DeepFlow

DeepFlow is an observability platform for cloud infrastructure and cloud-native applications. It best suits teams that want to bring infrastructure and application signals together, especially across Kubernetes environments. Its free, open-source Community Edition has a broad technical scope, but teams needing managed alerting, reports, or custom dashboards will need Enterprise.

Overview

DeepFlow combines a universal service map, distributed tracing, and continuous profiling, with eBPF collection of application performance metrics and related data. That range makes it a candidate for teams seeking a wider observability view than tracing or profiling alone. The trade-off is a broader platform to deploy and operate rather than a narrowly focused tool.

The core modules use the Apache 2.0 License. DeepFlow supports hybrid deployment, and its documentation covers all-in-one installation with Kubernetes or Docker Compose. The maker, Yunshan Networks, was founded in December 2011.

For more tools in this area, browse eBPF Observability Tools.

Key features

Service map, tracing, and profiling

The universal service map helps teams understand service relationships, while distributed tracing follows requests and continuous profiling adds performance data over time. Having all three in one product can suit teams that need to connect service behavior with application performance; it is less compelling if the need is only one of those capabilities.

Protocol coverage and integrations

Built-in parsing covers HTTP, HTTPS, Dubbo, gRPC, MySQL, PostgreSQL, Redis, MongoDB, Kafka, MQTT, and DNS. That breadth is useful for mixed service environments, though protocol coverage alone does not establish how deeply each protocol can be inspected.

DeepFlow can act as a storage backend for Prometheus, OpenTelemetry, SkyWalking, and Pyroscope, and exposes SQL, PromQL, and OTLP interfaces. AutoTagging associates observability data with cloud and Kubernetes resources, Kubernetes tags, and CMDB business tags. These integrations and tags can help teams bring signals into existing workflows and relate them to infrastructure or business context.

Collection and deployment

eBPF-based collection is designed to gather application performance metrics, traces, and continuous profiling data without application intrusion. Kubernetes support, network visibility, application tracing, and kernel profiling make the product relevant to cloud-native and infrastructure teams. The Community Edition supports Linux servers and selected Kubernetes, cloud, and container environments, so it is not a blanket fit for every deployment.

Pricing

The Community Edition costs nothing. It is the open-source edition, with core modules under Apache 2.0, and is the clearest fit for teams prepared to run the software themselves and work within its supported environments. It does not include Enterprise alert management, report management, or custom dashboard management; teams that depend on those functions should not treat the free edition as feature-equivalent.

The Cloud Edition is a fully managed platform described as being in the testing trial phase, with custom pricing. It may suit teams seeking a managed option, but its trial-phase status makes it a less settled choice than the self-hosted Community Edition.

The Enterprise Edition has custom pricing and adds enterprise features and services. It supports encrypted transmission between agent and server, multi-tenancy, and data permission isolation. Enterprise after-sales support includes fault troubleshooting, performance tuning, version upgrades, and implementation best practices. Those capabilities matter for organizations with security boundaries or a need for vendor assistance, but come with pricing that must be obtained directly.

Platforms

DeepFlow supports Linux, Windows, and Android, along with API, web, and self-hosted access. Its deployment model is hybrid, and Kubernetes is supported. The Community Edition's stated support is narrower: Linux servers and selected Kubernetes, cloud, and container environments.

Who it's for

DeepFlow is a strong candidate for cloud-native teams that want service mapping, tracing, profiling, protocol parsing, and integration interfaces in one observability product. It is especially relevant where Kubernetes and network visibility matter, or where teams want to connect telemetry with cloud, Kubernetes, and CMDB tags.

It is a weaker fit for teams seeking a managed service with established availability, or for those who require alerting, reports, and custom dashboards without moving to a custom-priced Enterprise plan. Teams that need only one focused capability may prefer a narrower tool.

Pros and cons

Broad signal coverage: service mapping, tracing, and continuous profiling address related observability needs in one product.

Wide protocol and integration range: support for common databases, messaging systems, and telemetry interfaces can help in heterogeneous environments.

Open-source core: Apache 2.0 licensing and a free edition give teams a self-hosted route to the core modules.

Community feature gaps: alert management, report management, and custom dashboard management are reserved for Enterprise.

Enterprise costs are custom: organizations needing its security controls and support must request pricing rather than select a published rate.

Alternatives

Choose Coroot if you want a freemium, self-hosted option with an Apache 2.0 Community Edition and a published $1 a month Standard plan.

Kubeshark is an alternative with a free Community plan capped at three nodes or 60 pods, plus unlimited API call capacity and community support.

Choose Odigos if core OpenTelemetry tracing in an Apache 2.0 open-source edition is the priority; its Enterprise plan has custom pricing.

Elastic Observability is another option, with a free plan and a paid, usage-based serverless offering.

groundcover may suit teams looking for a free-forever BYOC plan with 12-hour data retention and Slack community support.

Qpoint offers a free Community plan for up to 25 endpoints, including agent discovery and monitoring with attribution.

Metoro Kubernetes Profiling is worth considering for a small Kubernetes profiling setup: its free Hobby plan covers one cluster, one user, two nodes, and 28-day retention.

Anteon is another observability option.

Verdict

Choose DeepFlow if your team wants an open-source, hybrid observability platform spanning service mapping, tracing, profiling, and broad protocol support. Its main advantage is the breadth of those capabilities and integrations; its main drawback is that the Community Edition leaves out several management features, while the fuller Enterprise offering has custom pricing. Look elsewhere if you need those features without an enterprise sales process, or prefer a narrowly scoped tool.