Use Cases
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DryDock is a registry-agnostic container image build tool.

Images as Code

Automatically build images from Dockerfiles stored in version control. Images will always be up to date with your selected branch.


Each image is only rebuilt when needed. Configure right-sized nodes to reduce build time and cost.


Autoscaling means that builds never queue for resources. Large nodes eliminate out-of-memory errors and support parallel compilation.


Review the success of each build, code commit that was used, and which changes triggered the build.

Image Security

Avoid vulnerabilities due to out-of-date packages.
  • Image dependencies are automatically detected using FROM instructions in your Dockerfiles.
  • Dependencies are scanned for changes every 5 minutes.
  • When changed, DryDock automatically rebuilds your image.
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Catalogs of Images

Manage variants of similar images.
  • You may wish to ship your application with and without optional dependencies, publishing multiple images.
  • This often involves complex and brittle continuous integration scripts to fully leverage caching.
  • DryDock can manage this tree of dependencies, and efficiently build images as needed.

Compile Large Applications

Build resource intensive images, fast.
  • DryDock supports high-performance build nodes.
  • Select a high-memory node to build complex Conda environments.
  • Select a high-CPU node to compile your code with maximum parallelism.
  • DryDock enables builds that were previously only possible using self-hosted CI systems.



1 CPU | 2 GB RAM

Limit 5 images

Queue for shared node pool

Flat Rate per 90 build-hours

Starting at 4 CPU | 8 GB RAM for $30 / mo

No build queues

Unlimited builds, images, and users

Up to 32 CPU | 256 GB RAM