Platform EngPractitioner

Observability Fundamentals

Prometheus · Grafana · Loki · Tempo · OpenTelemetry

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Two full lessons from Observability Fundamentals — exact topics, hands-on lab pairings, same depth as the paid course. Watch the videos free; sign up to access labs + the rest of the curriculum.

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Lesson 0120 min

The three pillars — and why one of them is misunderstood

Metrics, logs, traces — every observability vendor pitches the three pillars. We explain what each is actually for, when traces are the most underused signal, and how to choose what to instrument first.

What this lesson teaches

· Metrics: cheap to store, lossy, great for alerting and dashboards
· Logs: expensive at scale, lossless, great for debugging unknown unknowns
· Traces: most underused — the only way to debug distributed systems
· Why most teams instrument metrics first (it's the wrong order)
· Cost reality: log volume can dominate a Datadog bill 20-to-1

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Lesson 0228 min

OpenTelemetry the right way — once, not three times

OpenTelemetry is the right answer to vendor lock-in but easy to set up wrong. We walk through instrumentation, the collector, exporters, and the trap of 'instrumented' apps that emit nothing useful.

What this lesson teaches

· OTel SDK auto-instrumentation: what works, what doesn't
· The Collector pattern: deploy it as a sidecar or daemonset
· Exporters: Prometheus + Loki + Tempo (open) vs Datadog + Honeycomb (commercial)
· Sampling strategies: head, tail, dynamic — when each
· What 'context propagation' actually means in practice

● Paired lab

Instrument a 3-service Node + Python app with OTel and trace a request end-to-end in Tempo.

These are 2 of 30 lessons. Subscribe to @computerpathshala654 for new lessons + course launches. The full 28 remaining lessons are included with cohort enrolment, with a 7-day money-back guarantee.

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