Integration Tests workflow (hyperledger-cello/cello)
The Integration Tests workflow from hyperledger-cello/cello, explained and optimized by Latchkey.
CI health: C - fair
Point runs-on at Latchkey and get run de-duplication, job timeouts, self-healing for flaky steps, and up to 58% lower cost, applied automatically.
What it does
This is the Integration Tests workflow from the hyperledger-cello/cello repository, a real project running GitHub Actions. It is shown here with attribution under its Apache-2.0 license.
Below, Latchkey shows a faster, safer version produced by its optimization engine.
The workflow
name: Integration Tests
on:
push:
branches: ["main"]
pull_request:
branches: ["main"]
jobs:
build:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Start Dashboard, DB, and API Engine
run: docker compose -f docker-compose.dev.yaml up -d --build
- name: Start Hyperledger Fabric Agent
working-directory: src/agents/hyperledger-fabric
run: |
docker build -t cello-hyperledger-fabric-agent .
docker run -d --network cello-net -v /var/run/docker.sock:/var/run/docker.sock --name cello-hyperledger-fabric-agent cello-hyperledger-fabric-agent
- name: Build Hyperledger Fabric Node
working-directory: src/nodes/hyperledger-fabric
run: docker build -t hyperledger/fabric:2.5.15 .
- name: Run newman tests
working-directory: tests/postman
run: docker compose up --abort-on-container-exit
- name: Stop Hyperledger Fabric Chaincode
run: docker ps -q --filter "name=dev-peer0.org1.foo.com-basic_1.0" | xargs -r docker stop
- name: Stop Hyperledger Fabric Nodes
run: docker stop orderer0.foo.com peer0.org1.foo.com
- name: Stop Hyperledger Fabric Agent
run: docker stop cello-hyperledger-fabric-agent
- name: Stop Dashboard, DB, and API Engine
run: docker compose -f docker-compose.dev.yaml down -v
- name: Clean up
if: always()
run: docker system prune -a -f
The same workflow, on Latchkey
Removes redundant runs and caps runaway jobs. Added and changed lines are highlighted.
name: Integration Tests on: push: branches: ["main"] pull_request: branches: ["main"] concurrency: group: ${{ github.workflow }}-${{ github.ref }} cancel-in-progress: true jobs: build: timeout-minutes: 30 runs-on: latchkey-small steps: - uses: actions/checkout@v3 - name: Start Dashboard, DB, and API Engine run: docker compose -f docker-compose.dev.yaml up -d --build - name: Start Hyperledger Fabric Agent working-directory: src/agents/hyperledger-fabric run: | docker build -t cello-hyperledger-fabric-agent . docker run -d --network cello-net -v /var/run/docker.sock:/var/run/docker.sock --name cello-hyperledger-fabric-agent cello-hyperledger-fabric-agent - name: Build Hyperledger Fabric Node working-directory: src/nodes/hyperledger-fabric run: docker build -t hyperledger/fabric:2.5.15 . - name: Run newman tests working-directory: tests/postman run: docker compose up --abort-on-container-exit - name: Stop Hyperledger Fabric Chaincode run: docker ps -q --filter "name=dev-peer0.org1.foo.com-basic_1.0" | xargs -r docker stop - name: Stop Hyperledger Fabric Nodes run: docker stop orderer0.foo.com peer0.org1.foo.com - name: Stop Hyperledger Fabric Agent run: docker stop cello-hyperledger-fabric-agent - name: Stop Dashboard, DB, and API Engine run: docker compose -f docker-compose.dev.yaml down -v - name: Clean up if: always() run: docker system prune -a -f
What changed
- Run on Latchkey managed runners with one line (
runs-on), which apply the fixes below automatically and self-heal transient failures. This example useslatchkey-small; pick the runner size that fits the job. - Cancel superseded runs when a branch or PR gets a newer push.
- Add a job timeout so a hung step cannot burn hours of runner time.
What Latchkey heals here
This workflow has steps that commonly fail on transient issues (network, registries, flaky browsers). On Latchkey managed runners they are detected, retried, and self-healed instead of failing your build:
- Container pulls and builds
This workflow runs 1 job per trigger. On Latchkey the same minutes cost up to 58% less than GitHub-hosted, with zero queue time.