ai-agent/symphony-ai-agent/testing/Goal-2-Task-3/Goal-2-Task-3-test-plan.md

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# RBAC Performance Test Plan (Goal-2-Task-3)
## Test Objectives
- Validate RBAC performance under production-like load conditions
- Measure key metrics: role resolution latency, permission check throughput, concurrent session handling, memory usage
- Identify performance bottlenecks and scaling limits
## Test Environment
- **Infrastructure**: AWS EC2 instances (3x m5.xlarge workers, 1x m5.2xlarge load generator)
- **Monitoring**: Grafana dashboard with Prometheus metrics collection
- **Test Duration**: 60 minutes per test scenario
## Test Scenarios
### Scenario 1: Baseline Performance
- **Description**: Measure performance with single user session
- **Parameters**:
- Users: 1
- Role assignments: 5 roles per user
- Permission checks: 1000 sequential checks
- **Metrics**:
- Average role resolution latency
- Permission check throughput
- Memory usage baseline
### Scenario 2: Concurrent Users
- **Description**: Measure performance with increasing concurrent users
- **Parameters**:
- Users: 100 → 1000 → 5000 (ramp up over 10 minutes)
- Role assignments: 5 roles per user
- Permission checks: 100 checks per user
- **Metrics**:
- 95th percentile latency
- Throughput under load
- Memory usage growth
### Scenario 3: Complex Role Hierarchies
- **Description**: Measure impact of complex role structures
- **Parameters**:
- Users: 100
- Role assignments: 20 roles per user (nested hierarchy)
- Permission checks: 100 checks per user
- **Metrics**:
- Role resolution latency distribution
- CPU utilization
- Garbage collection impact
## Success Criteria
- P95 role resolution latency < 100ms at 1000 concurrent users
- Permission check throughput > 500 ops/sec at peak load
- Memory usage growth < 20% during test duration
## Execution Steps
1. Provision test environment using Terraform
2. Deploy RBAC service and monitoring
3. Execute test scenarios using load generator
4. Collect and analyze metrics
5. Generate performance report