Run Docker Compose on a Linux GitHub Actions runner, wait on declared service health, execute the test command, collect logs if anything fails, and tear the stack down in an always-running cleanup step. The pattern is repeatable because the Compose file defines the same multi-container stack used by the workflow.
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The important choices are where the job runs, how containers are addressed, how readiness is expressed, and whether test data should survive the job. The sections below show a complete workflow and the decisions behind each step.
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What Docker Compose contributes to a GitHub Actions job
Docker Compose defines and runs a multi-container application from one Compose file. Docker documents Compose for production, staging, development, testing, and continuous-integration workflows, so a CI job can use the same service definition instead of maintaining a second, hand-written collection of container commands.
A normal workflow has five phases:
- Check out the repository.
- Start the Compose project and build any local images.
- Wait until the services meet their readiness checks.
- Run tests or another one-off command.
- Print diagnostics on failure and remove the stack.
The test service, image names, ports, and test command are project-specific. Compose supplies the orchestration; your repository still has to describe what “ready” means for each dependency.
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Runner requirements and job placement
GitHub requires a Linux runner for workflows that use Docker container actions, job containers, or service containers. GitHub-hosted jobs should use an Ubuntu runner. A self-hosted runner must be Linux and have Docker installed and usable by the runner account.
The placement of the job determines how applications reach services. Decide this before writing connection strings.
| Job placement | How services are addressed | When it fits | Operational detail |
|---|---|---|---|
| Runner machine | Map Compose ports and use localhost:port or 127.0.0.1:port. |
The workflow needs host shell tools, direct Docker commands, or simple host-level access. | Use an Ubuntu GitHub-hosted runner or a Linux self-hosted runner with Docker. |
| Container job | GitHub connects the job and its service containers to a user-defined bridge network; a configured service label becomes the hostname, such as redis. |
The tests should run in a fully containerized environment and use label-based service discovery. | Keep application configuration aligned with the hostnames supplied by the job network. Running a Compose stack inside a job container also requires deliberate access to a Docker daemon; it is not created automatically merely by adding container:. |
Most Compose-based workflows start on the runner machine because the Docker CLI and daemon are available directly. A container job is useful when the test process itself must be isolated and the network model is understood. Do not mix the two addressing schemes: a hostname that works for a service container is not automatically the same as a host-mapped port.
A complete Compose workflow
This example follows the dependable CI sequence. It checks the installed Compose plugin, starts the stack, runs a one-off test container, saves status and logs if a previous step failed, and always removes the stack.
name: CI
on:
push:
pull_request:
jobs:
test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Check Docker Compose
run: docker compose version
- name: Start services
run: docker compose up --build --wait
- name: Run tests
run: docker compose run --rm web pytest
- name: Show status and logs on failure
if: failure()
run: |
docker compose ps
docker compose logs --no-color
- name: Tear down
if: always()
run: docker compose downdocker compose up builds images when requested, creates or recreates containers, starts services, and normally attaches to them. The --build option ensures a local application image is rebuilt from the checked-out revision. The --wait option tells Compose to wait for service readiness; pair it with --wait-timeout when a project needs an explicit upper bound.
The command uses the service name web only as an example. Replace it with the service that contains your test dependencies and use that service’s actual test command. The workflow does not assume that the test process should be the long-running application container.
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Prepare the Compose file for CI
Define every dependency in one place
Put the application, database, cache, queue, and any other required dependency in the Compose project used by the job. A repeatable file prevents the workflow from silently depending on software installed on the runner. Keep development-only tools out of the startup path unless the tests require them.
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Express readiness with healthchecks
A container being started is not the same as an application being ready. Add a Compose healthcheck that exercises the service’s native readiness command, then make dependent services wait for the healthy state where your Compose configuration supports that relationship. For example, a Redis-backed application can use the Redis client’s ping command as the health probe:
services:
redis:
image: redis
healthcheck:
test: ['CMD-SHELL', 'redis-cli ping']
interval: 5s
timeout: 3s
retries: 20
web:
build: .
depends_on:
redis:
condition: service_healthyThe exact probe must match the image and the readiness condition that matters to the application. A process-level check can pass while migrations, schema loading, or an HTTP endpoint is still unavailable, so prefer an application-level check when one exists.
Choose ports intentionally
Map only the ports that a process outside the Compose network must use. Containers in the same Compose project can normally communicate over the project network by service name; the host needs a published port when a runner-shell command or an external tool must connect through localhost. Fewer published ports reduce collisions and make the workflow easier to reason about.
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A dedicated test service or the application service’s image can run the test command. Separating that one-off command from the long-running stack lets the workflow remove the test container with --rm while leaving dependencies available for the duration of the test.
Start and wait for services correctly
Use Compose’s wait mechanism first
docker compose up --build --wait is preferable to a fixed sleep. Compose can use the healthchecks in the file and wait for the project to reach the declared state. If startup can legitimately take longer in CI, increase the value supplied to --wait-timeout rather than adding an arbitrary delay.
- name: Start services with an explicit limit
run: docker compose up --build --wait --wait-timeout 180There is no universal readiness delay. A database that initializes an empty data directory, an image that performs migrations, and a service that waits for another dependency all have different startup times. The healthcheck and the timeout should reflect the project’s actual behavior.
Use polling only when a healthcheck cannot express the condition
Some readiness conditions involve a separate command, a generated file, or an application-level API that is awkward to encode in Compose. In that case, run a bounded polling command after startup and fail with a useful message when the condition is not met. Keep the poll bounded; an infinite loop hides a broken service and consumes the entire job timeout.
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Understand attached and detached behavior
Compose can leave services running in detached mode while the workflow executes later steps. The important property for CI is that the start step returns only after the required readiness condition is met, not merely after containers have been created. If you choose a different up invocation, verify that it leaves the dependencies available to the test step.
Run tests, migrations, and administrative commands
Use docker compose run --rm for one-off work
docker compose run --rm web pytest creates a temporary container for the selected service, runs the command, and removes that container when it exits. The same pattern works for migrations, fixtures, linters, or an administrative check.
Compose does not create the service’s declared published ports for a normal run invocation. This behavior avoids accidental port collisions in CI. If the one-off process must accept incoming connections on those ports, request them explicitly with the service-port option supported by your Compose version; otherwise, keep the default isolation.
- name: Apply migrations
run: docker compose run --rm web python manage.py migrate
- name: Run the test suite
run: docker compose run --rm web pytestUse --exit-code-from when a test service controls the result
When the test itself is modeled as a Compose service, docker compose up --exit-code-from tests can make that service’s exit code become the command’s exit status. This is useful when the test container starts alongside dependencies and the workflow should finish with the test service’s result. Keep the service name in the option synchronized with the Compose file.
Choose one clear test model per job: a one-off run --rm command after the stack is ready, or an up command whose selected test service determines success. Mixing both can run the suite twice or obscure which process produced the failure.
Connect to databases, caches, and other services
Tests launched by Compose
A test container launched with docker compose run joins the Compose project network. Configure the application to use the dependency’s service name as its host, not localhost. Inside a container, localhost refers to that same test container.
For example, if the Compose service is named redis, the test configuration should use redis as the host and the container port exposed by the Redis service. The exact port and credentials belong in the project’s Compose configuration.
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Commands executed on the runner
A shell command running directly on the Ubuntu runner is outside the Compose network. Publish the required service port and connect to localhost: or 127.0.0.1:. This is the correct model for a host-installed test tool or a diagnostic command that is not containerized.
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Container jobs and GitHub service containers
In a container job that uses GitHub service containers, the service label is the hostname on the user-defined bridge network. A service labeled redis is therefore reachable as redis from the job container, without using a host-mapped port. Keep this configuration separate from a runner-machine job, where the same dependency would normally be reached through a published localhost port.
Capture useful diagnostics before cleanup
When startup or tests fail, collect the state of the project before removing it. The sequence in the example workflow uses:
docker compose psto show each service’s state.docker compose logs --no-colorto emit readable logs in the Actions transcript.
Put the diagnostic step behind if: failure() so it runs after a failed earlier step. Keep teardown behind if: always(); otherwise a failed test can leave containers running until the runner is recycled. If a service exits immediately, its logs often reveal a missing environment variable, an invalid configuration, a failed migration, or a dependency that never became healthy.
For a failure that occurs during the start command, the diagnostic step should still run. For a failure in the test command, it should show both the dependency state and the application output. Avoid tearing down first: docker compose down removes the containers and their writable-layer data, which can erase the evidence you needed.
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Use down for isolated CI runs
docker compose down removes the project’s containers and writable-layer data. It is the normal choice when every job should start from a clean stack and no state needs to survive the run.
Use stop when you intentionally want stopped containers retained
docker compose stop stops services but preserves the stopped containers. That can be useful for interactive debugging on a persistent self-hosted machine, but it is usually the wrong default for an ephemeral CI run because old containers can affect later jobs.
Persist data explicitly
If a workflow genuinely needs data after the containers are removed, use a Compose volume or an external service designed for persistence. Do not rely on a container’s writable layer: the cleanup step is deliberately designed to remove it.
Build images locally or pull them from a registry
| Image strategy | Workflow command | Advantages | Trade-offs |
|---|---|---|---|
| Build from the checked-out source | docker compose up --build --wait |
Tests the exact revision in the repository and does not require a separately published application image. | Each run spends time building and can fail on a Dockerfile or dependency change. |
| Pull a published image | Use an image reference in the Compose file, then start with docker compose up --wait. |
Shortens startup when the image is already built and gives the workflow a fixed artifact. | The image must be available to the runner, and the workflow can test a published artifact rather than the source currently checked out. |
Choose the strategy that matches the question the job is answering. A pull-based job validates an artifact; a build-based job validates that the current source can produce and run the application.
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| Question | Prefer a runner-machine job when… | Prefer a container job when… |
|---|---|---|
| Where should tests execute? | Existing shell tools or host-level Docker commands are part of the test process. | The test process should share a controlled container environment. |
| How will the database be addressed? | The test command runs on the host and can use a published localhost port. | The job uses GitHub service containers and can use the service label as a hostname. |
| What is the main isolation boundary? | Compose containers isolate dependencies while the runner hosts the test command. | The job, test process, and service containers are all part of the containerized job setup. |
| What must be checked first? | Docker is installed, the Compose plugin is available, and required ports are free. | The Linux runner, job image, service labels, and Docker access needed by any Compose command are all configured. |
The safest implementation is the one whose network addresses appear exactly once in configuration and mean the same thing at runtime. Changing from a runner job to a container job without changing connection strings is a common source of “connection refused” and “host not found” errors.
Troubleshoot common failures
The workflow cannot find docker compose
- Run
docker compose versionearly so the failure is explicit. - Use a Linux runner as required for Docker container, job, and service-container workflows.
- On a self-hosted runner, verify that Docker and the Compose plugin are installed for the account executing Actions.
The test starts before the database or cache is ready
- Add or correct the dependency’s healthcheck.
- Use
docker compose up --waitand set a project-appropriate--wait-timeout. - Inspect
docker compose psanddocker compose logs --no-colorbefore teardown.
The test reports “connection refused”
- If the test runs in a Compose container, use the dependency’s service name and container port.
- If the test runs on the runner, publish the port and use
localhostor127.0.0.1. - If the test uses
docker compose run, remember that declared service ports are not created unless you request service-port behavior.
Logs disappear after a failure
Move diagnostics before teardown and guard the log step with if: failure(). Keep the cleanup step guarded by if: always() so a failed test does not leave resources behind.
The job passes even though the test service failed
Make the test command the step’s foreground process, or use --exit-code-from with the selected test service. A workflow that only checks whether dependency containers started can report success without executing a successful test suite.
A later job sees stale data or containers
Use docker compose down for isolation and avoid retaining stopped containers with docker compose stop unless the runner is intentionally used for debugging. Persist only the data that must survive, through a volume or an external service.
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- The job runs on Ubuntu or another supported Linux runner.
- The runner has Docker and the Compose plugin available.
- The repository is checked out before Compose builds local images.
- Every required dependency is represented in the Compose project.
- Healthchecks describe application readiness rather than relying on a fixed sleep.
docker compose up --build --wait(and, where needed,--wait-timeout) starts the stack.- The test command runs through
docker compose run --rmor a clearly selected--exit-code-fromservice. - Containerized tests use service-name hostnames; runner-shell tests use mapped localhost ports.
- Failure diagnostics print
docker compose psand color-free logs before removal. - Teardown runs with
if: always()and usesdownunless retained containers are deliberate. - Any data that must persist is stored in a volume or external service, not a writable container layer.
Putting the pattern into practice
Start with the smallest workflow that proves the stack can boot: checkout, Compose version check, up --build --wait, and cleanup. Add the test command only after the readiness check is meaningful. Then add failure logs, migrations, or a separate test service as the project requires.
When a failure occurs, classify it before changing commands: an image-build failure belongs in the Dockerfile or dependency definition; a readiness failure belongs in the healthcheck or timeout; a connection failure belongs in the job’s network addressing; a test failure belongs in the test process; and a cleanup failure belongs in runner permissions or retained resources. That separation keeps the workflow deterministic instead of masking one problem with a longer sleep or an abandoned container.
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