== Running CI tasks locally Since Concourse is built on top of Docker, it's easy to: * Debug what went wrong on your local machine. * Test out a a tweak to your `test.sh` script before sending it out. * Experiment against a new image before submitting your pull request. All of these use cases are great reasons to essentially run what Concourse does on your local machine. IMPORTANT: To do this you must have Docker installed on your machine. 1. `docker run -it --mount type=bind,source="$(pwd)",target=/spring-data-mongodb-github springci/spring-data-openjdk17-with-mongodb-5.0.3 /bin/bash` + This will launch the Docker image and mount your source code at `spring-data-mongodb-github`. + Next, run the `test.sh` script from inside the container: + 2. `PROFILE=none spring-data-mongodb-github/ci/test.sh` Since the container is binding to your source, you can make edits from your IDE and continue to run build jobs. If you need to test the `build.sh` script, do this: 1. `mkdir /tmp/spring-data-mongodb-artifactory` 2. `docker run -it --mount type=bind,source="$(pwd)",target=/spring-data-mongodb-github --mount type=bind,source="/tmp/spring-data-mongodb-artifactory",target=/spring-data-mongodb-artifactory springci/spring-data-openjdk17-with-mongodb-5.0.3 /bin/bash` + This will launch the Docker image and mount your source code at `spring-data-mongodb-github` and the temporary artifactory output directory at `spring-data-mongodb-artifactory`. + Next, run the `build.sh` script from inside the container: + 3. `spring-data-mongodb-github/ci/build.sh` IMPORTANT: `build.sh` doesn't actually push to Artifactory so don't worry about accidentally deploying anything. It just deploys to a local folder. That way, the `artifactory-resource` later in the pipeline can pick up these artifacts and deliver them to artifactory. NOTE: Docker containers can eat up disk space fast! From time to time, run `docker system prune` to clean out old images.