Metoro Kubernetes Profiling
Metoro Kubernetes Profiling uses an eBPF sampler at the kernel level to profile Kubernetes workloads continuously and display interactive flame graphs.
What Metoro Kubernetes Profiling is
Metoro Kubernetes Profiling uses an eBPF sampler at the kernel level to profile Kubernetes workloads continuously and display interactive flame graphs. Users can group graphs by service, pod, or container and filter them by cluster, namespace, deployment, or Kubernetes label. The profiler is designed for less than 0.5% CPU overhead per node and supports Go, Python, C++, C, Rust, Node.js, and Java, with host-level frames for other runtimes. It can profile third-party containers and vendor workloads without requiring SDKs, code changes, language agents, restarts, or rebuilds. Profiles connect with Metoro APM traces, logs, metrics, pod state, and deployment context. Installation uses Helm, with Cloud, BYOC, and on-premises deployment options. The free Hobby plan is limited to one cluster, one user, and two nodes, with 28-day retention. Scale costs $20 USD per node per month, with $0.20 per GB charged for usage above 100GB per node. Enterprise uses contract pricing. Profiling requires Linux kernel 4.18 or newer.
Good
- Interactive flame graphs with service, pod, and container views.
- Profiles connect to traces, logs, metrics, and deployment context.
- No application changes or restarts are required.
- Can profile third-party and vendor containers.
- Available as Cloud, BYOC, or on-premises.
Watch out
- Free plan is limited to two nodes.
- eBPF requires Linux kernel 4.18 or newer.
- Scale charges extra above 100GB per node.
- Enterprise pricing is by contract.
Who it suits
It suits teams investigating application CPU and memory behavior in supported Kubernetes environments, including third-party containers they do not build. The free plan may fit small deployments; larger environments can consider Scale or Enterprise.
Verdict
Metoro links workload profiles with surrounding Kubernetes and observability context, without requiring application instrumentation changes. Check the node allowance, kernel requirement, and per-node pricing against your environment.
Plans and prices
From Metoro Kubernetes Profiling's own pricing page, checked 15 Oct 2026.
| Plan | Price | What it gives you |
|---|---|---|
| Hobby | Free | 1 cluster · 1 user · 2 nodes · 28-day retention · Free forever |
| Cloud | $20 a month | Fully managed cloud · unlimited users · SSO/SAML · full observability · $20 per host/month |
| Scale | $20 a month | Unlimited clusters · unlimited users · unlimited nodes · 28-day retention · engineer Slack support · $20 USD per Kubernetes node/month; $0.20/GB over 100GB per node |
| BYOC | — | Isolated instance in your cloud · feature parity with Cloud · managed by Metoro · one-month pilot · Contact us |
| Enterprise | Priced on request | Unlimited clusters · unlimited users · unlimited nodes · bulk discounts · 24/7 support · custom SLA · on-premises · BYOC · Let's talk |
| On Prem | — | Isolated instance · customer-managed · dedicated support engineer · one-month pilot · Contact us |
The facts
Each one read from Metoro Kubernetes Profiling's own pages, with the date it was checked.
What it does
- AI operations
- Metoro offers automated issue detection, alert investigation, root-cause analysis, deployment verification, runtime-to-code context and remediation workflows.checked 15 Oct 2026
- AI privacy
- The AI policy says AI is opt-in, providers do not train on customer data, connections and stored results are encrypted, and agents have no general internet access.checked 15 Oct 2026
- API
- The API reference documents a POST environment-creation endpoint using bearer authentication that returns an environment token.checked 15 Oct 2026
- APM
- Its eBPF collection maps Kubernetes services, requests, latency, errors and traces without manual instrumentation.checked 15 Oct 2026
- Automatic instrumentation
- Metoro installs an eBPF DaemonSet with Helm and gathers telemetry without application code changes, SDKs, sidecars or container restarts.checked 15 Oct 2026
- Continuous profiling
- The Kubernetes Profiling feature continuously samples CPU activity at the kernel, attributes stacks to pods and services, and relates changes to deployments, traffic shifts and noisy neighbors.checked 15 Oct 2026
- Correlation
- Profiles are connected to Metoro APM traces, logs, metrics, pod state, and deployment context.checked 30 Sep 2026
- Deployment
- Metoro is installed with Helm and is available as Metoro Cloud, BYOC, or on-premises deployment.checked 30 Sep 2026
- Deployment options
- Metoro offers managed Cloud, BYOC in a customer account and on-premises deployment models.checked 15 Oct 2026
- Documentation and support
- Metoro provides Mintlify-hosted technical documentation, a community Slack and dedicated Slack Connect support for customers.checked 15 Oct 2026
- Flame graphs
- Interactive flame graphs can be aggregated by service, pod or container and filtered by cluster, namespace, deployment or Kubernetes label.checked 15 Oct 2026
- Funding
- Crunchbase lists a Metoro pre-seed funding round, but the amount and date are hidden on the public page.checked 15 Oct 2026
- Instrumentation
- Profiling requires no SDKs, application code changes, language agents, restarts, or rebuilds.checked 30 Sep 2026
- Integrations
- Official documentation lists Slack, PagerDuty and webhooks as alert destinations, while the Cloud page also names Datadog and Grafana.checked 15 Oct 2026
- Kubernetes support
- Metoro states support for EKS, GKE, AKS, OpenShift, Rancher, k3s, kind, and self-managed CNCF-conformant Kubernetes distributions; eBPF requires Linux kernel 4.18 or newer.checked 30 Sep 2026
- Languages
- Metoro lists Go, Python, C++, C, Rust, Node.js, and Java as supported runtimes, with host-level frames for other runtimes.checked 30 Sep 2026
- Limit: G2 reviewer
- That reviewer said the main difficulty was making sense of the large amount of information presented.checked 15 Oct 2026
- Limit: independent review
- FunBlocks said regulated teams may be uneasy about AI-generated code changes and requested finer controls over agent decisions plus broader custom-CRD support.checked 15 Oct 2026
- Logs and events
- The platform searches application logs, Kubernetes events, deployment changes and workload metadata through one investigation path.checked 15 Oct 2026
- MCP and SDK extensibility
- Metoro publishes an MCP server that can be built in Go and exposes tools for querying Metoro data from AI clients, although it cannot start an AI investigation run directly.checked 15 Oct 2026
- Notable news
- LinkedIn records Metoro’s Product Hunt launch announcement approximately six months before the page capture.checked 15 Oct 2026
- OpenTelemetry
- The in-cluster exporter accepts custom metrics through an OTLP HTTP endpoint and examples are provided for Python, Go and Node.js.checked 15 Oct 2026
The company
- Company founding
- LinkedIn gives Metoro a 2023 founding year and San Francisco, California headquarters.checked 15 Oct 2026
- Company size
- LinkedIn lists Metoro as privately held with 11–50 employees.checked 15 Oct 2026
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