Elastic named Strong Performer in Forrester Wave for AIOps Platforms

What Forrester scored highest

Elastic says the Forrester evaluation covered 10 providers and 24 criteria. In five of them, the company reports, it received the highest possible score:

• algorithmic trust and explainability
• observability as code (OaC) and GitOps alignment
• AI stack and semantic observability
• sovereign deployment and data isolation
• pricing flexibility and transparency

Elastic links these results to how it built AIOps into an AI SRE, which it says shows its evidence, learns from every investigation and finds what alerts miss. The company's blog post, written by Natalie Blake and published on October 28, 2026, frames the ratings with the phrase "we believe", so the interpretation is Elastic's own.

Elastic's argument: trust, context and learning

Elastic argues that the AI debate in operations has moved beyond whether a model can propose a root cause. In its view, teams now ask whether they can rely on the answer, especially as telemetry keeps growing, code is generating code, and AI-based components make failures harder to predict.

The company's product here is Elastic nightshift AI SRE, which it describes as an always-on AI coworker that investigates like an engineer. According to Elastic, it lays out its reasoning, the data it looked at, the explanations it considered and the evidence behind its conclusion. SRE teams can follow the investigation from the start and confirm it before approving an action.

On data, Elastic points out that many teams cut telemetry to control costs, so the evidence an investigation needs may be gone when an incident hits. The company says it offers cost-efficient storage for logs, traces and metrics so teams can keep everything in one place. It also says it distills the relevant parts of the environment into compact context for the SRE agent, which it claims improves both accuracy and token-efficiency.

Elastic also says its AI SRE carries lessons from past incidents into the next one, so a recurring problem is recognized sooner and recommendations improve over time. It contrasts this with alert-based detection, which it says only covers failures that can be predicted, and says its system aims to surface the "unknown unknowns" that cannot be covered by a rule.

Open standards and what it means for buyers

Elastic describes itself as open by design and built on OpenTelemetry. It says it keeps data in its native form, so teams can adopt new instrumentation without rebuilding pipelines or translating schemas.

The company ties its pitch together as a chain: efficient storage makes complete context possible, complete context makes AI investigations accurate, transparent reasoning makes them checkable, and open standards keep the investment portable. For teams evaluating AIOps tools, the report's criteria on explainability, deployment sovereignty and pricing transparency are the areas where Elastic says it scored highest.

The Forrester report is available through Elastic's post. Forrester states that it does not endorse any company, product, brand or service in its research publications, and that its opinions reflect judgment at the time and are subject to change. Elastic also notes that the release and timing of any features described remain at its sole discretion, and that features not currently available may not be delivered on time or at all.