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Metoro
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A ready Metoro account with a paid subscription: install the agent into your cluster with a single Helm command, and within minutes you see metrics, logs, traces and the service map. The first thing to establish is whose email the account uses: the seller's email means access can technically return to them along with your cluster's telemetry. Metoro sees the whole inside of production, including process profiles and deployment context with author names, so make sure you ask who else has access to the account and whether someone else's clusters are still connected. Confirm the paid node count and the remaining period — they determine whether your whole fleet can be onboarded.
An autonomous site reliability engineer for Kubernetes: observability and incident analysis in one place, with telemetry gathered by eBPF — a Linux kernel technology — so application code stays untouched and containers are never restarted. Straight after installation you see seven kinds of signal: logs from stdout and structured JSON, metrics following the RED and USE methodologies, distributed traces with zero code changes, continuous profiling with CPU and memory flame graphs, Kubernetes events, cluster resource versioning, and deployment context down to the commit, author and pull request. Then the AI takes over: it notices a regression or anomaly by itself, investigates a firing alert, verifies whether a fresh deployment affected production, produces a root cause analysis and can open a pull request with a fix. It ships with a cluster service map, dashboards, alerting, cost monitoring, uptime and cron job monitoring, plus separate monitoring of AI agent behaviour. It installs with a single Helm command and is operational within minutes, behaves identically on EKS, GKE, AKS, OpenShift and bare-metal Kubernetes, is compatible with OpenTelemetry and Prometheus, notifies in Slack and delivers fixes through GitHub. It can be deployed as a cloud service, inside your own cloud managed by the vendor, or entirely on your own infrastructure.