DeepFlow – open-source eBPF Distributed Tracing

DeepFlow – open-source eBPF Distributed Tracing

for Cloud-Native Applications

Absolutely no Code Complete Stack eBPF & & Wasm

Network-Centric Distributed Tracing with DeepFlow: Repairing Your Microservices in Zero Code Download paper > > >

Relied on by leading worldwide brand names

Dispersed Tracing for Any Request

Absolutely no Code dispersed tracing powered by eBPF supports applications in any language and facilities consisting of entrances, service meshes, databases, message lines, DNS and NICs, leaving no blind areas. Complete Stack network efficiency metrics and file I/O occasions are immediately gathered for each Span. Dispersed tracing goes into a brand-new age: Zero Instrumentation.

Constant Profiling for Any Function

DeepFlow gathers profiling information at an expense of listed below 1% with Absolutely no Code plots OnCPU/OffCPU function call stack flame charts, finds Complete Stack efficiency traffic jam in application, library and kernel functions, and instantly relates them to distrubuted tracing information. DeepFlow can even evaluate code efficiency through network profiling under old variation kernels (2.6+).

Smooth Integration with Popular Stack

DeepFlow can act as storage backed for Prometheus, OpenTelemetry, SkyWalking and Pyroscope. It likewise offers SQL, PromQL and OLTP APIs to work as information source in popular observability stacks. It injects meta tags for all obervability signals consisting of cloud resource, K8s container, K8s labels, K8s annotations, CMDB service characteristics, and so on, removing information silos.

Efficiency 10x ClickHouse

SmartEncoding injects standardized and pre-encoded meta tags into all observability information, lowering storage overhead by 10x compared to ClickHouse String or LowCard approach. Customized tags and observability information are saved individually, making tags offered for practically endless measurements and cardinalities with uncompromised question experience like BigTable

OpenSourced under the Apache 2.0 License

Star us on GitHub >> > >

$ helm set up deepflow — repo https://deepflowio.github.io/deepflow deepflow

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