Integrations

This section provides information and code samples to help you integrate Dagger with other tools and platforms.

📄️ Argo Workflows

Dagger provides a programmable container engine that can be invoked from an Argo Workflow to run a Dagger pipeline. This allows you to benefit from Dagger's caching, debugging, and visualization features, whilst still keeping all of your existing Argo Workflows infrastructure.

📄️ AWS CodeBuild

Dagger provides a programmable container engine that allows you to migrate most of your AWS CodeBuild specification into Dagger Functions. This allows you to execute your pipeline the same locally and in AWS CodeBuild, with the additional benefits of intelligent caching and portability.

📄️ Azure Pipelines

Dagger provides a programmable container engine that allows you to replace your YAML Azure Pipelines definitions with Dagger Functions written in a regular programming language. This allows you to execute your pipeline the same way locally and in CI, with the additional benefit of intelligent caching.

📄️ CircleCI

Dagger provides a programmable container engine that allows you to replace your YAML workflows in CircleCI with Dagger Functions written in a regular programming language. This allows you to execute your pipeline the same locally and in CI, with the additional benefit of intelligent caching.

📄️ GitHub

Dagger provides a number of GitHub-specific features that make it easier to develop and run CI pipelines in GitHub repositories.

📄️ GitLab CI

Dagger provides a programmable container engine that allows you to replace your YAML pipeline definitions in GitLab with Dagger Functions written in a regular programming language. This allows you to execute your pipeline the same locally and in GitLab, with the additional benefit of intelligent caching.

📄️ Google Cloud Run

Dagger can be used to deploy any containerized application to Google Cloud Run. This allows developers to create continuous delivery pipelines that can be used both locally and in CI, and also run faster due to Dagger's intelligent caching. This integration does not require any installation of Google Cloud tools, such as the Google Cloud CLI or the Google Cloud SDKs.

📄️ Java

Dagger can be used to perform common CI tasks - testing, containerizing, publishing and more - for any Java application. Java developers can leverage an excellent Java module from the Daggerverse which provides various Dagger Functions to work with Java projects. These Dagger Functions make it easy to configure the Java/Maven versions to use, the Maven sub-commands for building and packaging the application, and the output target.

📄️ Jenkins

Dagger provides a programmable container engine that allows you to replace your Groovy-based Jenkins pipelines with with Dagger Functions written in a regular programming language. This allows you to execute your pipeline the same locally and in Jenkins, with intelligent caching, while keeping all of your existing Jenkins infrastructure.

📄️ Kubernetes

This section covers different strategies for deploying Dagger on a Kubernetes cluster.

📄️ Nerdctl

Dagger can be used with any OCI-compatible container runtime, including nerdctl.

📄️ OpenShift

Dagger can be used to set up a Continuous Integration (CI) environment on an OpenShift cluster. This makes it possible to distribute CI workloads across multiple nodes and scale out as needed.

📄️ PHP

Dagger can be used to perform common CI tasks - testing, containerizing, publishing and more - for any PHP application, by encapsulating these CI tasks as Dagger Functions in a Dagger module.

📄️ Podman

Dagger can be used with any OCI-compatible container runtime, including Podman.

📄️ Tekton

Dagger provides a programmable container engine that can be invoked from Tekton to run a Dagger pipeline. This allows you to benefit from Dagger's caching, debugging, and visualization features, whilst still keeping all of your existing Tekton infrastructure.