Performance Test Plan Performance Test Plan Project: {{PROJECT_NAME}} Version: {{VERSION}} Date: {{DATE}} Author: {{AUTHOR}} Status: Draft | In Review | Approved Reviewers: {{REVIEWERS}} Document History Version Date Author Changes 0.1 {{DATE}} {{AUTHOR}} Initial draft 1. Performance Testing Objectives Validate that {{PROJECT_NAME}} meets the performance SLAs defined in the NFR document under normal operating conditions Determine the maximum capacity the system can handle before performance degrades Identify bottlenecks (database, application, infrastructure) before production release Establish a performance baseline for regression comparison in future releases Reference NFRs: {{NFR_DOC_LINK}} 2. Performance Requirements Reference Endpoint / Feature P50 P90 P95 P99 Error Rate Throughput GET / (homepage) < {{P50}}ms < {{P90}}ms < {{P95}}ms < {{P99}}ms < {{ERR}}% {{RPS}} req/s POST /api/auth/login < {{P50}}ms < {{P90}}ms < {{P95}}ms < {{P99}}ms < {{ERR}}% {{RPS}} req/s GET /api/{{RESOURCE}} < {{P50}}ms < {{P90}}ms < {{P95}}ms < {{P99}}ms < {{ERR}}% {{RPS}} req/s POST /api/{{RESOURCE}} < {{P50}}ms < {{P90}}ms < {{P95}}ms < {{P99}}ms < {{ERR}}% {{RPS}} req/s Database query (P95) < {{DB_P95}}ms Page load (First Contentful Paint) < {{FCP}}ms 3. Test Types 3.1 Load Testing — Normal Load Simulation Objective: Confirm the system meets SLAs under expected normal load Normal load definition: {{NORMAL_USERS}} concurrent users / {{NORMAL_RPS}} requests/second Duration: {{LOAD_DURATION}} minutes (after ramp-up) Pass criteria: All SLA targets in Section 2 met with ≤ {{LOAD_ERROR_RATE}}% error rate 3.2 Stress Testing — Beyond Normal Capacity Objective: Find the maximum capacity and understand failure behavior Starting point: {{STRESS_START_USERS}} users, increasing by {{STRESS_INCREMENT}} users every {{STRESS_STEP}}min Stop condition: Error rate > {{STRESS_STOP_ERROR}}% or service crashes Pass criteria: System fails gracefully (circuit breakers, meaningful error messages), data integrity maintained 3.3 Spike Testing — Sudden Traffic Surges Objective: Verify system handles sudden traffic spikes without crashing Baseline: {{SPIKE_BASELINE}} users Spike to: {{SPIKE_PEAK}} users ({{SPIKE_MULTIPLIER}}× baseline) Spike duration: {{SPIKE_DURATION}} minutes Pass criteria: System recovers to baseline performance within {{SPIKE_RECOVERY}} minutes after spike ends 3.4 Endurance / Soak Testing — Sustained Load Objective: Identify resource leaks and degradation under sustained load Load level: {{SOAK_USERS}} users ({{SOAK_PERCENT}}% of normal load) Duration: {{SOAK_DURATION}} hours Metrics to watch: Memory usage trend, response time trend, disk space, database connection pool Pass criteria: No upward trend in memory/response time over the soak period 3.5 Scalability Testing — Increasing Load Objective: Verify linear (or better) scaling as infrastructure grows Test: Step load from {{SCALE_START}} to {{SCALE_MAX}} users while scaling from {{MIN_INSTANCES}} to {{MAX_INSTANCES}} instances Pass criteria: Throughput increases proportionally (≥ {{SCALE_EFFICIENCY}}% efficiency) with added instances 4. Load Profiles Scenario Virtual Users Ramp-Up Hold Ramp-Down Think Time Iterations Smoke (quick sanity) {{SMOKE_VU}} {{SMOKE_RAMP}}s {{SMOKE_HOLD}}min 30s 1s 1 Load (normal) {{LOAD_VU}} {{LOAD_RAMP}}min {{LOAD_HOLD}}min 5min {{THINK}}s — Stress {{STRESS_VU}} (increasing) {{STRESS_RAMP}}min Until failure — {{THINK}}s — Spike {{SPIKE_VU}} (instant) 0s {{SPIKE_HOLD}}min 0s {{THINK}}s — Soak {{SOAK_VU}} {{SOAK_RAMP}}min {{SOAK_HOLD}}h 10min {{THINK}}s — Think time simulation: Random between {{THINK_MIN}}s and {{THINK_MAX}}s (realistic user behavior) 5. Test Environment CRITICAL: Performance tests run on a dedicated environment with the same infrastructure sizing as production. Component Test Environment Production App instances {{TEST_APP_INSTANCES}} × {{TEST_INSTANCE_TYPE}} {{PROD_APP_INSTANCES}} × {{PROD_INSTANCE_TYPE}} Database {{TEST_DB_SPEC}} {{PROD_DB_SPEC}} Cache {{TEST_CACHE_SPEC}} {{PROD_CACHE_SPEC}} CDN Disabled (direct hit) Enabled Load generator infrastructure: Tool: {{PERF_TOOL}} Load generator location: {{LG_LOCATION}} (same region as app, separate VPC) Load generator sizing: {{LG_SPEC}} 6. Test Data Requirements Data Type Volume Generation Method Users {{USER_COUNT}} Script + factory {{DATA_TYPE_1}} {{VOLUME}} Bulk import script {{DATA_TYPE_2}} {{VOLUME}} Bulk import script Search index Production-sized Seeded from anonymized production data Database size at test time: {{DB_SIZE}}GB Data preparation: bash scripts/perf-seed.sh (estimated time: {{SEED_TIME}}min) 7. Tools & Infrastructure Tool Version Purpose Config {{PERF_TOOL}} {{VERSION}} Load generation perf-tests/ {{MONITOR_TOOL}} {{VERSION}} Real-time metrics during test Dashboard link {{APM_TOOL}} {{VERSION}} Application performance profiling Dashboard link {{DB_MONITOR}} {{VERSION}} Database query analysis Dashboard link Script location: {{PERF_SCRIPT_PATH}} 8. Key Metrics to Capture Response Time Metric Description Tool P50 (median) Half of requests faster than this {{TOOL}} P90 90% of requests faster than this {{TOOL}} P95 95% of requests faster than this {{TOOL}} P99 99% of requests faster than this {{TOOL}} Max Worst single request {{TOOL}} Throughput Metric Description Requests/second Total throughput at peak load Transactions/second Successful business transactions/second Data transferred Total MB/s in + out Error Metrics Metric Target HTTP error rate (5xx) < {{HTTP_ERR}}% Timeout rate < {{TIMEOUT_ERR}}% Connection refused rate 0% Resource Utilization Resource Warning Critical App CPU > {{CPU_WARN}}% > {{CPU_CRIT}}% App Memory > {{MEM_WARN}}% > {{MEM_CRIT}}% DB CPU > {{DB_CPU_WARN}}% > {{DB_CPU_CRIT}}% DB Connections > {{DB_CONN_WARN}}% of pool > {{DB_CONN_CRIT}}% Cache hit ratio < {{CACHE_HIT}}% < {{CACHE_CRIT}}% Database Query Performance Metric Target Average query time < {{AVG_QUERY}}ms Slow queries (> {{SLOW_THRESHOLD}}ms) < {{SLOW_COUNT}} per minute Deadlocks 0 9. SLA Targets Per Endpoint Endpoint Method P95 SLA Error Rate SLA Notes / GET {{P95}}ms < {{ERR}}% Static or cached /api/auth/login POST {{P95}}ms < {{ERR}}% Auth critical path /api/{{RESOURCE}} GET {{P95}}ms < {{ERR}}% {{NOTE}} /api/{{RESOURCE}} POST {{P95}}ms < {{ERR}}% {{NOTE}} 10. Baseline Establishment Baseline criteria: System in stable state, seeded with production-realistic data, running load test scenario for {{BASELINE_DURATION}} minutes Baseline metrics to record: Metric Baseline Value Date Recorded P95 latency (key endpoints) TBD {{DATE}} Throughput at normal load TBD {{DATE}} Error rate at normal load TBD {{DATE}} CPU utilization at normal load TBD {{DATE}} Memory utilization at normal load TBD {{DATE}} Regression threshold: Alert if any metric degrades > {{REGRESSION_THRESHOLD}}% vs baseline 11. Test Execution Schedule Run Type Trigger Environment Frequency Smoke Every deployment Staging Per deploy Load (baseline) Release candidate Production-sized Per release Stress Major feature releases Production-sized Quarterly Soak Before major releases Production-sized Per release Scalability Infrastructure changes Production-sized As needed 12. Results Analysis Template Test Run ID: {{RUN_ID}} Date: {{DATE}} Tester: {{TESTER}} Scenario: {{SCENARIO}} Build / Version: {{VERSION}} Endpoint P50 (ms) P90 (ms) P95 (ms) P99 (ms) Error % RPS Status vs SLA {{ENDPOINT}} — — — — — — ✅ Pass / ❌ Fail Summary: Peak concurrent users: {{PEAK_USERS}} Peak throughput: {{PEAK_RPS}} req/s Test duration: {{DURATION}} min Total requests: {{TOTAL_REQUESTS}} Total errors: {{TOTAL_ERRORS}} Notable findings: {{FINDING_1}} {{FINDING_2}} Comparison to baseline: {{COMPARISON}} Recommendation: Pass / Fail / Conditional pass with {{CONDITIONS}} 13. Bottleneck Identification Process 1. Check application error rate → Is the app returning errors, or just slow? 2. Check P99 vs P50 spread → Large spread = outlier requests (DB queries, locks, GC pauses) 3. Check CPU saturation → CPU > 80% sustained = compute bottleneck 4. Check memory → Memory growing during test = leak / GC pressure 5. Check DB metrics → Slow queries, high connections, deadlocks 6. Check cache hit rate → Low cache hit = DB overloaded unnecessarily 7. Check external calls → Third-party API latency or rate limiting 8. Check network → Bandwidth saturation, packet loss 14. Remediation Tracking Issue Found In Severity Root Cause Fix Fixed In Verified {{ISSUE}} {{SCENARIO}} {{SEVERITY}} {{CAUSE}} {{FIX}} {{VERSION}} {{DATE}} Related Documents Test Strategy Monitoring & Observability SLA Report Approval Role Name Date Signature Author Reviewer Approver