DeepFlow vs Metoro Kubernetes Profiling
DeepFlow
deepflow.ioMetoro Kubernetes Profiling
metoro.ioSide by side
| Figure | DeepFlow | Metoro Kubernetes Profiling |
|---|---|---|
| Price from | Free | $20/mo |
| Free plan | Yes | Yes |
| Free trial | Yes | Yes |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | — |
| Linux | Yes | Yes |
| Android | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 3 | 6 |
| Spec score · eBPF Observability Tools | 8.1 (#8) | 8.8 (#3) |
| Deployment | The documentation provides Kubernetes and Docker Compose deployment methods for an all-in-one installation. | Metoro is installed with Helm and is available as Metoro Cloud, BYOC, or on-premises deployment. |
| Integrations | DeepFlow can serve as a storage backend for Prometheus, OpenTelemetry, SkyWalking, and Pyroscope, and provides SQL, PromQL, and OTLP interfaces. | Official documentation lists Slack, PagerDuty and webhooks as alert destinations, while the Cloud page also names Datadog and Grafana. |
| Purpose | DeepFlow is an observability product for complex cloud infrastructure and cloud-native applications. | Metoro continuously profiles Kubernetes workloads using an eBPF sampling profiler running at the kernel level. |
Plans
DeepFlow
- Community EditionFree
- Cloud EditionPriced on request
- Enterprise EditionPriced on request
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
DeepFlow
DeepFlow is an observability product for cloud infrastructure and cloud-native applications. It uses eBPF to collect application performance metrics, distributed traces, and continuous profiling data without intrusion. Its core capabilities include a universal service map, distributed tracing, and profiling. Built-in parsing covers HTTP, HTTPS, Dubbo, gRPC, MySQL, PostgreSQL, Redis, MongoDB, Kafka, MQTT, and DNS. DeepFlow can serve as storage for Prometheus, OpenTelemetry, SkyWalking, and Pyroscope, and offers SQL, PromQL, and OTLP interfaces. AutoTagging links observability data with cloud and Kubernetes resources, tags, and CMDB business tags. The Community Edition is open source under Apache 2.0 and is listed at free. It supports Linux servers and selected Kubernetes, cloud, and container environments; deployment guidance covers Kubernetes and Docker Compose. Enterprise Edition adds encrypted agent-to-server transmission, multi-tenancy, and data permission isolation. The listed platforms include Android, API, Linux, self-hosted, web, and Windows.
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.