Metoro Kubernetes Profiling vs Parca
Metoro Kubernetes Profiling
metoro.io
Parca
parca.devSide by side
| Figure | Metoro Kubernetes Profiling | Parca |
|---|---|---|
| Price from | $20/mo | Free |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 6 | 1 |
| Spec score · eBPF Observability Tools | 8.8 (#3) | 8.1 (#9) |
| Spec score · Continuous Profiling Tools | 8.8 (#5) | 8.1 (#12) |
| Deployment | Metoro is installed with Helm and is available as Metoro Cloud, BYOC, or on-premises deployment. | The project documents installation using binaries, containers, Kubernetes, and Snaps. |
| Languages | Metoro lists Go, Python, C++, C, Rust, Node.js, and Java as supported runtimes, with host-level frames for other runtimes. | The agent’s automatic profiling supports languages including C, C++, Rust, Go, Ruby, Node.js, Python, Java, .NET, Perl, and PHP. |
| Overhead | The profiler samples at 97Hz per CPU core and is designed for less than 0.5% CPU overhead per node. | The FAQ reports observed Agent overhead of less than 1% CPU and less than 200 Mb memory, depending on the number of actively profiled targets. |
| Security | Metoro states SOC 2 Type II certification, TLS 1.3 in transit, AES-256 at rest, SSO/SAML, RBAC and audit logging for Cloud. | The project says the Agent source is open source, it is written in Go, and its binaries and container images are fully reproducible; the Agent needs privileged access to load eBPF programs. |
| Support | The Scale plan includes support via Slack with Metoro engineers, while Enterprise includes 24/7 white-glove support and onboarding. | Polar Signals offers paid support for users of Parca’s open-source project. |
Plans
Metoro Kubernetes Profiling
- HobbyFree
- Cloud$20 a month
- Scale$20 a month
- BYOCPrice not published
- EnterprisePriced on request
- On PremPrice not published
In their own words
Metoro Kubernetes Profiling
Metoro Kubernetes Profiling continuously profiles Kubernetes workloads with an eBPF sampler running at the kernel level. It creates interactive flame graphs that can be grouped by service, pod, or container and filtered by cluster, namespace, deployment, or Kubernetes label. Metoro lists Go, Python, C++, C, Rust, Node.js, and Java support, with host-level frames for other runtimes. Profiling does not require SDKs, code changes, language agents, restarts, or rebuilds, and can cover third-party containers and vendor workloads. Profiles connect to 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 includes one cluster, one user, and two nodes with 28-day retention. Scale costs $20 USD per node per month, plus $0.20 per GB above 100GB per node. Enterprise pricing is contract-based and offers custom retention and SLAs. eBPF requires Linux kernel 4.18 or newer.
Parca
Parca is a self-hosted profiling system that collects and stores CPU, memory, I/O, and other profiles for queries over time. Its eBPF-based Parca Agent captures user-space and kernel-space stack traces, while the system also accepts valid pprof-formatted profiles pushed through gRPC or pulled from targets over HTTP. Users can query by labels, compare dimensions such as processes or code versions, and view profiles in the web interface with Icicle Graphs. A Grafana plugin can display profiles stored in Parca. The agent supports automatic profiling for languages including C, C++, Go, Rust, .NET, Deno, Erlang, Java, Julia, Node.js, Wasmtime, PHP, Ruby, and Python. Installation options include binaries, containers, Kubernetes, and Snaps. Parca is open source under the Apache 2 License and is free. The agent requires Linux kernel 4.18 or newer and privileged access to load eBPF programs. Parca says it receives profiling statistics and function-name metadata, not binaries or source code.