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Tracked since2026
0 reviews trackedThe Bottom Line
Entry price
Free, no paid tier
Biggest pro
Provides a clear visual breakdown of Docker image layers
Biggest con
The image efficiency metric is experimental (beta quality)
TL;DR - Dive
- Analyzes Docker/OCI image layers and their contents.
- Identifies wasted space and provides an image efficiency score.
- Helps reduce image size and optimize Docker builds.
Pricing: Free forever
Best for: Individuals & startups
What is Dive?
Dive is a command-line tool designed to help developers analyze and optimize their Docker/OCI images. It provides a detailed breakdown of an image's layers, allowing users to visualize the contents of each layer and identify changes (additions, modifications, removals) between them. This granular view helps in understanding how an image is constructed and where inefficiencies, such as duplicated files or unnecessary content, might exist.
The tool is primarily for developers, DevOps engineers, and anyone working with Docker or OCI images who wants to reduce image size, improve build times, and enhance the overall efficiency of their containerized applications. By highlighting wasted space and providing an "image efficiency" score, Dive empowers users to make informed decisions about their Dockerfile instructions and build processes, leading to smaller, faster, and more secure images.
Dive supports various image sources and container engines, including Docker and Podman, and can be integrated into CI pipelines to automate image analysis and enforce size constraints. Its interactive TUI (Text User Interface) allows for easy navigation and exploration of the file system within each layer.
Available on: macOS, Linux
Pros & Cons
Pros
- Provides a clear visual breakdown of Docker image layers
- Helps identify and eliminate wasted space in Docker images
- Can be integrated into CI/CD pipelines for automated checks
- Supports various installation methods across different operating systems
- Offers quick build and analysis cycles
Cons
- The image efficiency metric is experimental (beta quality)
- Snap installation method for Docker might conflict with apt-get Docker installations
- Podman engine support is Linux only
Preview
Key Features
Show Docker image contents broken down by layerIndicate what's changed (added, modified, removed) in each layerEstimate "image efficiency" with a percentage score and total wasted file spaceQuick build/analysis cycles for immediate feedbackCI integration for automated pass/fail results based on image efficiencySupports multiple image sources and container engines (Docker, Podman, Docker Tar Archive)Interactive file tree exploration with arrow keys
Pricing Plans
Pricing checked Jul 15, 2026
Open Source
Free
- Full source code access
- MIT License license
- Community support
- Self-hosted
Reviews

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Dive FAQ
How does Dive help optimize Docker image sizes?
Dive provides a detailed, visual breakdown of an image's layers, allowing users to identify and eliminate wasted space. It highlights inefficiencies like duplicated files or unnecessary content, helping users make informed decisions about their Dockerfile instructions to achieve smaller images.
Which teams benefit most from using Dive?
Dive is most beneficial for developers, DevOps engineers, and anyone working with Docker or OCI images. These teams can leverage Dive to reduce image size, improve build times, and enhance the overall efficiency of their containerized applications.
How is Dive priced?
Dive is free to use, with no paid plan required. This makes it accessible for all users looking to analyze and optimize their Docker and OCI images without a subscription cost.
Can Dive be integrated into continuous integration pipelines?
Yes, Dive can be integrated into CI pipelines to automate image analysis. This allows teams to enforce size constraints and ensure image efficiency as part of their regular build processes.
How does Dive compare to Podman for image analysis?
Dive is a tool for analyzing and optimizing Docker/OCI images, while Podman is a container engine that can also manage images. Dive specifically focuses on layer breakdown and efficiency scoring, whereas Podman provides broader container management capabilities, though its engine support in Dive is currently Linux only.
What kind of limitations should users be aware of when using Dive?
Users should note that Dive's image efficiency metric is currently experimental, meaning it is in beta quality. Additionally, the snap installation method for Docker might conflict with existing apt-get Docker installations, and Podman engine support is exclusively for Linux.
Source: github.com