Metoro
eBPF-powered AI SRE that auto-detects, root-causes, and opens fix PRs for Kubernetes incidents — no code changes needed.
Overview
Metoro is a Y Combinator-backed AI Site Reliability Engineer platform purpose-built for Kubernetes teams. It uses eBPF kernel-level instrumentation to capture full-stack telemetry — logs, metrics, distributed traces, continuous profiling, and Kubernetes events — across any cluster (EKS, GKE, AKS, OpenShift, bare-metal) with a single Helm install and no application code changes. The platform becomes operational in under five minutes and correlates all signals automatically to surface production issues the moment they occur.
Once an incident is detected, Metoro's AI agents autonomously investigate the root cause, filter noisy alerts, verify deployment health before and after releases, and generate GitHub pull requests with proposed fixes. Founders Chris Battarbee and Tom Pointon (both ex-Palantir, Jump Trading) built the tool they wished existed while debugging distributed systems. Metoro is SOC 2 Type II certified, a CNCF Silver member, and supports flexible deployment via fully managed cloud, bring-your-own-cloud, or on-premises air-gapped installations with Asia-Pacific data residency available.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 16 Jun 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.
Use cases
What you can produce with Metoro
- Full-stack Kubernetes telemetry (metrics, logs, traces, profiling, events) with zero code changes, live in under 5 minutes
- Autonomous incident detection with AI root-cause narrative and correlated evidence across signals
- AI-generated GitHub pull requests proposing infrastructure and configuration fixes
- Deployment verification reports comparing pre- and post-release telemetry for latency, error rate, and memory regressions
- Alert noise filtering that distinguishes flapping alerts from genuine production issues before paging on-call
- REST API, webhooks, and OpenTelemetry compatibility for integration with Slack, PagerDuty, Datadog, and Grafana
- SOC 2 Type II compliant data storage with Asia-Pacific region option and AES-256 encryption at rest
ASEAN Perspective
Metoro in Southeast Asia
Metoro supports an Asia-Pacific data residency region in its fully managed cloud offering, which addresses the data-localisation concerns relevant to Singapore's PDPA, Malaysia's PDPA 2010, and Indonesia's PDP Law. The $20/node/month pricing is competitive against Datadog and New Relic in a region where engineering teams are cost-sensitive, and the zero-instrumentation deployment suits ASEAN startups and fintechs running lean DevOps functions. However, Metoro is a seed-stage, roughly five-person company with no documented ASEAN customer cases or local sales presence, meaning regional buyers should factor in support timezone risk and the possibility of roadmap pivots before committing production workloads.
Metoro is genuinely impressive technical work for Kubernetes-native teams: eBPF auto-instrumentation removes the biggest friction point of any observability rollout, and the AI-driven root-cause-to-pull-request loop addresses a real gap between detection and resolution that established platforms leave entirely to humans. The $20/node/month Scale pricing is meaningfully cheaper than Datadog or New Relic at equivalent cluster sizes, and the free Hobby tier lets small teams evaluate the full product with no credit card. SOC 2 Type II and CNCF Silver membership signal serious enterprise intent for a team of roughly five people.
The caveats are real, though. Metoro's scope is deliberately narrow — it sees only Kubernetes workloads, so teams with VMs, serverless functions, managed databases, or non-container services will need a second observability layer. Incident-management depth (on-call scheduling, escalation routing, status pages) is absent and must come from integrations. At 50+ nodes the $1,000+/month cost starts to challenge the affordable positioning, and the ecosystem is noticeably less mature than incumbents: documentation is thinner, the integration catalog smaller, and there are no credible third-party review scores yet.
What people say
Metoro is an early-stage but technically credible AI SRE platform that removes instrumentation friction via eBPF and closes the gap between alert and fix with AI-generated pull requests — a workflow few established incumbents offer out of the box. Pricing at $20/node/month undercuts Datadog for pure Kubernetes workloads, and a free Hobby tier enables genuine evaluation. No third-party platforms have published verified user ratings as of mid-2026 (its April 2026 Product Hunt launch shows zero reviews), so independent benchmarks are unavailable. Key limitations: Kubernetes-only scope, no native incident management, a small team, and thinner documentation than mature alternatives.
Summary of public user & expert reviews, compiled by RECATOOLS.
Notable facts
- Metoro's AI agents can open a GitHub pull request to fix an infrastructure issue before an on-call engineer has even acknowledged the alert — the company reports roughly a 60% merge rate on auto-generated fix PRs.
- The entire platform deploys via a single Helm command and reaches full observability in under five minutes, compared with days or weeks of instrumentation work required by traditional APM tools.
- Metoro is a CNCF (Cloud Native Computing Foundation) Silver member — an unusual distinction for a seed-stage, roughly five-person startup — and holds SOC 2 Type II certification.
- Both founders worked at Palantir on Foundry's compute platform and built distributed systems at Jump Trading before creating Metoro as the debugging tool they wished had existed.
Frequently asked questions
About this listing
This entry was compiled from publicly available data including Metoro's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with Metoro unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
For the latest details, please refer to Metoro directly →
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