Meet the Guardener: The intelligent migration expert for everyone

Today, we’re introducing the Guardener: an AI-native agent that accelerates engineering teams’ seamless adoption of trusted open source artifacts across their software development and deployment workflows. The Guardener is designed to simplify replacing insecure artifacts with hardened Chainguard components, continuously maintaining a secure-by-default posture in the software supply chain.

The first use case the Guardener meets is one of the highest-friction problems we see from customers: seamlessly converting legacy, bloated Dockerfiles to use secure, minimal Chainguard container images.

Trusted container images have become a foundational layer of the modern software development lifecycle, but organizations large and small still struggle to move their legacy, bloated distro images to distroless, zero-CVE defaults. The challenge isn't convincing engineering teams that trusted container images matter. It's giving them a path that scales across their teams without sacrificing velocity, eliminating perceived barriers like developer toil and refactoring workloads.

From manual refactoring to intelligent automation

Rather than offering a simple “find and replace,” the Guardener intelligently gathers environmental context and insights to understand what a Dockerfile is designed to do before rebuilding it layer by layer, testing as it goes. The result is an accurate, stable, secure-by-default Dockerfile, not a best-guess translation that needs hours of debugging.

The impact of rapid, accurate, and stable image migration is felt across an organization:

• For platform engineers: Rapidly generate golden image catalogs and drive broad standardization on zero-CVE, built-from-source base images. The Guardener turns what was a months-long migration project into an automated workflow, so platform teams can focus on architecture and governance rather than Dockerfile refactoring.

• For developers: Stay in your flow state. The Guardener automates package mappings from traditional, bloated distros so developers don't need to learn new package managers or manually map APK equivalents. It mirrors standard Docker build workflows, making secure Dockerfiles the path of least resistance.

• For security teams: Every migration includes post-migration insights that compare image size, Common Vulnerabilities and Exposures (CVEs), and filesystem changes, providing verifiable audit trails. Security stakeholders get the transparency they need without adding friction to engineering workflows.

What makes the Guardener unique

The Guardener takes an active, opinionated role in delivering the outcome engineering and security teams want. This is made possible by leveraging the same technology we built for our own Chainguard Factory, scaling our own maintenance capabilities to merge over 30,000 PRs in the last quarter alone. We’re going much further than general-purpose AI tools that identify and suggest `FROM:` line changes in a Dockerfile and insert a new registry.

Some of the unique capabilities of the Guardener include:

• Intelligent AI orchestration: The Guardener makes contextual decisions about package mappings and build strategies, going beyond simple text replacement to produce accurate, stable conversions that reflect the intent of the original Dockerfile.

• Incremental validation: Instead of generating a complete file and hoping it works, The Guardener builds Dockerfiles layer by layer, catching divergence points early. It provides functional equivalence checks and detailed migration reports so teams know exactly what changed and why.

• GitHub or local deployment: The Guardener can be deployed via a GitHub app integration or locally in your environment to provide deeper context, telemetry, and validation. The Guardener calls back to Chainguard Factory via API, delivering accuracy that standalone tools can't match.

From migration to agentic development partner

There’s far more the Guardener can unlock for our customers in the future, removing more barriers to adoption and secure velocity, especially as agentic development fleets interface with Chainguard’s agent. We see the Guardener evolving in a few distinct ways:

• Going from conversion to ongoing build and maintenance: Grow from Dockerfile conversion to custom image build and continuous maintenance with Chainguard Factory’s AI-native, hardened SLSA Level-3 pipeline. The Guardener will continuously push compatible image and dependency updates to downstream artifact managers and/or repos.

• Expanding to new secure-by-default artifacts: Extend to other code development artifacts, such as language libraries, as well as CI/CD tooling like GitHub Actions, offering secure-by-default options and frictionless adoption paths. 

• Predictive artifact requests: Continuously assess your environment and identify frequently installed third-party dependencies, proactively suggesting hardened, compliant versions of artifacts in Chainguard Factory based on their usage. 

• Tracking implementation and reconciliation to runtime: Give teams better visibility into implementation progress and, as runtime insight expands, a clearer view of how those changes are reflected in production environments.

• Providing supply chain security insights: Enhance telemetry and reporting on open source artifact adoption will give platform and security teams a continuous view into supply chain health so they can invest resources and evaluate risks effectively.

• Creating greater personalization: Build and leverage Guardener skills designed for particular teams or product units, delivering agent- or team-specific parameters governing access, customizations, and builds without impeding speed or flexibility.

Get started today

If your organization has embraced trusted container images as part of the path forward and is now figuring out how to make that real across every team and pipeline, the Guardener is built for you. Sign up for the beta waitlist to see how Guardener can accelerate adoption without compromising the developer experience.