Testing
XDP (eXpress Data Path) is the fastest packet processing layer in Linux — hooks into the NIC driver before the kernel's network stack, processes packets at wire speed, and acts on them: drop, pass, redirect, or transmit. The same properties that make XDP powerful make it dangerous to ship
Testing
Cilium Tetragon brings eBPF-powered runtime security enforcement to Kubernetes. It can block file access, kill processes that violate policy, and generate structured security events at the kernel level — all without modifying your application. But like any security control, Tetragon policies are only as good as the testing behind them.
Testing
Writing eBPF programs is hard. Testing them is harder. The kernel-userspace boundary, the BPF verifier, the lack of standard debugging tools — all of it conspires to make eBPF a domain where bugs hide for a long time. libbpf, the canonical C library for loading and interacting with BPF programs,
Testing
Modern software testing has a visibility problem. Unit tests tell you whether your code returns the right value. Integration tests confirm your services talk to each other. But neither tells you what the kernel is actually doing while your application runs — which syscalls fire, how long disk I/O blocks,
Testing
The Linux kernel's BPF subsystem has one of the most sophisticated CI testing infrastructures in open-source software. The BPF selftests, the netdev CI, the QEMU-based kernel test framework — these systems catch regressions in hundreds of BPF programs across dozens of kernel versions before any code merges.
Testing
Observability pipelines fail in subtle ways. A field name typo in a log goes unnoticed until a dashboard breaks. A new label with high cardinality silently degrades Prometheus performance over three weeks. A sampling rule with an off-by-one error drops 10% more traces than intended. None of these
Testing
Vector is fast. The Rust-based observability data pipeline handles logs, metrics, and traces with impressive throughput. But speed means nothing if your transforms mangle data or your sinks silently drop events. Vector's built-in unit test framework makes it practical to test pipelines without running a full
Testing
OpenTelemetry Collector sits at the heart of modern observability pipelines. It receives telemetry from your services, processes it, and exports it to your backends. When that pipeline misbehaves—dropping spans, garbling attributes, or misrouting logs—debugging it is painful. The solution is testing it properly before it ever touches production.
Testing
Fluentd and Fluent Bit are the workhorses of log aggregation. Fluentd's rich plugin ecosystem handles complex parsing and routing; Fluent Bit's lightweight C core handles high-throughput edge collection. Both have one thing in common: when their configs break, logs disappear silently. This guide shows how
Testing
Unit testing individual pipeline components catches local bugs. But the integration between Kafka, OTel Collector, and your backends is where real failures hide. A schema mismatch between Kafka producer and OTel receiver. A Loki label cardinality issue that only surfaces under load. An OTel Collector exporter that retries forever when
Observability
Sentry integration is easy to break silently—a wrong DSN, a muted beforeSend hook, or a missing SDK init call can cause errors to vanish without anyone noticing. This guide covers how to verify Sentry actually captures what it should: SDK mocks in unit tests, integration tests for captureException, testing
Observability
Prometheus alerting rules can fail silently for years: a typo in a PromQL expression, a label mismatch in Alertmanager routing, or a threshold that never actually fires. promtool provides a native unit testing framework for alert rules—YAML-defined tests that validate expressions against synthetic time-series data without running