How We Reduced Dependabot Noise in Our Monorepo

Source: Dev.to

Why we needed Dependabot

• Dependency management had become increasingly manual and error‑prone.
• InnerSource Terraform modules were frequently updated, but consuming projects had to track and apply those changes manually. Over time, projects fell behind, making upgrades harder and increasing the risk of incompatibilities.
• Spring Boot dependencies were rarely updated after the initial setup, leaving known vulnerabilities in the codebase and triggering repeated alerts from Nexus SCA.
• CI pipelines began failing due to vulnerability policy violations—often for issues that already had fixes available.

We needed an automated way to keep both infrastructure and application dependencies up to date to avoid security alerts, CI failures, and the growing cost of manual updates. This led us to adopt Dependabot from GitHub.

Managing Dependabot in a monorepo

Grouped pull requests by ecosystem

• All Maven‑based updates generate a single pull request.
• All Docker‑based updates generate a separate single pull request.
• The same pattern applies to other ecosystems.

Update frequency per ecosystem

• Terraform dependencies are checked daily, since our InnerSource modules evolve frequently.
• All other ecosystems (Maven, Docker, etc.) are checked weekly to balance freshness with review effort.

Example Dependabot configuration

updates:
  - package-ecosystem: "maven"
    directories:
      - "/packages/app_a"
      - "/packages/app_b"
    schedule:
      interval: "weekly"
      day: "tuesday"
      time: "19:00"

Treat Dependabot PRs like regular feature branches

• Every Dependabot PR triggers the same CI pipelines as a developer‑created branch.
• Automated test suites run for each pull request, validating both infrastructure and application changes.
• Updates are only merged after passing all required checks and reviews.

Ownership and monitoring

• Each Dependabot PR is linked to a small Jira task and explicitly assigned to a developer.
• The assigned developer reviews the PR outcome and investigates any CI or test failures.
• If a PR fails, they identify the cause (breaking change, test issue, config update needed) and take corrective action.

This lightweight process ensures Dependabot PRs don’t become background noise.

Off‑hours CI execution

• Dependabot‑triggered pipelines are scheduled to run outside peak development time.
• This reduces contention on shared CI resources while developers are actively working.
• Teams still receive fresh results by the next working day, without slowing down feature development.

Tangible benefits

• Significant reduction in dependency‑related CI failures.
• Lower vulnerability alerts from Nexus SCA due to timely updates.
• Fewer, more meaningful pull requests, making reviews faster and easier.
• Improved stability across Terraform modules and Spring Boot applications.
• Better use of CI resources without impacting active development.

Overall, this approach has turned dependency management from a reactive problem into a predictable, low‑noise, and reliable process.