I am happy to announce that Dell Technologies has acquired Moogsoft on September 17, 2023.

This is good news for existing and future Moogsoft and Dell customers.

Earlier this year Moogsoft embarked upon raising capital to accelerate growth. This initiative generated a lot of interest from many companies with many different proposals — and after a thorough review process, it was clear that Dell Technologies was by far the best fit in terms of both companies’ passion for innovation to benefit customers and a founder-led culture and core values based on ethics, inclusion and diversity.

Dell is a leader across many IT sectors and has consistently received worldwide recognition, including Fast Company’s 2023 World Changing Company of the Year, 10th out of 750 in Forbes’ World’s Best Employers 2023 ranking, first place in Newsweek’s 2023 America’s Most Loved Workplaces survey and the Ethisphere Institute’s 2023 World’s Most Ethical Companies Award.

The acquisition will further enhance our ability to accelerate advanced cloud-based AIOps capabilities for the Moogsoft application and to enhance Dell’s AIOps capabilities as part of its longstanding approach of embedding AI functionality in its product portfolio and as a critical component of its “multicloud by design” strategy.

Existing Moogsoft customers can look forward to us meeting with them to discuss their needs, our ongoing support, and the Moogsoft product roadmap.

Phil Tee, VP Strategy and Operations, ISG AIOps
Dell Technologies

The post Dell Technologies acquires Moogsoft appeared first on Moogsoft.

Moogsoft continues to prioritize Correlation and Collaboration – Check out these product enhancements!

New! Correlation Groups

Previously, Moogsoft offered one set of definitions that determined correlation behavior. With Correlation Groups, you can now:

• Define different correlation behaviors
• Group sets of correlation definitions
• Allow specific teams to choose correlation behaviors based on their use cases
• Enable multiple merge behaviors between incidents

This functionality gives your teams better control over incidents that are specific to their domain(s). Review the documentation to learn more.

New! Incident Watchers

During major incidents, you need to keep stakeholders and related teams (or individuals) up to date in real-time.

With Incident Watchers you can add Moogsoft Cloud users and groups to a list of watchers who are associated with a particular incident. Watchers receive an email whenever an announcement is added for the incident.

See how to add or remove watchers, and send announcements.

New! Shareable Views

Most operators have incident to-do lists specific to their area of responsibility. Instead of creating a list for yourself to identify everything you need, you can now use Shareable Views to easily create the scope, share it with your team and toggle it. 

Your views are customizable:

• Specify which columns are displayed, in which order
• Save the view and share it. 

Now everyone on your team will be looking at the exact same list, rendered in the exact same way so there’s no need to reapply filters or rearrange columns.

Plus, if you manage multiple teams, you can set up a view for each team. You can also switch to a dashboard view of the list to easily see overall team performance while still being able to drill down to a specific situation.

Check out this quick explainer video (1:35).

New! Dashboards

Incident lists are useful for operations staff, but managers may need a holistic view to see how their teams and services are doing.

New dashboards functionality lets you quickly:

• Tile by services, type, classes or other variables
• Easily filter or drill down
• Directly access the Situation Room
• Save dashboards for one-click access to team stats
• Share dashboards with specific groups or everyone
• Set a dashboard as your default view

Here’s a short demo video (1:56)

Interested in getting a deeper look at any of these features? request a live demo or tune in for the Moogsoft in Action Demo webinar series.

The post Correlation & Collaboration Product Enhancements appeared first on Moogsoft.

And now there is new Gartner AIOps terminology to navigate. This blog will give you a Cliff Notes version while highlighting some of the big takeaways from our expert AIOps panel, so you can gain insights on the latest Gartner research and more clarity around the value of AIOps and regular use cases.

Let’s explore some of the topics from Gartner’s latest AIOps findings, and how some experts are responding:

1. Don’t get confused by the new AIOps terminology.

After a constant drumbeat dialogue about domain-agnostic versus domain-centric, (point solution monitoring) AIOps last year, Gartner is now breaking AIOps solutions into three categories:

1. Data and Analytics
2. AIOps Features
3. AIOps Platforms

“Nothing changed in the markets in terms of what these products do. This is just a different way of helping people understand where the vendor offerings fit into this space,” explains Phil Tee, Moogsoft founder. He describes the fresh categories as an artificial ontology and translates the new slang into the following.

Data and Analytics: This is a large-log analytics-like platform you leverage combined with Pythonesque libraries to build something that looks like AI on top of that framework. These vendor(s) are minimal in the space and weren’t included in Gartner’s AIOps market findings previously because they aren’t true AI-powered solutions.

AIOps Features: These are the point-solution-monitoring platforms that Gartner previously labeled Domain Centric AIOps—accounting for a large chunk of available AIOps technologies. 

AIOps features usually focus on a single area or “domain,” built for limited use cases. These rely on their own agents or collectors to retrieve “first-party” data and do not ingest data from other applications. Even as these AIOps Features continually evolve, few ingest data from other sources. The Domain-Centric solutions that can are usually more expensive. 

The result? Most organizations using Domain-Centric AIOps platforms, i.e., AIOps features ingest minimal third-party data—making it harder to get a clear view across your IT environment. 

AIOps Platforms: AIOps platforms like Moogsoft were previously known as Domain-Agnostic AIOps solutions. They integrate data from multiple sources, across IT technologies and vendors. AIOps platforms help you connect the dots—pulling data from your monitoring stack, (logs, event data, metrics, and traces), correlating them, and unleashing a deeper view across all your systems.

Confusion around the AIOps solutions market isn’t new, and the space hasn’t changed in a meaningful way. There are still vendors adding AIOps capabilities like machine learning and algorithms to replace the rules and heuristics driving their solutions. These vendors can’t stand on their own as an AIOps platform but are all too often positioned as one—limiting performance outcomes and increasing customer costs.

2. Do prioritize your unique AIOps use cases.

In its latest AIOps reporting, Gartner recommends prioritizing your AIOps use cases based on business impact like mean time to detection (MTTD), mean time to resolution (MTTR), visibility, faster decision-making, and IT staff reallocation.

Our panel experts hone in on how business pain points and goals can shape these priorities.

“The user benefit is critical to any implementation, there’s no difference with AIOps,” says Jay Rudrachar, TIAA Enterprise Monitoring & Observability Engineering Senior Director. “[At TIAA], we look at all AIOps implementations in general.”

“Ultimately, what is our biggest benefit? To reduce the customer-facing outages and downtime as much as possible and be proactive.”

“Customer experience and retention often drive your AIOps use cases.” Rudrachar explains to prioritize accurately, it’s useful to consolidate a view of critical factors such as MTTD, MTTR, blast radius, and response team activity in one place. It’s also important to look at the pattern of repeated incidents and automate self-healing based on existing knowledge.”

3. Don’t get distracted by the AI hype.

“[Gartner] really breaks down the different types of barriers—internal and external,” observes Bill Driscoll, Windward Consulting Customer Success Vice President. “Internally, a lot of companies don’t have the processes in place. They’re lacking the data. 

“They don’t have a [Configuration Management Database], (CMDB), that’s well populated or top-down leadership support. We see some of those internal barriers and agree with what Gartner said about them. [Gartner] is also right on the external barriers—the hype; the confusion; the messaging, and the noise as far as what’s AI and machine learning (ML). Chat GPT and everything we’re seeing now is adding to that hype.”

Driscoll warns against focusing too much on hypotheticals that start in a lab. Examine the current state of your IT organization and the problems your customers are flagging instead.

Every IT decision-maker should answer:

• What are the performance issues? 
• What are the outages? 
• What are the availability issues? 
• What are the issues coming through in your tickets and your current monitoring systems? 

Next you explore how you can implement AI to solve these problems. It helps to get familiar with AIOps models and approaches.  Selecting the right AIOps solution requires how you want to apply your use cases to assess how the solution can improve user experience, impact your business in a positive way, and drill down to root causes for more agile responses.

Breaking down the barriers Gartner covers is mission-critical. That starts with making your AIOps implementation about solving the pain points that currently affect your business. Evaluating the current state of your IT organization and identifying where gaps and obstacles occur can help you develop more maturity, enlist leadership buy-in, and identify the right AIOps solution for your unique organizational needs. 

4. Don’t get lost in “Explainable AI”.

“Should AI be explainable? Do people really need to know what’s going on? You never sit there with Siri, Alexa, or Google Home with a screwdriver to figure out what’s going on in some of your favorite devices. But some AIOps vendors make an effort to differentiate open-box machine learning versus closed-box machine learning,” Tee says. 

“If your box is transparent that’s because there’s nothing in it. AI is complicated and difficult from a technical perspective. It’s up to the software vendor to hide as much of that complexity as possible from the end user.”

Instead, Tee proclaims that’s for the data scientists to do. Gartner’s “Explainable AI” to build traceability, transparency, and trust is a dated approach—most people trust and understand the value of AI already. 

What’s more important? The use of understandable AI and ML. Be able to control the process of data consumption and correlation without getting hung up on reducing it to a set of math equations. Take outcomes a step further by working backwards in the resolution process to understand how an incident originated. 

Securing leadership buy-in comes down to the business results. You probably wouldn’t want to explain complex machine learning algorithms working across aggregated data to a boardroom. Instead, you focus on what’s created obstacles for your IT organization and how AIOps is solving them. Let the data scientists do their jobs, so you can focus on what really matters—your teams; your customers; your business.

5. Don’t limit your AIOps adoption model.

Gartner has built a six-step AIOps adoption model that covers a lot of bases. But experts on the panel explain that you risk being slower to react instead of proactive with overly sequenced and prescriptive AIOps approaches. The six-step model can become a trap like a “Waterfall approach” to IT. 

Instead, drive your AIOps adoption by focusing on real world cases impacting your business right now. Step six, evolving your operator roles and processes, is an area of focus when testing and reviewing the tech—not two years later. Stay in the present and let the state of your business and IT organization guide your approach. Don’t implement AIOps in a vacuum.

Instead, cut out the noise by zooming in on ways you can:

• Cluster more data sets together
• Identify root causes and domain-specific processes
• Look at the data

Iterate AIOps in a way that benefits your enterprise. That starts with selecting the right AIOps vendor, and that might not be just one platform with all the room for deep domain knowledge. 

Start with your enterprise challenges and then go through a pilot or RFP to address the problems you already have today. If it’s taking too long and it seems too hard then it probably isn’t worth moving forward. 

Get the full rundown on Gartner’s latest AIOps analysis.

Hear from our panel on issues of collaboration, self-healing, and more. Watch the full webinar on demand. 

The main takeaway from Gartner’s reporting is clear. There is no future of ITOps without AIOps. Learning how to share and illustrate the use cases, value, and benefits is critical to maximizing support and adoption at every level of your organization. Don’t get left behind.

Gain more clarity and start your AIOps journey.

Moogsoft customers discover millions in monthly revenue savings from decreased downtime while taking 10% of their time back with greater focus and reduced noise by up to 99%.

Learn more about how AIOps saves your business valuable time and resources. Book your demo now.

Source: Gartner GTP Client Webinar: Accelerating Your AIOps Journey

The post 5 Takeaways from Gartner’s Latest AIOps Analysis appeared first on Moogsoft.

IT teams have been acclimated to disparate event management and monitoring tools. Now, with massive and rapidly increasing data flow, this disconnect is slowing and paralyzing IT teams. Modernization, with an aggregation layer like AIOps alleviates the complexity digital transformation adds to ITOps—not all aggregation layers offer the same value. Domain-agnostic AIOps platforms go deeper to accelerate remediation (MTTR) and fuel meaningful collaboration and productivity in a way other aggregation layers can’t.

Domain-agnostic AIOps Defined

Domain-agnostic AIOps leverages AIOps to ingest more data and navigate challenges across any domain with data from across your IT environment. From networking tuning, to application deployment, and performance management, a domain-agnostic AIOps platform helps your teams manage and align ITOps across existing platforms. Domain-agnostic AIOps integrates your tech stack to reduce noise and increase productivity while providing complete visibility.

As employee and customer expectations increase in our digital, 24x7x365 environment, finding ways to reduce alert noise and prioritize incidents delivers transformational benefits.

Most IT teams have adopted a variety of monitoring tools to identify incidents. Unfortunately, disparate tools create the perfect storm. Challenges with limited visibility creating siloed work streams and delaying MTTR ultimately render your organization less competitive. Efficiency matters as you grow and scale your business. The AIOps outcomes of correlation, collaboration, and automation can empower your organization’s performance.

This blog reviews five domain-agnostic AIOps benefits while exploring how an aggregation layer can streamline your IT operations to unleash a decisive, competitive edge.

With the right Domain-Agnostic AIOPs solution, you can:

1. Ignite collaboration and accelerate remediation (MTTR)

   With deeper visibility leveraging a domain-agnostic AIOps solution, you can capture all of your alerts and automate incident workflows in a single view—empowering meaningful collaboration and showing how incidents are connected to streamline and accelerate time to resolution.

   Does your team prefer collaborating in Microsoft Teams, Jira, or another ITSM platform an AIOPs platform? With outbound integrations breaks down silos and lets your team work on their terms.

2. Eliminate obstacles from your digital transformation

   Remote work and accelerated digital transformation increased the volume of data that IT teams process to an unmanageable amount. Growing data volumes increased the monitoring tech stack for most IT teams to add functionalities like application monitoring, cloud monitoring, and a whole suite of security solutions—all with different, often redundant, alerts. But, with AIOps, incidents are consolidated, correlated, and remeditated so your team spends less time monitoring and more time modernizing.

3. Bolster customer satisfaction and your user experience

   With increased visibility and prioritized and streamlined incidents, teams can quickly identify the highest-priority requests. That’s because with an AIOps solution, you automatically connect related incidents while eliminating (de-duplicating) redundant ones to improve (MTTR) response times dramatically.

4. Automate your repetitive tasks and boost productivity

   With an aggregation layer, your IT teams can deploy automated workflows, enabling auto-resolution, reducing workloads, and streamlining basic requests. Meanwhile, you can keep the tried-and-true legacy applications your monitoring and observability team is comfortable with while gaining momentum.

   You can simplify IT operations with a domain-agnostic AIOps solution. That starts by complementing your legacy monitoring platform with a modernized tool that aligns with legacy events while reducing IT alert noise, surface critical, customer-impacting incidents, and increasing visibility.

   The result? Timelier resolutions and higher user satisfaction.

5. Unleash immediate time to value

   Maximize your ROI with a new aggregation layer in days or weeks, harnessing a Natural Language Processing (NLP)-based correlation and deduplication capabilities. A cutting-edge, business-critical modern platform simplifies correlating raw events from legacy platforms with events from more modernized toolsets in no time.

The right domain-agnostic AIOps solution fuels productivity and transformation.

Identifying the right domain-agnostic AIOps solution to provide an aggregation layer for your IT teams can be a complete game changer for your business—unleashing continuous availability and increasing customer satisfaction. Domain-agnostic AIOps solutions correlate and consolidate alerts, integrating with legacy platforms to minimize noise and and reduce time to respond (MTTR).

The right solution can also streamline ITOps for a happier, more productive IT team—giving your team time to focus on your business and your next transformation initiative.

Moogsoft reduces noise and eliminates unnecessary work.

Moogsoft is a unique domain-agnostic AIOps solution that helps you reduce noise, gain correlation, and manage your IT environment on one pane of glass. From monitoring tools like SolarWinds, AppDynamics, New Relic, Datadog and/or PagerDuty, Moogsoft correlates and consolidates alerts and events from associated incidents.

“We’ve experienced a 99% reduction in SolarWinds alarms with very little effort compared to systems we’ve implemented in the past, when we had to develop scripts manually, requiring a developer skill set to build and maintain. The simplicity of Moogsoft’s correlation engine [with SolarWinds] makes creating these filters easy.”

-Andrew Jaquez, Internet Operations Manager, Cable One

Increase customer satisfaction with less downtime and empower greater IT productivity while improving team morale with Moogsoft. Learn more about how we can help. Schedule your demo now.

The post 5 Immediate Business Benefits of Leveraging Domain-Agnostic AIOps appeared first on Moogsoft.

Auditing a tech stack for superfluous or duplicate features is helpful, as tool sprawl is a risk to cost efficiency for just about every organization. To guide a strategic consolidation process, IT leaders should consider which tools provide meaningful and actionable insights (without expending the critical time of technicians). Oftentimes, solutions overlap — or, in other cases, the insights they provide do not track back to ROI in crucial areas like maintaining uptime and system performance.

Here’s how AIOps fulfills those essential functions — and more — during economic uncertainty.

Incident management goes beyond the tech stack

Many enterprise leaders view IT system event monitoring as a necessary business expense rather than a revenue opportunity. That is because traditional understandings of IT Ops involve back-office operations to keep mission-critical systems afloat, which includes people, processes and technology. In other words, many leaders regard IT service management (ITSM) and event management as deeply embedded capital infrastructure. But there is more to it.

Our modern business landscape has changed dramatically since IT first rose in prominence (think the ‘80s and ‘90s). For starters, digital transformation has accelerated rapidly, leaving many vendor-client relationships entirely digital. As a result, IT infrastructure has become far more complex — and critical. Internal and consumer-facing systems handle an array of new data streams, not to mention a higher overall volume of metrics, logs and events. Now, IT teams are tasked with maintaining fundamental internal systems and ensuring uptime for revenue-generating interfaces like e-commerce platforms.

That is where AIOps tools come into play. AIOps solutions untangle the mess of incidents by escalating issues to the appropriate parties and eradicating non-relevant alerts. Internally, AIOps solutions declutter event management and allow IT teams strategic insights in guiding them to reduce technical debt. And for consumer-facing systems, AIOps tools ensure more uptime, giving consumers 24/7 access to an organization’s products and services. Just as important, AIOps-provided outage and availability insights become available before customer complaints arise.

Although consistently important, system uptime — and the revenue it safeguards — becomes even more critical during an economic softening. Consider that more than 60% of the world’s GDP is digitized, and organizations that neglect to build proper infrastructure will eventually lose out.

The economics behind AIOps and reduced MTTX

Let us unpack the inherent ROI of AIOps: reduced mean time to detect (MTTD) and mean time to recover (MTTR). Together, these measurements — MTTX — can indicate the strength of a system’s data infrastructure.

Now, an example to illustrate the importance of low MTTX. Say a large retail organization experiences an outage on Monday at 9:30 a.m. During that outage, the organization’s physical and e-commerce sales platforms go dark worldwide, making it impossible for customers to check out. Because this organization employs good data practices and has previously deployed AIOps, its systems swiftly identify and escalate the issue to the appropriate technician. As a result of this expedited workflow, the organization’s systems return online at 9:31 a.m. An organization experiencing tool sprawl and fragmented data infrastructure, on the other hand, will likely have longer MTTX — their systems will remain offline until 11:30 a.m. as human technicians search for error context and origin. The 119 minutes of downtime could cost the business more than $2.6 million at $22,000 per minute, according to Forbes. 

Clearly, lower MTTX translates to fewer costs from extended downtime. However, treating MTTD and MTTR as representative of the same underlying issues is a mistake because their identification processes differ significantly.

MTTD involves a three-step process in which technicians must identify whether an incident is underway, the nature of the incident and the causes of the incident. Given tool sprawl, before Moogsoft, we have heard that these investigations can include more than 300 people. MTTR kicks in when technicians start communicating the incident’s nature and cause to the appropriate parties and executing a response. All five steps of MTTX are crucial. Therefore, reducing one aspect of MTTD over another will not help in the long run. IT and DevOps teams must consider the entire incident lifecycle — this is where AIOps tools excel.

In isolation, MTTX reduction requires a dedicated team. AIOps solutions simplify the process by identifying and escalating issues across all five classic telemetry points. And once these solutions are deployed, economic returns begin. Expedited data ingestion and correlation leave DevOps teams with context-rich event tickets — and fewer tickets overall, leading to less time wasted on repetitive incident resolution. As a result, technicians can finally cut down on monitoring and have time to focus on revenue-generating responsibilities. This is especially critical given recessionary pressures like the extended tech talent crunch, which has left many IT and DevOps teams understaffed and overworked.

Now is the time to strengthen observability measures

Economic fragility may convince some leaders to pause tool adoption. However, not all tools are created equally — not even all AIOps solutions are created equally. Leading AIOps tools like Moogsoft excel because they rely on AI and machine learning (ML) instead of logic-based algorithms (or the old rules-based architecture). Moogsoft’s AIOps solution adapts to the modern IT infrastructure landscape and allows DevOps teams to create efficiency with IT operations to focus on high-impact initiatives and revenue-based opportunities.

Leaders should keep this in mind as they review their existing tech stakes and determine which deliver meaningful value. A good rule of thumb is to prioritize solutions that not only provide data but also interpret and act on data. These functionalities will prove especially valuable in the challenging months ahead.

The post Why AIOps is Worth the Investment During an Economic Downturn appeared first on Moogsoft.

The last decade has seen exponential investment into DevOps and AIOps — especially when you remember that AIOps as a concept did not exist 15 years ago. Considering recent headway, it is valuable to review how far AIOps has come and use that progress roadmap to determine where the industry will trend in 2023 (and beyond!). Now, reach into the back of your fridge, pour yourself some leftover eggnog and let us get into it.

AIOps 1.0 is nearing completion

The initial wave of AIOps offerings came to market more than a decade ago. For context, when I founded Moogsoft in 2011, DevOps was a young movement, most organizations hosted their data on-prem and continuous integration/continuous development (CI/CD) philosophies were revolutionary. Clearly, our digital landscape has changed dramatically since then. Now, scattered tech stacks and multi-cloud data rule the day.

AIOps solutions that operate on decade-old inferences will ultimately stumble when faced with this modern IT infrastructure. This is especially true for event-only workflows over-relying on monitoring and domain-specific solutions prioritizing one dimension of AIOps over another. In effect, these tools focus on the what? or the how? as opposed to the complete picture: who, what, when, where and why. As workflows become more interconnected and complicated, comprehensive and immediate solutions will be critical. Accordingly, tools that support the entire change management process will define AIOps 2.0.

Data is consolidating

AIOps 2.0 will be defined by data consolidation. A proper AIOps workflow begins by ingesting and normalizing disparate source data, including log events, traces and metrics. By normalizing these data, AIOps can reduce incident volume and event noise, all while increasing situational awareness thanks to ML. DevOps and site reliability engineer (SRE) teams can use this aggregate analysis to identify problems before they arise, reducing mean time to recover (MTTR) and increasing overall system uptime.

Again — this is the proper AIOps workflow on which we built Moogsoft a decade ago. But many solutions on the market claiming to be AIOps stick to a problematic rules-based approach that treats IT infrastructure and data as static. Of course, IT systems are dynamic, as is data, and new problems arise by the hour. When so-called AIOps solutions ignore this fact, SRE teams and DevOps engineers lose access to the entire picture and inevitably miss concerning patterns in their data.

But the dog days of undynamic data are nearing an end. Authentic AIOps tools that consider the entire incident lifecycle and simplify the event management process will soon win the day as data sprawl creeps ever higher.

AIOps will integrate with (and improve) IT service management (ITSM)

Current ITSM tools are largely unchanged from the troubleshooting systems of yesteryear (or, in this case, those of about 30 years ago). Employees submit tickets using web forms attached to finite-state machine (FSM) logic. An FSM-based system escalates tickets to an administrator but cannot process the request’s colloquial context. For example, let us say an ITSM process starts with a verbal conversation around the water cooler. In the ticket arising from said conversation, employees may paraphrase their problem, preventing the system from reliably automating the review process.

AIOps presents a few opportunities for improvement to the ITSM workflow. First, AIOps tools can automate ticket creation after anomaly detection, creating a process with far greater context and fewer false positives. And with exposure to human-generated tickets, the system can understand the semantic context of future tickets via ML. For internal IT teams dealing with a monstrous ticket backlog, the value here is likely apparent: teams spend less time troubleshooting and more time addressing root issues.

Overall, I am happy to report the future of AIOps is looking bright. True AI will define the next era, and ML-backed tools that consolidate data to create an accurate timeline of the incident lifecycle will win the day. Moreover, IT leaders will soon apply those solutions across other workflows, including tedious ITSM. That means faster error identification and less system downtime. Lower mean time to detect and MTTR? I would call that an extremely admirable New Year’s resolution.

The post The State of AIOps: A New Years’ Message from Chief Moo Phil Tee appeared first on Moogsoft.

Moogsoft pioneered AIOps, essentially inventing the market 10 years ago. It is worthwhile revisiting why we did that to understand where we are going. My background is as the founder and inventor of Micromuse Netcool, and the RiverSoft’s OpenRiver technology. Those approaches were revolutionary in their day, but based upon the idea that infrastructure was fixed, applications may be less so. That radically changed with the advent of cloud computing and virtualization and we realized that AI was necessary to perform the advanced data analysis needed to quickly identify, diagnose and remediate the thousands of minor glitches that occur in a large business like Manulife. The rub being if they are left unresolved minor glitches can become major outages.

Looking forward, the arms race continues as we see increasing adoption of serverless, lambdas, SDN, DevOps, CI/CD and many other technologies. In fact the “doubling time” of change seems to be shortening. What this practically means is that we have to broaden the scope of our product from events to metrics, traces, logs, business data, environmental and social, and double down on the algorithmic sophistication we use to perform our critical task of moving our customers from 5 9’s to no nines. We today have a platform that can handle metrics, and we have active research in all areas of complex event analysis.

Tomorrow I envisage a single platform as the repository for all operational data, handling all availability management tasks from SecOps, DevOps, ITOps, SRE, Alerting, Problem Management and Service Desk. This will allow us to drive automation and liberate the time and attention of operations to run availability and risk as a business process not fire fighting!

Q: How does this take our ecosystem to the next level?

There are essentially two critical outcomes:

1. Availability: For example, one of our customers Manulife already does an excellent job of managing their error budget (total availability), targeting 5 9’s as the availability rate. Working together we can go after no-nines, ie 100% availability with business services being continuously available. We can see a time where major outages are exceedingly rare, if occurring at all and instead we manage a business operational risk metric. This essentially transforms platform services from a cost center to a P&L center as the consequence of opaque business operational risk is the need to hold higher reserves, reducing the return on equity. Not only can we target a better customer experience but better financial performance!
2. Operational Efficiency: Automation is the primary tool to reduce “toil” which is essentially the consumption of time in repetitive and mundane tasks by ops folks. These people are already overworked and overstressed (think air traffic control), and this really is about making sure they have more time for the fun side of the job, and a net reduction in the capital and opex spent by the firm in unproductive (but necessary) work.

So in short, better service levels, lower costs, more return on investment. That has to be good … right?

The post A Fireside Chat with Phil Tee, CEO of Moogsoft appeared first on Moogsoft.

Moogsoft’s Fall product updates enable you to:

• Unlock real-time visibility into your entire system’s health with Moogsoft Cloud Dashboard, summarizing all incidents across your monitoring tools in one place, with color-coded criticality enabling quick drill down in seconds
• Increase collaboration during incident response with our newly released Comments and Comments API, collecting team insights during diagnosis and resolution across communication tools into one place
• Scale without manual rules and catch all the unknown unknowns with Correlation Definition Ordering, allowing you to make sure no alert gets left behind

… and so much more! Read on for deeper details.

Moogsoft Cloud Dashboard

Now, you can stop bouncing between Grafana dashboards, Slack channels, and disparate dashboards for real-time monitoring. The Moogsoft Cloud Dashboard gives you and your team a single view into your system health by bringing all incidents across your monitoring and observability stack into a single pane of glass. Quickly understand the criticality of alerts with easy-to-understand color coding, view your events-to-incident count across your systems in one glance, and quickly drill into any incidents with one click. Read more about the Moogsoft Cloud Dashboard.

Comments

Incident resolution happens across many teams, tools, and places. Now within Moogsoft, you ensure and track your path to resolution in one place by integrating with your tool ecosystem, including tools such as ServiceNow, Microsoft Teams using the Comments API, and consolidating all comments related to an incident. Read more about Comments.

Correlation Definition Ordering

When’s the last time you had an incident come through and you thought to yourself, “My alerting rules should have caught this!”. At Moogsoft, we built our foundation around just that.

Our correlation engine uses ML algorithms to correlate alerts into actionable incidents using similarity, natural language processing, and shingling so every alert is evaluated – regardless of whether there’s a new service, new data type, or new kind of alert.

The newly launched Correlation Definition Ordering allows you to have even more hands-on control of how alerts are processed and correlated, including a “Catch All” feature ensuring that every alert is processed while the real incidents get through to your team. Read more about Correlation Definition Ordering.

Custom User Roles

During incident response, you want your team to be able to focus on their job to be done without distraction but at the same time allow everyone to have visibility into your system’s health. That’s where user roles come in!

Within Moogsoft you can choose from one of three default user roles – Owner, Administrator or Operator. Now with Custom User Roles, you can create more specific roles to allow or restrict access to varying parts of the product, depending on your unique business needs. A role could be created to only provide access to Incidents, and block other areas of the product from view. A role could be created for Integrations only, so users could adjust integrations but not other parts of the product.

Situation Room® – the beginning!

War rooms, bridge calls, and 10 Slack channels are times of the past. We’re excited to launch the foundation of Situation Room®, Moogsoft’s top feature in our On-Prem product into the Cloud, giving your team one dedicated place to track, collaborate, and resolve incidents together.

Today, you can access the Situation Room® from an incident to expand the view with Comments. But, keep an eye on this space – we have a lot more coming soon, like our customer-favorite timeline view, resolving steps, and incident similarity scoring to help you and your team resolve faster. Read more about the Situation Room®.

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Solidified in Google’s SRE handbook, a postmortem is defined as “a written record of an incident, its impact, the actions taken to mitigate or resolve it, the root cause(s), and the follow-up actions to prevent the incident from recurring.”

Translating that to the real world, postmortems are a critical part of the incident review process. They are an active record of where mistakes were made as a company and where we can do better. By detailing what happened to cause the incident, we can better understand how it can be resolved. Like the name implies, postmortems help us fully understand the reason behind a “deadly” issue.

Postmortems are a way for us to keep an eye on how we can improve either by making sure it never happens again, or if it does, we have better action plans to minimize our mean time to resolution.

How postmortems can keep you accountable – without throwing blame

While we can mitigate risk when we’re working on anything in the software realm, we can’t remove it entirely. Postmortems are a great way to publicly identify issues, without throwing blame at a single person or telling an engineer that their job is on the line for mistakes or outages. It pushes the onus from an individual to the company level – it’s not the individual that pushed the code. Sometimes there are landmines and you just happen to be the person walking on that path. An outage is everyone’s responsibility.

And if we are telling our engineers we blame them for every incident, we’re not going to see progress or development in a meaningful way, simply because they won’t want to take necessary risks. As a company, we need to take on the idea that an outage is everyone’s responsibility.

By utilizing a clear feedback or postmortem approach, you’re allowing a space for accountability and growth. You can structure feedback in a much more productive way and help your development team improve overall by prioritizing common issues.

How do you choose action items from postmortems?

Write everything down and think of it like a brainstorming session. The only way you can fix issues is to first identify them, and break them down into smaller parts and figure out how to manage each piece.

As a team, determine what parts are a priority and set actionable, achievable timelines to make those things happen. As far as how to pick which things are a priority – that’s where working with your team or company helps. One person might not know that a problem is linked to another area, so value and encourage that transparency and communication. A postmortem is no good if you don’t actually work towards solving the issue behind the incident.

Once you figure out what you want to do, put those action items into whatever ticketing system you and your team typically use.

Can this help our team reduce tech debt or better hit SLAs?

Tech debt can manifest itself in many ways, some of it is simply impacted by velocity. Managing code is often harder than it needs to be when there have been a lot of people working on something. But postmortems are a good way to reduce the time it takes to resolve issues – since you break down the issue and are prepared if it happens again – but there are all sorts of tech debt.

Deployments take a long time, builds take a long time, and those could all be considered tech debt that aren’t really improved by this process. So, though others might argue, postmortems may not be impactful to SLAs in that way. But! Teams are able to chase down potential bugs or fixes through this process, and that’s incredibly valuable, even if it is an indirect result.

So, when you have an incident, should you do a postmortem? Yes. Absolutely!

The post Episode 5: Mooving to… Practical Postmortems appeared first on Moogsoft.

With many new features recently rolled out we need to group them in logical order to cover each of the following categories:

• Correlation
• Workflow Automation
• Collector
• Collaboration
• Administration

Correlation

Incident Origin – At a glance, Moogsoft now displays which correlation was used to create the incident. Easily click on the link within the incident and navigate to the correlation definition used to correlate all the alerts into one actionable and insightful incident.

Correlation Containers – Moogsoft allows Correlation definitions to be processed in a pre-defined order. This unique capability provides additional logic and granularity for single matching as well as alerts belonging to one or more incidents. Users have the ability to group Correlation definitions into Correlation containers for prioritization and ordering.

Correlation Preview – Allowing you to Preview the results of a Correlation before enabling is now available. As you define the Correlation definition, you can now preview the alerts to be
included for processing to ensure your desired outcomes are met. Don’t like what you see? No harm, just change your filters and hit the Scope Preview button.

Workflow Automation

Workflow Preview – The Workflow Engine provides a no code/low code interface, by using an intuitive drag and drop technique to build and deploy both simple and complex workflows. Understanding what triggers each workflow is extremely important for deploying new workflows right, the first time.

Collector

Advanced Configuration – The Moogsoft Collector is a branch of the Vector open source code owned by Datadog. Moogsoft develops Plugins for various data sources, such as HTTP, MongoDB, SystemOS, Docker and many others. This new feature provides the best of both worlds, allowing users to configure Moogsoft Plugins as well as Vector sources.

Windows Supported – The Moogsoft Collector now supports the Windows Operating System. The installation is very easy and requires users to run a simple MSI executable and follow the guided instructions.

Collaboration

MS Teams – Bi-directional integration between Moogsoft and Microsoft Teams is now available. Simply configure the Outbound webhook in Moogsoft and install the package for MS Teams, and watch your teams collaborate around solving issues faster than ever before.

Zoom – Automatically start a Zoom meeting based on certain criteria of an incident. Instantly start or schedule for a future time and day.

Confluence – Automatically create a document in Confluence for Post Mortems and Retrospectives.

xMatters – Bi-directional integration for oncall alert notification and escalation with xMatters. Users can choose to update the incidents either in Moogsoft or xMatters mobile device or UI.

Webex Teams – Easily configure Moogsoft to post in different Webex Team Rooms. Each Webex Team Space can have an Incoming Webhook that can be configured from the Webex App Hub.

Administration

Custom Roles – The standard roles of Owner, Administrator and Operator have now been extended to include any number of custom roles. Simply create a new role and define the required permissions. These can be used with your SSO deployment.

Moogsoft in the News

Check out the recap:

Continuous Availability vs. Continuous Change – Read how to limit customer impact during cloud adoption – whether cloud migration for the first time, hybrid cloud adoption, or extending cloud-native with newer microservice architecture.

More Tools + More People = Increased Complexity – Consider what happens if digital apps or services go down. Companies lose revenue, decrease productivity, compromise customer loyalty and the list of repercussions goes on, depending on the business. Read how to ensure continuous availability.

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May Monthly Moo: Product Edition: To see these updates in action, sign up for the webinar here!

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