Elastic the Search AI Company, today announced that Gartner®, Inc. has named it a Leader in the Magic Quadrant™ for Observability Platforms for the third consecutive year. The evaluation was based on specific criteria that analyzed the company’s overall Completeness of Vision and Ability to Execute. This recognition comes alongside the Gartner companion Critical Capabilities for Observability Platforms report where Elastic ranked first for three of the seven use cases evaluated.
“Observability teams are facing unprecedented software complexity as AI-powered development accelerates the pace of innovation. More code, more services, and more telemetry create new challenges for maintaining reliability and controlling costs, which is why organizations need observability platforms that help them investigate issues faster and operate more efficiently at scale,” said Baha Azarmi, general manager, Observability at Elastic. “We believe Elastic’s third consecutive recognition as a Leader reflects our commitment to delivering agentic observability at scale, combining efficiency, open standards, and AI-driven investigations powered by complete operational context so teams can identify and resolve issues faster.”
We believe Elastic’s placement reflects three areas of differentiation:
- OpenTelemetry integration: Organizations can standardize on OpenTelemetry using upstream SDKs and community collectors without sacrificing analytics depth or investigation capability on the other side — no schema translation, no conversion layer, and no reinstrumentation required.
- Market responsiveness: In our view, the observability market is shifting rapidly, and Elastic’s observability platform has evolved to keep pace. It now includes MCP support that lets customers connect Elastic’s signals directly to any agent or AI harness they’re running today. Building on that foundation, Elastic is developing an autonomous SRE agent that can take action immediately when an incident fires, investigate the blast radius, form hypotheses, and surface a root cause using the telemetry stack customers already run. The AI SRE agent is expected to learn from every incident it encounters, becoming more specialized to each customer’s environment over time. Elastic is uniquely positioned with the signal depth, query speed, and AI infrastructure needed to make autonomous investigation work at production.
- Business model: At the datastore level, Elasticsearch stores logs and traces up to 4x more efficiently than standard indexing, and its columnar metrics datastore is up to 2.5x more efficient than Prometheus. This storage savings doesn’t compromise speed, with increased logs query performance of up to 40% faster. Second, by consolidating those signals onto a single platform, teams share infrastructure, query language, and pipelines rather than maintaining siloed tooling for each discipline.
“Elastic has become PepsiCo’s gold standard for telemetry ingestion, correlation, and resolution velocity,” said Vinod Chilakalapudi, director of Observability at PepsiCo. “It now sets performance baselines across our observability ecosystem.”
