Performance Optimization Projects | Planning Guide
Plan performance optimization projects with baselines and profiling. Prioritize by impact vs effort and track latency percentiles with GitScrum.
9 min read
Performance work requires measurement, not guessing. GitScrum helps teams plan optimization efforts, track improvements, and make data-driven decisions.
Performance Strategy
Measurement First
PERFORMANCE BASELINE:
┌─────────────────────────────────────────────────────────────┐
│ │
│ BEFORE OPTIMIZATION, MEASURE: │
│ │
│ KEY METRICS: │
│ • Response time (p50, p95, p99) │
│ • Throughput (requests/second) │
│ • Error rate │
│ • Resource usage (CPU, memory) │
│ • Core Web Vitals (LCP, FID, CLS) │
│ │
│ ─────────────────────────────────────────────────────────── │
│ │
│ BASELINE TASK: │
│ ┌─────────────────────────────────────────────────────────┐│
│ │ PERF-001: Establish performance baseline ││
│ │ ││
│ │ CURRENT STATE: ││
│ │ ││
│ │ Endpoint: /api/search ││
│ │ p50: 450ms ││
│ │ p95: 1200ms ││
│ │ p99: 2500ms ││
│ │ Throughput: 50 req/sec ││
│ │ Error rate: 0.5% ││
│ │ ││
│ │ TARGET: ││
│ │ p50: < 200ms ││
│ │ p95: < 500ms ││
│ │ p99: < 1000ms ││
│ │ Throughput: > 200 req/sec ││
│ │ Error rate: < 0.1% ││
│ │ ││
│ │ GAP: ││
│ │ Need 2x latency improvement ││
│ │ Need 4x throughput improvement ││
│ └─────────────────────────────────────────────────────────┘│
│ │
│ RULE: No optimization without measurement │
│ "We think it's slow" is not enough │
└─────────────────────────────────────────────────────────────┘
Identifying Bottlenecks
PROFILING AND ANALYSIS:
┌─────────────────────────────────────────────────────────────┐
│ │
│ PROFILING TASK: │
│ ┌─────────────────────────────────────────────────────────┐│
│ │ PERF-002: Profile search endpoint ││
│ │ ││
│ │ METHODOLOGY: ││
│ │ • APM traces for request breakdown ││
│ │ • Database query analysis ││
│ │ • CPU profiling under load ││
│ │ • Memory profiling ││
│ │ ││
│ │ FINDINGS: ││
│ │ ││
│ │ Time breakdown (p50 = 450ms): ││
│ │ ││
│ │ Database query: ████████████████ 280ms (62%) ││
│ │ Serialization: ████████ 120ms (27%) ││
│ │ Network overhead: ██ 30ms (7%) ││
│ │ App logic: █ 20ms (4%) ││
│ │ ││
│ │ BOTTLENECKS IDENTIFIED: ││
│ │ 1. Missing index on search_terms table ││
│ │ 2. N+1 query in result hydration ││
│ │ 3. Serializing unused fields ││
│ │ ││
│ │ RECOMMENDED PRIORITY: ││
│ │ 1. Add missing index (high impact, low effort) ││
│ │ 2. Fix N+1 query (high impact, medium effort) ││
│ │ 3. Optimize serialization (medium impact) ││
│ └─────────────────────────────────────────────────────────┘│
└─────────────────────────────────────────────────────────────┘
Optimization Work
Performance Epic
PERFORMANCE IMPROVEMENT EPIC:
┌─────────────────────────────────────────────────────────────┐
│ │
│ EPIC STRUCTURE: │
│ ┌─────────────────────────────────────────────────────────┐│
│ │ PERF-010: Search Performance Optimization ││
│ │ ││
│ │ Goal: Improve search to meet SLA ││
│ │ Target: p95 < 500ms (currently 1200ms) ││
│ │ Timeline: Sprint 12-13 ││
│ │ ││
│ │ INVESTIGATION: ││
│ │ ├── PERF-001: Baseline measurement ││
│ │ └── PERF-002: Profiling and analysis ││
│ │ ││
│ │ DATABASE OPTIMIZATIONS: ││
│ │ ├── PERF-011: Add search_terms index ││
│ │ ├── PERF-012: Fix N+1 in result hydration ││
│ │ └── PERF-013: Query optimization ││
│ │ ││
│ │ APPLICATION OPTIMIZATIONS: ││
│ │ ├── PERF-014: Optimize serialization ││
│ │ ├── PERF-015: Add result caching ││
│ │ └── PERF-016: Pagination improvements ││
│ │ ││
│ │ INFRASTRUCTURE: ││
│ │ ├── PERF-017: Connection pooling ││
│ │ └── PERF-018: CDN for static assets ││
│ │ ││
│ │ VALIDATION: ││
│ │ ├── PERF-019: Load testing ││
│ │ └── PERF-020: Monitor production rollout ││
│ └─────────────────────────────────────────────────────────┘│
└─────────────────────────────────────────────────────────────┘
Optimization Task
OPTIMIZATION TASK STRUCTURE:
┌─────────────────────────────────────────────────────────────┐
│ │
│ PERFORMANCE TASK: │
│ ┌─────────────────────────────────────────────────────────┐│
│ │ PERF-011: Add search_terms index ││
│ │ ││
│ │ PROBLEM: ││
│ │ Full table scan on search_terms for each query ││
│ │ Current cost: 280ms average ││
│ │ ││
│ │ SOLUTION: ││
│ │ Add compound index: (term, created_at DESC) ││
│ │ ││
│ │ EXPECTED IMPACT: ││
│ │ Query time: 280ms → ~20ms ││
│ │ Overall p50: 450ms → ~190ms ││
│ │ ││
│ │ RISKS: ││
│ │ • Increased write time (minimal) ││
│ │ • Disk space for index (~500MB) ││
│ │ ││
│ │ VERIFICATION: ││
│ │ ☐ Run EXPLAIN ANALYZE before/after ││
│ │ ☐ Load test with new index ││
│ │ ☐ Monitor production after deploy ││
│ │ ││
│ │ MEASUREMENT: ││
│ │ Before: [baseline metrics] ││
│ │ After: [to be filled after deploy] ││
│ └─────────────────────────────────────────────────────────┘│
└─────────────────────────────────────────────────────────────┘
Prioritization
Impact vs Effort
OPTIMIZATION PRIORITIZATION:
┌─────────────────────────────────────────────────────────────┐
│ │
│ PRIORITIZATION MATRIX: │
│ │
│ HIGH IMPACT │
│ │ │
│ ┌───────────┼───────────┐ │
│ │ │ │ │
│ │ DO │ DO │ │
│ │ FIRST │ NEXT │ │
│ │ │ │ │
│ LOW ────┼───────────┼───────────┤──── HIGH │
│ EFFORT │ │ │ EFFORT │
│ │ MAYBE │ MAYBE │ │
│ │ │ LATER │ │
│ │ │ │ │
│ └───────────┼───────────┘ │
│ │ │
│ LOW IMPACT │
│ │
│ ─────────────────────────────────────────────────────────── │
│ │
│ PRIORITIZED LIST: │
│ │
│ PRIORITY TASK IMPACT EFFORT │
│ ──────── ──────────────────── ────── ────── │
│ 1 Add DB index -260ms 2 hours │
│ 2 Fix N+1 query -80ms 1 day │
│ 3 Add caching -50ms 2 days │
│ 4 Optimize serialization -40ms 3 days │
│ 5 Connection pooling -20ms 4 hours │
│ │
│ START WITH QUICK WINS │
│ Index and N+1 fix = 75% of the improvement │
└─────────────────────────────────────────────────────────────┘
Measuring Results
Before/After Tracking
PERFORMANCE TRACKING:
┌─────────────────────────────────────────────────────────────┐
│ │
│ OPTIMIZATION RESULTS: │
│ ┌─────────────────────────────────────────────────────────┐│
│ │ PERF-010: Search Optimization Results ││
│ │ ││
│ │ BEFORE AFTER CHANGE ││
│ │ ────────────────────────────────────────────── ││
│ │ p50 latency: 450ms 180ms -60% ✅ ││
│ │ p95 latency: 1200ms 420ms -65% ✅ ││
│ │ p99 latency: 2500ms 850ms -66% ✅ ││
│ │ Throughput: 50/s 220/s +340% ✅ ││
│ │ Error rate: 0.5% 0.08% -84% ✅ ││
│ │ ││
│ │ ALL TARGETS MET ✅ ││
│ │ ││
│ │ BREAKDOWN BY OPTIMIZATION: ││
│ │ ││
│ │ PERF-011 (Index): -260ms (58% of total) ││
│ │ PERF-012 (N+1 fix): -80ms (18% of total) ││
│ │ PERF-014 (Serialization): -40ms (9% of total) ││
│ │ PERF-015 (Caching): -50ms (11% of total) ││
│ │ Other improvements: -20ms (4% of total) ││
│ │ ───────────────────────────────────────────── ││
│ │ TOTAL IMPROVEMENT: -450ms ││
│ └─────────────────────────────────────────────────────────┘│
│ │
│ DOCUMENT FOR FUTURE REFERENCE │
│ What worked, what didn't, lessons learned │
└─────────────────────────────────────────────────────────────┘
Ongoing Monitoring
PERFORMANCE MONITORING:
┌─────────────────────────────────────────────────────────────┐
│ │
│ CONTINUOUS TRACKING: │
│ │
│ DASHBOARD METRICS: │
│ • Key endpoints response times │
│ • Throughput trends │
│ • Error rates │
│ • Resource utilization │
│ │
│ ALERTS: │
│ • p95 > 500ms for 5 minutes │
│ • Throughput drops > 20% │
│ • Error rate > 1% │
│ │
│ REGRESSION DETECTION: │
│ • Compare against baseline weekly │
│ • Flag significant degradations │
│ • Investigate before reaching alerts │
│ │
│ ─────────────────────────────────────────────────────────── │
│ │
│ RECURRING TASK: │
│ ┌─────────────────────────────────────────────────────────┐│
│ │ PERF-REC: Weekly Performance Review ││
│ │ ││
│ │ Frequency: Every Monday ││
│ │ Owner: @perf-lead ││
│ │ ││
│ │ CHECK: ││
│ │ ☐ Review dashboard trends ││
│ │ ☐ Compare to baselines ││
│ │ ☐ Investigate any regressions ││
│ │ ☐ Plan optimization work if needed ││
│ │ ☐ Update team on performance status ││
│ └─────────────────────────────────────────────────────────┘│
└─────────────────────────────────────────────────────────────┘
Balancing Performance
Allocation Strategy
PERFORMANCE WORK ALLOCATION:
┌─────────────────────────────────────────────────────────────┐
│ │
│ SUSTAINABLE APPROACH: │
│ │
│ REGULAR ALLOCATION: │
│ Reserve 10-20% of capacity for performance │
│ Consistent investment prevents debt accumulation │
│ │
│ SPRINT EXAMPLE: │
│ ┌─────────────────────────────────────────────────────────┐│
│ │ Sprint 14 (30 points total) ││
│ │ ││
│ │ Features: 24 points (80%) ││
│ │ Performance: 6 points (20%) ││
│ │ ││
│ │ Performance allocation: ││
│ │ • PERF-025: Profile checkout flow (2 pts) ││
│ │ • PERF-026: Image optimization (3 pts) ││
│ │ • PERF-027: Database query review (1 pt) ││
│ └─────────────────────────────────────────────────────────┘│
│ │
│ WHEN TO INCREASE: │
│ • SLA breaches │
│ • User complaints about speed │
│ • Scaling issues │
│ • Major launch coming │
│ │
│ TREAT PERFORMANCE AS A FEATURE: │
│ "Page loads in < 2 seconds" is a requirement │
│ Not optional, not "nice to have" │
└─────────────────────────────────────────────────────────────┘