Elastic named a Leader in the 2025 Gartner® Magic Quadrant™ for Observability Platforms

Observability has an investigation problem, and dashboards and alerts aren’t enough for solving problems in today’s complex systems. AI-driven capabilities, powerful analytics, and the ability to scale are essential to drive real-time investigations while keeping costs low. We think this is why Elastic has been named a Leader in the 2025 Gartner® Magic Quadrant™ for Observability Platforms for the second time.

Elastic Observability helps organizations monitor, troubleshoot, and optimize their entire ecosystem from infrastructure and application performance to end-user experience, all powered by the Search AI Platform. We think our inclusion as a Leader reinforces our belief that open architecture, AI-powered insights, and scalability are the future of observability.

As an SRE, troubleshooting issues is more complex than ever. Regardless of the situation, there is a ton of information that needs to be consumed and processed. This includes not only what the customer is experiencing, but also internal data and context to help provide the most appropriate resolution.

Elastic offers AI-driven capabilities such as multi-signal anomaly detection, pattern analysis, and correlation and an AI Assistant that acts as a virtual SRE. 

With Elastic’s AI Assistant, an SRE can perform analysis using natural language questions. Elastic’s AI Assistant versatility comes not only from connecting to an out of box LLM or one of your choice, but also leveraging Elastic’s vector database to provide contextual and insightful information such as:

• Issues from internal GitHub repos, Jira, etc.

• Customer issues from your support service

• Retrieving and using runbooks

• Creating charts and dashboards

Managing LLMs is vital for Service Reliability Engineers (SREs) to manage GenAI applications and ensure error-free operations while minimizing the risks associated with the unpredictable nature of LLM generated responses.

Elastic provides out-of-the-box integrations for all major models, such as Azure OpenAI, OpenAI, Amazon Bedrock, and Google Vertex AI. These integrations include prebuilt dashboards that display token usage, cost-related metrics, and logs and metrics such as total invocations, error rates, and latency, broken down by model or endpoint. Cost insights are delivered automatically through Elastic’s alerting, SLOs, AI Assistant, and any configured ML jobs.

Gartner, Magic Quadrant for Observability Platforms,

Gregg Siegfried, Matt Crossley, Padraig Byrne, Andre Bridges, Martin Caren 7 July 2025.

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The release and timing of any features or functionality described in this post remain at Elastic's sole discretion. Any features or functionality not currently available may not be delivered on time or at all.

This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document.  The Gartner document is available upon request from Elastic.