In this lesson, you will learn how to automate the cleanup of obsolete images in your private registry to optimize storage costs and keep your development pipeline organized.
As you build and push images using the patterns we’ve covered—like semantic tagging and multi-stage builds—your private registry (such as Harbor, Artifactory, or AWS ECR) can quickly become cluttered with thousands of outdated or orphaned images. Manually deleting these is error-prone and inefficient. Instead, we use Retention Policies to define rules that tell the registry exactly when to prune old images.
How Retention Works
A retention policy acts as a "garbage collector" for your repository. Instead of just deleting everything older than a certain date, you typically define rules based on three criteria:
- Count-based: Keep only the "N" most recent images (e.g., keep the last 10 versions of
my-app). - Time-based: Delete images older than "X" days (e.g., remove anything pushed over 90 days ago).
- Tag patterns: Protect specific tags from deletion (e.g., always keep images tagged as
prodorstable, even if they are old).
Example Policy Logic
Imagine you are building my-app continuously. Your policy configuration might look like this conceptual rule set:
rules:
- rule_name: "Keep recent feature branches"
action: delete
params:
most_recent: 5
days_since_push: 30
exclude_tags: ["latest", "prod-*"]
By applying this, the registry will automatically scan your repositories. If you have 50 versions of a dev-branch image, the policy deletes all but the 5 most recent ones, provided they are older than 30 days. Crucially, it respects the exclude_tags list, ensuring that your production-ready images remain safely archived despite their age.
Implementing these policies is essential for cost management. Without them, you end up paying for storage of gigabytes of "dangling" images that are no longer used by any deployment. Automating this cleanup ensures that your registry remains performant and that your CI/CD environment stays lean as you scale your projects.
Key Takeaway: Automating image retention policies prevents storage bloat by programmatically pruning obsolete images while safeguarding critical production tags.