# Performance Tests

**Task**: AZ-146_test_performance
**Name**: Performance Tests
**Description**: Implement E2E tests measuring detection latency, concurrent inference throughput, tiling overhead, and video processing frame rate
**Complexity**: 3 points
**Dependencies**: AZ-138_test_infrastructure
**Component**: Integration Tests
**Jira**: AZ-146
**Epic**: AZ-137

## Problem

Performance characteristics must be baselined and verified: single image latency, concurrent request handling with the 2-worker ThreadPoolExecutor, tiling overhead for large images, and video processing frame rate. These tests establish performance contracts.

## Outcome

- Single image latency profiled (p50, p95, p99) for warm engine
- Concurrent inference behavior validated (2-at-a-time processing confirmed)
- Large image tiling overhead measured and bounded
- Video processing frame rate baselined

## Scope

### Included
- NFT-PERF-01: Single image detection latency
- NFT-PERF-02: Concurrent inference throughput
- NFT-PERF-03: Large image tiling processing time
- NFT-PERF-04: Video processing frame rate

### Excluded
- GPU vs CPU comparative benchmarks
- Memory usage profiling
- Load testing beyond 4 concurrent requests

## Acceptance Criteria

**AC-1: Single image latency**
Given a warm engine
When 10 sequential POST /detect requests are sent with small-image
Then p95 latency < 5000ms for ONNX CPU or p95 < 1000ms for TensorRT GPU

**AC-2: Concurrent throughput**
Given a warm engine
When 2 concurrent POST /detect requests are sent
Then both complete without error
And 3 concurrent requests show queuing (total time > time for 2)

**AC-3: Tiling overhead**
Given a warm engine
When POST /detect is sent with large-image (4000x3000)
Then request completes within 120s
And processing time scales proportionally with tile count

**AC-4: Video frame rate**
Given a warm engine with SSE connected
When async detection processes test-video with frame_period=4
Then processing completes within 5x video duration (< 50s)
And frame processing rate is consistent (no stalls > 10s)

## Non-Functional Requirements

**Performance**
- Tests themselves should complete within defined bounds
- Results should be logged for trend analysis

## Integration Tests

| AC Ref | Initial Data/Conditions | What to Test | Expected Behavior | NFR References |
|--------|------------------------|-------------|-------------------|----------------|
| AC-1 | Engine warm | 10 sequential detections | p95 < 5000ms (CPU) | ~60s |
| AC-2 | Engine warm | 2 then 3 concurrent requests | Queuing observed at 3 | ~30s |
| AC-3 | Engine warm, large-image | Single large image detection | Completes < 120s | ~120s |
| AC-4 | Engine warm, SSE connected | Video detection | < 50s, consistent rate | ~120s |

## Constraints

- Pass criteria differ between CPU (ONNX) and GPU (TensorRT) profiles
- Concurrent request tests must account for connection overhead
- Video frame rate depends on hardware; test measures consistency, not absolute speed

## Risks & Mitigation

**Risk 1: CI hardware variability**
- *Risk*: Latency thresholds may fail on slower CI hardware
- *Mitigation*: Use generous thresholds; mark as performance benchmark tests that can be skipped in resource-constrained CI
