Sidecars were the observability pattern of the 2020s. eBPF is the pattern of the 2026 and beyond — and the difference is dramatic.
Traditional monitoring with DaemonSets and sidecars adds 10-30% resource overhead per pod. eBPF observability with tools like Cilium Hubble and Pixie runs in the kernel with less than 1% overhead. Zero code changes. Zero sidecar injection. Just attach a BPF program and you get:
- HTTP/gRPC latency at the kernel level (no proxy hop)
- Network flow logs with process-level attribution
- CPU flame graphs by container without profiling agents
- File system and DNS activity per pod
The architecture is elegant: BPF programs hook into kernel tracepoints and kprobes, a user-space agent (running as a DaemonSet) collects and enriches the data, and metrics flow to your existing Prometheus/Grafana stack. No sidecars. No mTLS overhead. No Envoy configuration.
The full article walks through setting up Cilium Hubble on an EKS cluster, configuring Pixie for auto-telemetry, and building eBPF-based SLO dashboards that correlate kernel events to user-facing latency.
Dive into the kernel: https://devtocash.com/blog/ebpf-observability-sre-end-of-sidecars-2026
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