Server Operations: Capacity, Queues, and Observability

What this arc covers

Move from single-host comfort to coordinated services. You will configure structured logs, trace slow queries, and rehearse graceful degradation when dependencies spike latency. Labs include synthetic load generators so you can see failure modes without risking production systems. The tone stays operational: every scenario ends with a written incident summary you could hand to a lead engineer.

Feature stack

• Load shaping exercises with honest saturation curves
• Queue back-pressure drills with operator-friendly dashboards
• Log pipeline hygiene for JSON lines and cardinality control
• CPU vs I/O bound classification using simple profiling tools
• Post-incident review templates aligned with quality standards practice
• Synthetic traffic harness with reproducible ramp schedules
• Capacity notebooks that pair graphs with plain-language narratives

Outcomes you can demonstrate

• Draft a concise post-incident brief with timelines and mitigations
• Tune a queue worker fleet using lag metrics instead of guesswork
• Select three golden signals that actually matter for a sample API