jac-loadtest 0.2.1

HAR-based load testing CLI for jac-scale applications

jac-loadtest

HAR-based load testing CLI for jac-scale applications. Capture real browser traffic via Chrome DevTools, export it as a .har file, and replay it under load — no scripting required.

The tool registers itself as a jac subcommand, so after installation you run jac loadtest alongside jac start, jac deploy, and the rest of the jac ecosystem.

Testing Modes

Monolith mode (default) — all requests go through a single --url. Use this for production-realistic load testing: it measures what users actually experience end-to-end through the gateway.

Microservice mode — route requests directly to individual service processes by URL path prefix. Use this locally or inside your cluster to isolate per-service latency and identify which service is the bottleneck — without gateway overhead masking the signal.

# Monolith: all traffic through the gateway (default, production-realistic)
jac loadtest recording.har --url http://localhost:8000 --vus 10 --duration 30s

# Microservice: bypass gateway, route by path prefix to individual services
jac loadtest recording.har --mode microservice \
  --url http://localhost:8000 \
  --services-map '{"order_service":"http://localhost:18001","inventory_service":"http://localhost:18002"}' \
  --vus 10 --duration 30s

Note: Microservice mode requires direct network access to service ports. This means it's only usable locally (jac serve) or from inside a Kubernetes cluster — not from outside production. For remote or production load testing, use monolith mode.

Quick Start

# Minimal: 1 VU, 30s
jac loadtest recording.har --url http://localhost:8000

# 50 VUs with 10s ramp-up
jac loadtest recording.har --url http://localhost:8000 --vus 50 --ramp-up 10s --duration 60s

# Authenticated test with per-VU credentials
jac loadtest recording.har --url http://localhost:8000 --vus 20 --credentials-file creds.csv

# CI-friendly with thresholds
jac loadtest recording.har --url http://localhost:8000 \
  --vus 10 --duration 30s --fail-on-p95 500 --fail-on-error-rate 1

Developer Setup

# 1. Create and activate a conda env (Python 3.12 required)
conda create -n load python=3.12
conda activate load

# 2. Install the package in editable mode (runtime deps only)
pip install -e .

# 3. Also install test dependencies (when running tests)
pip install -e ".[test]"

# 4. Verify the command is registered
jac loadtest --help

Project Layout

jac_loadtest/
├── plugin.py      — registers `jac loadtest` via jaclang entry-points
├── cli.py         — argument wiring; JacMetaImporter bootstrap
├── config.py      — LoadTestConfig dataclass (three-layer resolution)
├── core/          — HAR parser, load engine, metrics (no jac-scale knowledge)
├── bridge/        — jac-scale-aware adapters (auth, topology)
└── output/        — console, JSON, HTML reporters

The hard boundary between core/ and bridge/ is what keeps the eventual migration to jac-scale[loadtest] a file move rather than a rewrite.

HAR Compatibility

Tested with HAR 1.1 and 1.2 (the format exported by Chrome DevTools, Firefox, Postman, and Insomnia). Files from other versions are parsed with a warning — open an issue if something breaks.

Documentation

• Architecture — module map, data flow, design decisions
• Roadmap — delivery phases and exit criteria
• Verification — phase-by-phase manual and automated verification checklists