api-chaos-runner

Overview

Most API tests run against perfect networks: <1ms latency, no packet loss, infinite bandwidth, deterministic ordering. Real production isn't like that. Network chaos testing drives the existing tests under controlled network impairment - the team discovers which retry / circuit-breaker / timeout patterns actually hold up before real customers find out.

The canonical open-source primitive is Toxiproxy - Shopify's "TCP proxy to simulate network and system conditions for chaos and resiliency testing" (toxiproxy-readme). The pattern: sit Toxiproxy between client and upstream; manipulate toxics (latency, timeout, bandwidth, etc.) during test execution.

This skill is build-an-X - the workflow chains the team's existing API tests (Postman / Karate / RestAssured / Tavern / Schemathesis) through a Toxiproxy-managed connection and orchestrates a per-scenario chaos matrix.

When to use

• The API has documented resilience requirements (retry on 5xx, circuit-break on 3 consecutive failures, timeout at 5s, etc.) and the team needs to verify them, not just document them.
• A new external dependency just got added; the team wants to pressure-test fallback behavior.
• An incident postmortem identified a "we should have caught this in testing" item; chaos coverage is the prevention mechanism for that class.
• The team has integration tests already and wants to multiply their signal value via fault injection.

If the team is just starting API testing and has no resilience patterns to verify, this skill is overkill - start with happy-path coverage via postman-collections or the language-native equivalents first.

Step 1 - Pick the chaos primitive

Default recommendation: Toxiproxy for per-API chaos in CI. The others fit when the team is already in those ecosystems (Docker-Compose-heavy projects, Kubernetes-first projects).

Step 2 - Define the chaos matrix

For each existing API test scenario, define a matrix of conditions to run it under:

Per toxiproxy-readme, the canonical toxic types include latency, down (forced failure), bandwidth, slow_close, timeout, slicer, limit_data, reset_peer.

The matrix is the load-bearing artifact: what the team expects under each condition is what differentiates resilience verification from "did the test pass?" The Expected column drives the assertions.

Step 3 - Wire Toxiproxy into the test environment

Setup (Docker example)

# docker-compose.test.yml
services:
  toxiproxy:
    image: ghcr.io/shopify/toxiproxy:latest
    ports:
      - 8474:8474   # control API
      - 5432:5432   # proxied DB
      - 8080:8080   # proxied API
  app:
    build: .
    environment:
      DATABASE_URL: 'postgres://user:pass@toxiproxy:5432/db'
      EXTERNAL_API_URL: 'http://toxiproxy:8080'

Per toxiproxy-readme, the application points at Toxiproxy's listen ports rather than the upstream. Toxiproxy forwards to the real upstream when no toxic is active.

Define proxies via the control API

# Register the upstream
curl -d '{"name":"orders-api","listen":"0.0.0.0:8080","upstream":"orders-api-real:8080"}' \
  http://toxiproxy:8474/proxies

Add a toxic during a test

Per toxiproxy-readme:

# 1000ms latency on every request through this proxy
toxiproxy-cli toxic add -t latency -a latency=1000 orders-api

# Bandwidth cap at 10 KB/s
toxiproxy-cli toxic add -t bandwidth -a rate=10 orders-api

# Forced timeout
toxiproxy-cli toxic add -t timeout -a timeout=5000 orders-api

# Remove all toxics
toxiproxy-cli toxic remove orders-api -n <toxic-name>

For a stateless add-test-remove cycle, the language-native client libraries (toxiproxy-python, toxiproxy-node, toxiproxy-ruby, toxiproxy-go) wrap the HTTP API.

Step 4 - Run the matrix

A minimal runner shell script:

#!/usr/bin/env bash
# scripts/chaos-matrix.sh
set -e

PROXY=orders-api
TEST_CMD="npx newman run collections/orders.postman_collection.json -e environments/chaos.json -r cli,junit --reporter-junit-export results-$1.xml"

run_with_toxic() {
  local label="$1"; local type="$2"; local args="$3"
  echo "=== $label ==="
  toxiproxy-cli toxic remove "$PROXY" -n latency 2>/dev/null || true
  toxiproxy-cli toxic remove "$PROXY" -n bandwidth 2>/dev/null || true
  toxiproxy-cli toxic remove "$PROXY" -n timeout 2>/dev/null || true
  if [ -n "$type" ]; then
    toxiproxy-cli toxic add -t "$type" $args "$PROXY"
  fi
  $TEST_CMD "$label" || true   # don't bail; we want the matrix
}

run_with_toxic 'control'   ''        ''
run_with_toxic 'latency-1s' latency  '-a latency=1000'
run_with_toxic 'bandwidth' bandwidth '-a rate=10'
run_with_toxic 'timeout'   timeout   '-a timeout=5000'

The matrix produces one JUnit XML per scenario. Aggregate them in the report stage.

Step 5 - Report what broke under what

A successful chaos run produces a resilience matrix report:

## API Chaos Matrix — verdict: REVIEW

| Scenario         | Control | Latency 1s | Bandwidth 10k | Timeout 5s | Reset peer |
|------------------|:-------:|:----------:|:-------------:|:----------:|:----------:|
| POST /orders     |    ✅   |     ✅     |       ✅      |     ✅     |     ❌     |
| GET /orders/:id  |    ✅   |     ✅     |       ❌      |     ✅     |     ✅     |
| DELETE /orders/:id |  ✅   |     ✅     |       ✅      |     ✅     |     ✅     |

### Failures

| Test | Toxic       | Expected                                          | Actual |
|------|-------------|---------------------------------------------------|--------|
| POST /orders | reset_peer | 502 + retry attempted; second attempt succeeds | 502; no retry observed in client logs |
| GET /orders/:id | bandwidth=10k | 200 in <30s | 408 timeout at 10s |

A green matrix isn't the goal - finding where resilience is missing is the goal. A failure under a chaos scenario is a feature request, not a bug in the test.

Choosing what to inject

Match toxics to documented resilience requirements:

Run only the toxics that map to a documented expectation; running every toxic against every endpoint is noise.

Anti-patterns

Limitations

• Toxiproxy is TCP-level. UDP flaws (DNS resolver weirdness, QUIC) need different tooling.
• Doesn't model partial failures within a single connection. Toxiproxy treats each connection uniformly; for "retry on the 3rd request after 2 successes" patterns, layer a counting middleware.
• Per-test-suite isolation. When tests run in parallel against the same Toxiproxy instance, they fight over the same toxic state; serialize chaos scenarios or use one Toxiproxy instance per worker.

References

• toxiproxy - main repo: install, control API, toxic types, language-native clients.
• Pumba - https://github.com/alexei-led/pumba
• LitmusChaos - https://litmuschaos.io/
• Principles of Chaos Engineering - https://principlesofchaos.org/
• postman-collections, tavern-testing, karate-testing, restassured-testing - example-based test suites that this skill drives through chaos.