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<!--Delete sections as needed --> ## Description Updated Offload Beta docs for enterprise EA. Notable topics updated: - [All topics under `/offload/`](https://deploy-preview-23632--docsdocker.netlify.app/offload/) - [Manage Docker products](https://deploy-preview-23632--docsdocker.netlify.app/admin/organization/manage-products/) - [Settings reference - Enable Docker Offload](https://deploy-preview-23632--docsdocker.netlify.app/enterprise/security/hardened-desktop/settings-management/settings-reference/#enable-docker-offload) - [Settings - Docker Offload](https://deploy-preview-23632--docsdocker.netlify.app/desktop/settings-and-maintenance/settings/#docker-offload) - [VM/VDI - Use Docker Offload](https://deploy-preview-23632--docsdocker.netlify.app/desktop/setup/vm-vdi/#use-docker-offload) - [Docker Offload CLI reference](https://deploy-preview-23632--docsdocker.netlify.app/reference/cli/docker/offload/) ~~**Pending audit log updates**~~ Will handle in followup PR to keep this moving ## Related issues or tickets DCL-745 DCL-1033 DCL-1019 ENGDOCS-2929 ## Reviews <!-- Notes for reviewers here --> <!-- List applicable reviews (optionally @tag reviewers) --> - [ ] Technical review - [ ] Editorial review - [ ] Product review --------- Signed-off-by: Craig Osterhout <craig.osterhout@docker.com>
79 lines
3.0 KiB
Markdown
79 lines
3.0 KiB
Markdown
---
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title: Optimize Docker Offload usage
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linktitle: Optimize usage
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weight: 40
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description: Learn how to optimize your Docker Offload usage.
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keywords: cloud, optimize, performance, offload
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---
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Docker Offload builds and runs your containers remotely, not on the machine where you invoke the
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commands. This means that files must be transferred from your local system to the
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cloud over the network.
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Transferring files over the network introduces higher latency and lower
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bandwidth compared to local transfers.
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Even with optimizations, large projects or slower network connections can lead to longer transfer times. Here are
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several ways to optimize your setup for Docker Offload:
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- [Use `.dockerignore` files](#dockerignore-files)
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- [Choose slim base images](#slim-base-images)
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- [Use multi-stage builds](#multi-stage-builds)
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- [Fetch remote files during the build](#fetch-remote-files-in-build)
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- [Leverage multi-threaded tools](#multi-threaded-tools)
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For general Dockerfile tips, see [Building best practices](/manuals/build/building/best-practices.md).
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## dockerignore files
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A [`.dockerignore` file](/manuals/build/concepts/context.md#dockerignore-files)
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lets you specify which local files should *not* be included in the build
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context. Files excluded by these patterns won’t be uploaded to Docker Offload
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during a build.
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Typical items to ignore:
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- `.git` – avoids transferring your version history. (Note: you won’t be able to run `git` commands in the build.)
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- Build artifacts or locally generated binaries.
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- Dependency folders such as `node_modules`, if those are restored in the build
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process.
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As a rule of thumb, your `.dockerignore` should be similar to your `.gitignore`.
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## Slim base images
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Smaller base images in your `FROM` instructions can reduce final image size and
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improve build performance. The [`alpine`](https://hub.docker.com/_/alpine) image
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is a good example of a minimal base.
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For fully static binaries, you can use [`scratch`](https://hub.docker.com/_/scratch), which is an empty base image.
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## Multi-stage builds
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[Multi-stage builds](/build/building/multi-stage/) let you separate build-time
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and runtime environments in your Dockerfile. This not only reduces the size of
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the final image but also allows for parallel stage execution during the build.
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Use `COPY --from` to copy files from earlier stages or external images. This
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approach helps minimize unnecessary layers and reduce final image size.
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## Fetch remote files in build
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When possible, download large files from the internet during the build itself
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instead of bundling them in your local context. This avoids network transfer
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from your client to Docker Offload.
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You can do this using:
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- The Dockerfile [`ADD` instruction](/reference/dockerfile/#add)
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- `RUN` commands like `wget`, `curl`, or `rsync`
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### Multi-threaded tools
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Some build tools, such as `make`, are single-threaded by default. If the tool
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supports it, configure it to run in parallel. For example, use `make --jobs=4`
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to run four jobs simultaneously.
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Taking advantage of available CPU resources in the cloud can significantly
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improve build time.
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