Reliability Intelligence: your reliability expert

For the last decade, Gremlin has helped Fortune 500 organizations with critical uptime requirements proactively uncover reliability risks and prevent costly outages. We started with Chaos Engineering, then built Reliability Management to help teams standardize and scale their testing efforts.

Today, we take another leap forward with the release of Reliability Intelligence.

Reliability Intelligence draws on Gremlin expertise with each test to show you what happened and recommend remediation.

Now every engineer across your organization has access to the expert knowledge needed to run reliability tests, track down root causes, and fix issues quickly. Instead of reliability being one team’s problem, organizations can easily scale reliability efforts across their teams, removing bottlenecks and improving reliability without sacrificing deployment speed.

Reliability without disrupting release velocity

The release couldn’t come at a more crucial time. Because of AI, deployment speeds and infrastructure sizes are steadily increasing, which adds more failure modes, greater complexity, and an increased possibility for errors. At the same time, companies are pushing for more aggressive timelines and ambitious goals.

This leaves teams stuck between a rock and hard place. On one hand, they need to use testing to meet reliability and performance thresholds, while on the other, they need to ship faster to hit their roadmap schedule. Unfortunately, shipping often takes priority, which means teams ignore reliability until it causes an outage.

Reliability Intelligence means you don’t have to choose.

In high-velocity environments reliability can't be an afterthought. Reliability Intelligence equips SRE and performance teams with deep, real-time insights from telemetry and trace data—enabling early detection of reliability regressions, faster root cause isolation, and proactive remediation without disrupting release velocity.”

Reliability Intelligence Features

Experiment Analysis

Using knowledge of your data and your systems, Experiment Analysis connects the cause with the effect to help you pinpoint the root problem faster.

Historically, analyzing Fault Injection experiments has been a time-consuming process. You can see how the service reacted, but determining whether or not that was expected behavior was often done manually.

Gremlin’s Reliability Management was already a huge step forward. By integrating with a team’s monitoring solution, we can automatically determine whether a test passed or failed. But that doesn’t always tell you what went wrong, just that something did.

Experiment Analysis digs into the data surrounding the test, including the kind of failure, health check details, service type, and more, to provide crucial context beyond a simple pass/fail. But the analysis is only the beginning.

Recommended Remediation

Recommended Remediation builds on the foundation of Experiment Analysis to give you specific actions based on industry best practices and Gremlin’s extensive reliability experience with hundreds of companies.

Gremlin was founded by pioneers in the reliability space from Amazon and Netflix, the birthplace of Chaos Engineering. Our engineers come from companies where uptime is critical, and our customers include top global organizations in fields like finance and retail. Over the years, that expertise has been used to create extensive documentation, best practices, recommended tests, and more.

Recommended Remediation allows you to draw on this expertise with every test.

When a test fails, you’ll also get a detailed analysis, a list of the most likely culprits behind the failure, and recommendations for how to address the issue.

Experiment Analysis and Recommended Remediation can save teams hours of digging every month and make it easier for engineers to get started so proactive testing is more accessible. Together, they make it easier to scale across teams and improve reliability without sacrificing roadmap progress.

Gremlin MCP server

There’s power in being able to leverage and explore your own data. The Gremlin MCP server allows you to tap into that power, giving you news to gain insights and recommendations on how to improve and run your system using Gremlin.

In fact, our team at Gremlin has already proven its effectiveness right out of the gate.

Our teams use Gremlin as a regular part of our internal reliability program. While beta testing the MCP server, we  uncovered bugs that would have been real problems in production before they were ever released and found multiple opportunities for improvement. All from analyzing our own data.

Gremlin’s MCP server is now available on GitHub. Setting it up is as easy as deploying the MCP server on your host using your LLM of choice as the client, then connecting to Gremlin using your API key.

From there, your teams can use plain language to query data, uncover insights, create dynamic dashboards, and more. An MCP server allows you to unleash the full potential of AI-powered reliability management for your teams.

Reliability testing made simple—and fast

At Gremlin, we’ve always focused on how to make it easy to do the right thing. Running Chaos Engineering experiments, interpreting the results, and turning them into actionable outcomes is difficult. It requires experience in how the system behaves, various tools, and knowledge of the underworking code.

With Reliability Intelligence, we’ve taken all the data we’ve collected over the past decade and synthesized it with the knowledge of our team and industry experts to build a system that can execute tests, analyze results, and recommend remediations.

Reliability Intelligence makes it simple for teams to run tests, find risks, and fix issues faster than ever. You’ll be able to leverage our extensive expertise, speed up diagnoses, and prevent outages—without having to sacrifice velocity.

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