= Continuous Integration

image:https://jenkins.spring.io/buildStatus/icon?job=spring-data-jdbc%2Fmain&subject=Moore%20(main)["Spring Data JDBC", link="https://jenkins.spring.io/view/SpringData/job/spring-data-jdbc/"]
image:https://jenkins.spring.io/buildStatus/icon?job=spring-data-jdbc%2F1.0.x&subject=Lovelace%20(1.0.x)["Spring Data JDBC", link="https://jenkins.spring.io/view/SpringData/job/spring-data-jdbc/"]

== Running CI tasks locally

Since this pipeline is purely Docker-based, it's easy to:

* Debug what went wrong on your local machine.
* Test out 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 the CI server 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-jdbc-github  -v /usr/bin/docker:/usr/bin/docker -v /var/run/docker.sock:/var/run/docker.sock adoptopenjdk/openjdk8:latest /bin/bash`
+
This will launch the Docker image and mount your source code at `spring-data-jdbc-github`.
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2. `cd spring-data-jdbc-github`
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Next, test everything from inside the container:
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3. `./mvnw -Pci,all-dbs clean dependency:list test -Dsort -B` (or whatever test configuration you must use)

Since the container is binding to your source, you can make edits from your IDE and continue to run build jobs.

NOTE: Docker containers can eat up disk space fast! From time to time, run `docker system prune` to clean out old images.