LESSON 6.6 · Engineering · 120 min
Service reliability: limits, caching, degradation, observability
Service reliability: limits, caching, degradation, observability. Learn SLOs, queues, backpressure, prefix caching, and tracing and complete: Design capacity for 100 QPS. Part of t
Learning objectives
- Explain what problem “Service reliability: limits, caching, degradation, observability” solves without hiding behind terminology.
- Trace the variables and causal links across SLOs, queues, backpressure.
- Complete “Design capacity for 100 QPS” and judge the result with evidence rather than intuition.
Core concepts
SLOs
SLOs is part of the lesson’s causal model. State its inputs, outputs, invariants, and failure mode; then verify it with a hand-check or a minimal experiment before moving to an optimized implementation.
queues
queues is part of the lesson’s causal model. State its inputs, outputs, invariants, and failure mode; then verify it with a hand-check or a minimal experiment.
backpressure
backpressure is part of the lesson’s causal model. State its inputs, outputs, invariants, and failure mode; then verify it with a hand-check or a minimal experiment.
prefix caching
prefix caching is part of the lesson’s causal model. State its inputs, outputs, invariants, and failure mode; then verify it with a hand-check or a minimal experiment.
and tracing
and tracing is part of the lesson’s causal model. State its inputs, outputs, invariants, and failure mode; then verify it with a hand-check or a minimal experiment.
Build and verify
Design capacity for 100 QPS
- Predict: write the expected output, trend, or failure before running code.
- Build: implement only the minimum components needed to answer the question.
- Verify: compare with a baseline or trusted implementation; save seeds, parameters, and raw outputs.
- Transfer: change one shape, dataset, scale, or workload condition and explain whether the conclusion still holds.