Metoro
An AI 'site reliability engineer' for Kubernetes that finds the cause of production incidents on its own and opens a pull request with the fix.
🔗 Visit Metoro
Description
When something breaks in a Kubernetes cluster at 3am, the hard part usually isn't fixing it — it's figuring out what actually broke and why, across a maze of pods, services, and logs. Metoro tries to remove that investigation step entirely: it watches your cluster continuously, and when something goes wrong, an AI agent digs through the telemetry itself, works out the likely root cause, and can even open a pull request with a proposed fix.
Metoro uses eBPF for zero-instrumentation telemetry collection — a single Helm install with no code changes or sidecars — gathering logs, metrics, traces, profiling data, Kubernetes events, and deployment context. It supports any CNCF-conformant Kubernetes distribution (EKS, GKE, AKS, OpenShift, bare-metal). The free Hobby tier covers 1 cluster / 2 nodes / 200GB monthly ingestion; the Scale tier is $20/node/month with unlimited clusters and users. It's YC-backed, SOC 2 Type II certified, and a CNCF Silver Member.
💬 Our review
The short version: Metoro is one of the more ambitious entries in the 'AI SRE' category — it doesn't just show you a dashboard, it actively investigates incidents and proposes fixes, which is a genuinely different value proposition from traditional observability tools.
Against Coroot, its closest architectural cousin (both use eBPF for zero-instrumentation Kubernetes observability), Metoro leans more managed-SaaS while Coroot offers a free self-hosted path — so budget-conscious teams comfortable running their own infrastructure may prefer Coroot, while teams that want a hands-off, fully managed AI SRE will find Metoro's automation more complete. Against Datadog, Metoro's claimed cost advantage (the company cites up to 50x cheaper for comparable coverage) is significant if accurate, though Datadog's broader non-Kubernetes coverage and mature integration ecosystem remain hard to match. The $20/node/month Scale pricing is straightforward and the free Hobby tier is generous enough to genuinely evaluate the product before paying — a fair way to try before committing.
📊 Global score
🤖 AI-enriched data
Hobby : gratuit, 1 cluster, 2 nœuds, 200GB d'ingestion/mois. Scale : $20/nœud/mois, clusters et utilisateurs illimités. Enterprise : tarif custom.
Pros
Zéro instrumentation via eBPF
Détection, diagnostic ET proposition de correctif automatiques (PR)
Installation en moins de 5 minutes (Helm)
Certifié SOC 2 Type II, membre CNCF
Cons
Uniquement Kubernetes, pas d'infra non-conteneurisée
Fonctions IA dépendantes d'un LLM tiers
Tarif Enterprise non public