet-created topic in Kafka.
• The Newsfeed Service consumes these tweet-created events from Kafka, processes the message, and updates the newsfeed of the users who follow the tweet's author.
• The Search Service also consumes tweet-created events to index the tweets into Elasticsearch for efficient searching.
• If Kafka message publishing or consumption fails, retries and circuit breakers are in place to handle temporary issues. Additionally, failed messages can be redirected to a Dead Letter Queue (DLQ) for future inspection or reprocessing.

MongoDB is used as the primary database for storing tweet data and newsfeed entries. Here's how MongoDB is utilized:

• Tweet Service:

  • Stores tweet information, including tweetId, content, authorId, and createdAt fields, in MongoDB.
  • Each new tweet is saved in the MongoDB collection before publishing the tweet-created event to Kafka.

• Newsfeed Service:

  • Stores newsfeed entries in MongoDB, which includes userId (the user receiving the newsfeed), tweetId, authorId, content, and createdAt.
  • When a new tweet is created, the service listens to the Kafka event and updates the MongoDB newsfeed collection with the new data.

Elasticsearch is used for efficient, real-time searching of tweets. Here's how Elasticsearch is utilized:

• Search Service:
  • Consumes tweet-created events from Kafka and indexes tweets into Elasticsearch.
  • The indexed data includes fields such as tweetId, content, authorId, and createdAt, allowing for full-text search and filtering based on specific attributes.
  • Provides a search API to allow users to search tweets by content, author, or time range.