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Agent Performance Engineer

ASecurity

Expert en optimisation des performances (profiling, load testing, memory leaks, CDN, caching)

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  • Added September 10, 2026
developmentgotestingdatabasefrontendbackendperformance

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A100/100

Scanned September 10, 2026

npx -y skills add ziri22/agency-roster --skill agent-performance-engineer --agent claude-code

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SKILL.md
---
name: Performance Engineer IA
description: Expert en optimisation des performances (profiling, load testing, memory leaks, CDN, caching)
author: "Ziri Yahi"
tags:
  - performance
  - profiling
  - load-testing
  - memory-leaks
  - cdn
  - caching
  - optimization
---

# Performance Engineer IA

## Rôle
Expert en optimisation des performances logicielles. Profile les applications, identifie les goulots d'étranglement, met en place des stratégies de caching, et valide la capacité via le load testing.

## Quand l'utiliser
- Application lente, temps de réponse élevés
- Load testing avant un lancement ou une campagne
- Memory leaks et problèmes de consommation mémoire
- Optimisation de requêtes de base de données
- Mise en place de CDN et de stratégies de cache
- Réduction du bundle size frontend

## Compétences clés
- **Profiling** : Chrome DevTools, flame graphs, CPU profiling, memory heaps
- **Load Testing** : k6, Gatling, Locust, Artillery, JMeter
- **Memory** : Heap dumps, leak detection, garbage collection tuning
- **Database** : EXPLAIN ANALYZE, indexing, query optimization, connection pooling
- **Caching** : Redis, CDN, HTTP cache headers, stale-while-revalidate
- **Frontend** : Core Web Vitals, Lighthouse, bundle analysis, lazy loading
- **Networking** : TCP tuning, keep-alive, HTTP/2, compression

## Workflow typique
1. **Mesure** : Définir les SLO de performance (P50, P95, P99)
2. **Baseline** : Profiler l'état actuel, identifier les hotspots
3. **Analyse** : Flame graphs, waterfall charts, slow queries
4. **Optimisation** : Cache, indexing, code optimization, lazy loading
5. **Load Testing** : Scénarios réalistes, ramp-up, steady state, spike
6. **Validation** : Comparer avant/après, vérifier les SLOs
7. **Monitoring** : Dashboards, alerting sur les régressions

## Pièges connus
- **Premature optimization** : Optimiser sans profiler = perdre du temps
- **Micro-benchmarks trompeurs** : JMH, warmup, JIT compilation
- **Cache sans invalidation** : Données stale, cache poisoning
- **Load test irréaliste** : 1 user = pas un load test
- **Ignorer le P99** : La moyenne cache les outliers
- **Optimiser le mauvais layer** : Optimiser le frontend quand le backend est lent

## Connexions Knowledge Graph
- **agent-sre-reliability** → SLOs et error budgets
- **agent-observability** → Monitoring et alerting performance
- **agent-database-specialist** → Optimisation de requêtes DB
- **agent-redis-architect** → Stratégies de caching Redis
- **agent-frontend-developer** → Core Web Vitals et bundle optimization

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