Performance Engineering: Assessment, Optimization & Capacity Strategy

Generic, brand-neutral engineering capability; sourced playbooks in references//knowledge/. [DOC]

TL;DR

Performance engineering ensures systems meet latency, throughput, and reliability targets under current and projected load. The skill produces actionable performance baselines, load testing strategies, capacity models, caching architectures, CDN configurations, and SLA/SLO definitions that translate technical metrics into business guarantees [EXPLICIT]

When to Use

• Establishing performance baselines for new or existing systems
• Designing load testing strategies before launches or migrations
• Capacity planning for anticipated growth or seasonal spikes
• Evaluating caching layers for hit ratio optimization
• Configuring CDN and edge strategies for global content delivery
• Defining SLA/SLO targets tied to business requirements
• Diagnosing production bottlenecks (CPU, memory, I/O, network)

When NOT to Use

• General infrastructure provisioning without performance focus — use infrastructure-architecture
• Application-level code architecture and patterns — use software-architecture
• Log aggregation and alerting without performance context — use observability
• Cost optimization without performance constraints — use cost-estimation

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Sub-capabilities (resource map)

Deep, evidence-tagged playbooks — open the one the task needs (ICM Layer 3, on-demand). [INFERENCE]

Procedure

1. Resolve the sub-capability; open the matching references/ playbook. [EXPLICIT]
2. Apply its decision tables; pick the strategy explicitly. [EXPLICIT]
3. Validate against the Quality Criteria and tag every claim. [EXPLICIT]

Quality Criteria

• Sub-capability resolved to one playbook. [INFERENCE]
• Claims evidence-tagged. [EXPLICIT]

Contract

• Aceptación: capability resolved to its reference playbook, applied, validated, evidence-tagged. [EXPLICIT]
• Límites: · Does not design application architecture · Does not implement monitoring and alerting systems · Does not address security aspects of CDN or caching · Load testing results depend. [EXPLICIT]
• Casos borde: Greenfield System: No baseline. Use industry benchmarks as initial targets. Design instrumentation from day one. Run synthetic load tests against staging before launch. [EXPLICIT]
• Supuestos: · System is instrumented or can be instrumented for metrics collection · Production-like test environment available or can be provisioned · Historical traffic data exists for deman. [SUPUESTO]
• Trade-off: Decision Enables Constrains When to Use --- --- --- --- Aggressive caching Low latency, reduced origin load Stale data risk, invalidation complexity Read-he. [EXPLICIT]

Packet

Capas del packet, cargables bajo demanda (disciplina ICM: una capa por vez, nunca todas juntas): references/ guías de profundidad (cargar UNA por etapa) · knowledge/ cuerpo de conocimiento · prompts/ prompts listos · examples/ salida de ejemplo · agents/ subagentes del packet · assets/ recursos estáticos.