Moving Our Observability Data Collector from Sidecars to eBPF

Speedscale is moving its Kubernetes observability collector from per-pod sidecars to eBPF programs running at the Linux kernel level, arguing that sidecars add proxy latency, consume CPU and memory, increase operational complexity, and couple collection failures to application health. The company describes observability as the collection and correlation of logs, traces, and metrics for diagnosing and improving distributed systems, with eBPF providing lower-overhead, real-time network visibility by attaching safely verified programs to kernel socket hooks. Its implementation aims to preserve full request and response payload capture and protocol-aware parsing for HTTP, HTTP/2, gRPC, database traffic, and other protocols, despite eBPF constraints involving limited memory, instruction limits, stateless execution, and complex protocol state management. Speedscale reports reductions of 30–50% in CPU use, 60–80% in memory consumption, and 2–5 milliseconds in p99 latency, while allowing node-level deployment rather than maintaining a sidecar for every pod. The company also acknowledges that kernel-level capture cannot fully interpret application semantics, runtime behavior, encrypted traffic context, or certain stateful protocols, so it uses a hybrid model that supplements eBPF with language-level instrumentation, particularly for Java workloads.

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