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 These figures reflect RECATOOLS research as of 31 Aug 2026 and may be out of date or incomplete.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.
- 1 cluster, 2 nodes
- 28-day retention
- Limited AI SRE access
- Unlimited clusters and nodes
- Full APM, logs, traces, profiling
- Guardian AI root-cause + fix PRs
- Slack support
- Custom retention
- On-prem/BYOC deployment
- 24/7 white-glove onboarding
- Bulk discounts
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's pitch is eBPF: install one Helm chart, get full-stack telemetry across any Kubernetes cluster in under five minutes, no code changes, no restarts. That's a real advantage over agent-based observability tools that need per-service instrumentation. Where it gets ambitious is the AI SRE layer — Guardian watches production, investigates alerts on its own, and opens GitHub pull requests with proposed fixes rather than just paging a human. At $20/node/month it undercuts Datadog and New Relic for pure Kubernetes workloads, and the Hobby tier is free for small clusters. Public data on the company itself is thin and inconsistent — reported team size ranges from two to five people across sources, and funding reports conflict between a small YC check and no outside funding at all. The product is Kubernetes-only, so teams running VMs, serverless, or managed databases alongside their cluster need a second tool, and there's no independent review data yet to check the AI-fix claims against.
What people say
Twenty-eight days after its Product Hunt launch in April 2026, Metoro's page still showed zero written reviews — a reminder that this is very early-stage, whatever the engineering looks like. The engineering itself is legitimately interesting: eBPF programs loaded straight into the kernel mean the platform captures logs, metrics, traces, and continuous profiling across any Kubernetes flavor (EKS, GKE, AKS, OpenShift, bare metal) without touching application code or restarting a single pod. A Helm install gets a cluster fully instrumented in under five minutes, faster than most agent-based competitors manage.
The AI layer, called Guardian, is where Metoro differentiates from plain observability: it correlates the telemetry automatically, investigates incidents on its own, checks deploy health before and after releases, and — the standout claim — opens a GitHub pull request with a proposed fix rather than stopping at "here's the anomaly." Founders Chris Battarbee and Tom Pointon both spent years on distributed systems at Palantir and Jump Trading before starting the company in 2023.
Pricing is transparent and competitive: $20 per node per month for the Scale tier, with a genuinely free Hobby tier for small clusters (up to two nodes) that doesn't require a credit card. Company-level facts are murkier than the product claims — published team size estimates range from two to five people, and funding reports disagree on whether Metoro raised a modest YC check or nothing at all. Scope is also narrow by design: this only sees Kubernetes, so any service running outside the cluster is invisible to it.
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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