Automatic Kubernetes telemetry
Collects logs, metrics, traces, on-CPU profiles, and Kubernetes state without manual instrumentation. Custom OpenTelemetry traces and metrics are also supported.
Metoro helps Kubernetes teams monitor workloads and investigate production incidents by connecting logs, metrics, traces, profiles, and cluster state to alerts and deployment changes.
Metoro is a Kubernetes-native observability and AI SRE platform for teams that need to monitor workloads and investigate production incidents. It collects logs, metrics, traces, profiling data, and Kubernetes state, with built-in telemetry gathered without manual instrumentation. Custom OpenTelemetry telemetry can also be sent to Metoro.
The platform connects operational signals with Kubernetes context to support alert investigation, deployment verification, issue detection, and root-cause analysis. Teams can debug in the same environment used for monitoring, attach runbooks to alerts, and connect code changes to runtime behavior. Metoro is installed with Helm and is built for Kubernetes environments.
Collects logs, metrics, traces, on-CPU profiles, and Kubernetes state without manual instrumentation. Custom OpenTelemetry traces and metrics are also supported.
Detects deployments, compares telemetry before and after changes, and flags regressions with supporting evidence.
Detects unusual behavior and investigates firing alerts using telemetry and Kubernetes context, returning root-cause findings and evidence.
Search Kubernetes objects and examine their state over time alongside associated metrics, events, and logs to investigate changes.
When connected to GitHub, Metoro can inspect code changes, recommend fixes, and prepare pull requests for team review.
Teams can attach instructions to alerts or ask Metoro to gather information, giving investigations a defined operational context.
After a code or configuration deployment, compare pre- and post-change telemetry and review evidence of potential regressions.
Use an existing alert or Metoro alerting to investigate whether it reflects a real incident, then review the root-cause evidence.
Correlate service telemetry and Kubernetes state with deployment history, and, when GitHub is connected, inspect relevant code changes and proposed fixes.
Review logs, metrics, profiles, events, and historical object state together to examine bottlenecks or changes affecting a Kubernetes workload.
Metoro is installed in a Kubernetes environment using Helm. Its documentation describes a single Helm install taking under five minutes.
Metoro collects its built-in logs, metrics, traces, profiling, and Kubernetes state without manual instrumentation. Custom application telemetry can be sent through OpenTelemetry.
Yes. Teams can use Metoro alerting or send alerts from other sources to Metoro for investigation. Runbook instructions can be attached to alerts.
After connecting GitHub, Metoro can inspect code changes, recommend fixes, and create pull requests for review; the team reviews the proposed changes.
The pricing page lists a free Hobby plan for up to one cluster, one user, and two nodes, a Scale plan billed at $20 per node per month, and Enterprise pricing by discussion. AI model usage is passed through at cost.
Os dados de tráfego são apenas para referência.
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