Every production outage is debugged twice: once by the engineer, and once by the tools that were supposed to see it coming.
*The Signal Path* builds those tools from scratch. Across 302 pages and sixteen chapters you grow a single observability system — **Lens** — from a Go binary that reads `/proc` all the way to a multi-cluster platform with its own metrics store, tracer, anomaly detection and cost model. Metrics, logs and traces: the three pillars, built by hand so you understand exactly what every off-the-shelf agent is actually doing.
**The path**
1. The single agent — reading `/proc`, emitting the first metric
2. The first thousand metrics — a TSDB ring buffer from scratch
3. Logs are just events — structured logging and the label index
4. The agent grows — eBPF probes into the kernel
5. Traces and the span — a distributed tracer
6. The unified pipeline — an OpenTelemetry Collector clone
7. The three pillars — correlating metrics, logs and traces
8. Service maps — building the dependency graph
9. Anomaly detection — statistical models that flag the unusual
10. Root cause analysis — causal graphs through a failure
11. Predictive observability — forecasting before it breaks
12. The dashboard that thinks — an SLO and error-budget engine
13. The data lake — tiered storage at petabyte scale
14. Multi-cluster — federating queries across clouds
15. The cost of seeing — what observability actually costs, and how to cut it
16. The principles that remain — what stays true when the tools change
Each chapter introduces exactly one problem, explains why it happens, and shows the code that solves it — in Go and Python, with real frameworks and explicit trade-offs.
**Companion code included.** Sixteen chapter directories, each a complete, runnable program showing Lens as it stood at the end of that chapter. Free on GitHub: `github.com/DjangoZenDev/signal-path`
**Formats:** PDF and EPUB. Download immediately after purchase.