Metoro
eBPF-powered AI SRE that detects and root-causes Kubernetes incidents and drafts fixes — no code changes needed.
Overview
Metoro is a Y Combinator-backed (Summer 2023) AI Site Reliability Engineer platform for Kubernetes teams. It uses eBPF kernel-level instrumentation to capture logs, metrics, distributed traces, continuous profiling and Kubernetes events across EKS, GKE (not Autopilot), AKS, OpenShift and bare metal with a single Helm install and no application code changes.
Once an incident is detected, its AI agent, Guardian, investigates the root cause, filters noisy alerts, checks deployment health around releases and drafts code fixes that a user can raise as a GitHub pull request — nothing is merged automatically. Metoro offers a managed cloud hosted in US East, bring-your-own-cloud, and air-gapped on-premises deployment, and advertises SOC 2 Type II certification.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 27 Sep 2026 and may be out of date or incomplete.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, 1 user, 2 nodes
- 28-day retention
- Limited AI SRE access
- Unlimited clusters, users and nodes
- 100 GB per node, then $0.20/GB
- Guardian root-cause + drafted code fixes
- Slack support
- Custom retention
- On-prem (air-gapped) or BYOC deployment
- 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 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 drafts code fixes rather than just paging a human, though a person still opens and merges the pull request. At $20 a node a month it undercuts Datadog and New Relic for pure Kubernetes workloads, and the Hobby tier is free for small clusters. The company is small — YC lists a team of two — and announces no funding beyond Y Combinator. It is Kubernetes-only, so teams running VMs, serverless or managed databases alongside their cluster need a second tool, and there is no independent review data yet to check the AI-fix claims against.
What we found
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 — drafts a code fix rather than stopping at "here's the anomaly". The docs are more careful than the marketing: Guardian writes the diff and a person opens the pull request, and nothing is merged automatically. The company came out of Y Combinator's Summer 2023 batch; its launch post credits Chris Battarbee and Tom Pointon with distributed-systems work at Palantir and Jump Trading, though YC now lists only Battarbee as an active founder.
Pricing is transparent and competitive: $20 per node per month for the Scale tier, plus $0.20 a gigabyte past 100 per node, and a genuinely free Hobby tier for one cluster of up to two nodes with 28-day retention; paid plans carry a 14-day trial. Company-level facts are thinner than the product claims: YC lists a team of two, Metoro describes a small team in London and San Francisco, and no funding beyond Y Combinator is announced anywhere on its own site. Scope is narrow by design: this only sees Kubernetes, GKE Autopilot excluded, so anything outside the cluster is invisible to it.
Two claims in circulation need care. Metoro advertises SOC 2 Type II and CNCF Silver membership in its footer, but publishes no trust portal, and it does not appear in the CNCF's own member data. And its managed cloud runs in US East with every subprocessor listed in the United States, so data residency elsewhere means the on-premises option.
Compiled by RECATOOLS from public sources: vendor documentation and pricing, code repositories and published reporting.
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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