A command-line tool for analyzing Docker image layers to inspect file sizes and composition.
dlayer is a command-line tool designed to analyze Docker image layers by inspecting the files and directories within each layer. It helps developers identify which components contribute most to image size, making it easier to optimize Docker builds and reduce bloat. The tool accepts input from `docker save` commands or tar files and provides interactive or text-based output.
DevOps engineers, backend developers, and platform teams who regularly build and optimize Docker images for production deployments.
dlayer offers a lightweight, fast alternative to GUI-based Docker analysis tools, with a focus on terminal usability and scriptable output for integration into CI/CD pipelines.
dlayer is docker layer analyzer.
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The README includes a screenshot and describes an interactive mode (-i flag) that allows browsing layers and files directly in the terminal, making exploration intuitive without leaving the command line.
dlayer accepts input from stdin via docker save or from saved tar files (-f flag), as shown in usage examples, providing versatility in how images are analyzed without locking users into a single workflow.
It can be run as a Docker container itself, demonstrated in commands like docker run -v $PWD:/workdir -it orisano/dlayer, enabling easy use in isolated or CI/CD environments without local Go installation.
The tool allows adjusting max depth (-d flag) and max files (-n flag) for output, enabling focused analysis on specific layers or directories, as highlighted in the command-line options.
dlayer requires images to be exported via docker save before analysis, adding an extra step compared to tools that inspect images directly from registries or running containers.
It focuses only on file size and distribution analysis, lacking built-in features for security scanning, dependency tracking, or automated optimization suggestions, which might require supplementary tools.
The README is brief with basic examples, offering little guidance on advanced use cases, error handling, or integration scenarios, which could hinder adoption for complex workflows.