Metoro

Metoro is an AI-powered site reliability engineering (SRE) agent designed specifically for Kubernetes environments. It addresses the need for comprehensive observability, autonomous monitoring, and incident remediation within Kubernetes clusters by combining AI-driven automation with kernel-level telemetry collection. The platform is suitable for teams operating Kubernetes at scale who require deep visibility into their infrastructure and automated incident response.

The tool provides a unified observability solution that includes dashboards, service maps, and distributed traces, all generated without requiring code changes or SDK instrumentation. Metoro’s collector runs as a DaemonSet on every node, capturing a full stack of telemetry—logs, metrics, traces, profiling data, Kubernetes events, and deployment context—directly at the kernel level using eBPF. This data is automatically correlated with Kubernetes identities, ensuring that services, pods, and deployments are accurately linked for analysis. The log management feature captures stdout, stderr, and structured JSON from every container, with real-time transformations and high-performance querying. Metrics collection supports RED, USE, and custom metrics, is compatible with Prometheus and OpenTelemetry, and allows for unlimited cardinality and rapid querying. Distributed tracing works across multiple protocols and databases, with spans linked back to their originating Kubernetes resources.

Metoro’s AI SRE agent autonomously detects and resolves incidents, verifies deployments, investigates alerts, and performs root cause analysis. It can open fix pull requests when issues are identified. The platform includes continuous CPU and memory profiling, automatic detection of performance regressions, and the ability to analyze logs and metrics at scale. Kubernetes events and resources are versioned and fully indexed, providing point-in-time diffs and enabling users to traverse from any signal to its source or related deployment. Deployment context ties every rollout to its git commit, author, pull request, and affected workloads, with this information surfaced throughout the observability stack.

Delivery options include Metoro Cloud (fully managed), BYOC (hosted by the user but managed by Metoro), and On-Prem deployments with the possibility of airgapped operation. Installation is streamlined through a single Helm install, requiring no code changes and minimal setup time.