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build: editorial suggestions for cache docs 

Co-authored-by: CrazyMax <github@crazymax.dev>
Co-authored-by: Justin Chadwell <github@jedevc.com>
This commit is contained in:
David Karlsson 2022-09-20 15:20:47 +02:00 committed by Justin Chadwell
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---
title: Optimizing builds with cache management
description: Improve your build speeds by taking advantage of the builtin cache
keywords: build, buildx, buildkit, dockerfile, image layers, build instructions, build context
keywords: >
build, buildx, buildkit, dockerfile, image layers, build instructions, build
context
---
It's very unlikely you end up just building a docker image once - most of the
time, you'll want to build it again at some point, whether that's for the next
release of your software, or, more likely, on your local development machine
for testing. Because building images is a frequent operation, docker provides
several tools to speed up your builds for when you inevitably need to run them
again.
You will likely find yourself rebuilding the same Docker image over and over
again. Whether it's for the next release of your software, or locally during
development. Because building images is a common task, Docker provides several
tools that speed up builds.
The main approach to improving your build's speed is to take advantage of
docker's build cache.
The most important feature for improving build speeds is Docker's build cache.
## How does the build cache work?
Docker's build cache is quite simple to understand - first, remember the
instructions that make up your Dockerfile, for example, in this build which
might be used to create a C/C++ program:
Understanding Docker's build cache helps you write better Dockerfiles that
result in faster builds.
Have a look at the following example, which shows a simple Dockerfile for a
program written in C.
```dockerfile
FROM ubuntu:latest
RUN apt-get update && apt-get install -y build-essentials
COPY . /src/
COPY main.c /src/
WORKDIR /src/
RUN make build
```
Each instruction in this Dockerfile (roughly) translates into a layer in your
final image. You can think of layers in a stack, with each layer adding more
content to the filesystem on top of the layer before it:
Each instruction in this Dockerfile translates (roughly) to a layer in your
final image. You can think of image layers as a stack, with each layer adding
more content on top of the layers that came before it:
![Image layer diagram showing the above commands chained together one after the other](../images/cache-stack.svg){:.invertible}
Now, if one of the layers changes, somewhere - for example, suppose you make a
change to your C/C++ program in `main.c`. After this change, the `COPY` command
will have to run again, so that the layer changes, so the cache for that layer
has been invalidated.
Whenever a layer changes, that layer will need to be re-built. For example,
suppose you make a change to your program in the `main.c` file. After this
change, the `COPY` command will have to run again in order for those changes to
appear in the image. In other words, Docker will invalidate the cache for this
layer.
![Image layer diagram, but now with the link between COPY and WORKDIR marked as invalid](../images/cache-stack-invalidate-copy.svg){:.invertible}
But since we have a change to that file, we now need to run our `make build`
step again, so that those changes are built into our program. So since our
cache for `COPY` was invalidated, we also have to invalidate the cache for all
the layers after it, including our `RUN make build`, so that it will run again:
If a layer changes, all other layers that come after it are also affected. When
the layer with the `COPY` command gets invalidated, all layers that follow will
need to run again, too:
![Image layer diagram, but now with all links after COPY marked as invalid](../images/cache-stack-invalidate-rest.svg){:.invertible}
That's pretty much all there is to understand the cache - once there's a change
in a layer, then all the layers after it will need to be rebuilt as well (even
if they wouldn't build anything differently, they still need to re-run).
And that's the Docker build cache in a nutshell. Once a layer changes, then all
downstream layers need to be rebuilt as well. Even if they wouldn't build
anything differently, they still need to re-run.
> **Note**
>
@ -60,214 +60,230 @@ if they wouldn't build anything differently, they still need to re-run).
> Dockerfile to upgrade all the software packages in your Debian-based image to
> the latest version.
>
> Unfortunately, this doesn't mean that the images you build are *always* up to
> date! If you built the image a week ago, then the results of your `apt-get`
> will get cached, and re-used if you re-run it now! The only way to force a
> re-run is to make sure that a layer before it has changed, for example, by
> making sure you have the latest version of the image used in `FROM`.
> This doesn't mean that the images you build are always up to date. Rebuilding
> the image on the same host one week later will still get you the same packages
> as before. The only way to force a rebuild is by making sure that a layer
> before it has changed, or by clearing the build cache using
> [`docker builder prune`](/engine/reference/commandline/builder_build/).
## How can I use the cache efficiently?
Now that we've seen how the cache works, we can look at how to best take
advantage of the cache to get the best results. While the cache will
automatically work on any docker build that you run, you can often refactor
your Dockerfile to get even better performance and save precious seconds (or
even minutes) off of your builds!
Now that you understand how the cache works, you can begin to use the cache to
your advantage. While the cache will automatically work on any `docker build`
that you run, you can often refactor your Dockerfile to get even better
performance. These optimizations can save precious seconds (or even minutes) off
of your builds.
### Order your layers
Putting the commands in your Dockerfile into a logical order is a great place
to start. Because a change in an earlier step will rebuild all the later steps,
we want to make sure that we put our most expensive steps near the beginning,
and our most frequently changing steps near the end, to avoid unnecessarily
rebuilding layers that haven't changed much.
Putting the commands in your Dockerfile into a logical order is a great place to
start. Because a change causes a rebuild for steps that follow, try to make
expensive steps appear near the beginning of the Dockerfile. Steps that change
often should appear near the end of the Dockerfile, to avoid triggering rebuilds
of layers that haven't changed.
Let's take a simple example, a Dockerfile snippet that runs a javascript build
from the source files in the current directory:
Consider the following example. A Dockerfile snippet that runs a JavaScript
build from the source files in the current directory:
```dockerfile
FROM node
WORKDIR /app
COPY . .
RUN npm install
RUN npm build
COPY . . # Copy over all files in the current directory
RUN npm install # Install dependencies
RUN npm build # Run build
```
We can examine why this isn't very efficient. If we update our `package.json`
file, we'll install all of our dependencies and run the build from scratch, as
intended. But, if we update `src/main.js`, then we'll install all of our
dependencies again - even if nothing has changed!
This Dockerfile is rather inefficient. Updating any file causes a reinstall of
all dependencies every time you build the Docker image &emdash; even if the
dependencies didn't change since last time!
We can improve this, to only install dependencies the relevant files have
changed:
Instead, the `COPY` command can be split in two. First, copy over the package
management files (in this case, `package.json` and `yarn.lock`). Then, install
the dependencies. Finally, copy over the project source code, which is subject
to frequent change.
```dockerfile
FROM node
WORKDIR /app
COPY package.json yarn.lock .
RUN npm install
COPY . .
RUN npm build
COPY package.json yarn.lock . # Copy package management files
RUN npm install # Install dependencies
COPY . . # Copy over project files
RUN npm build # Run build
```
What we've done is to divide up our `COPY` command to only copy over our
`package.json` and `yarn.lock` before the `npm install` - this means that we'll
only re-run `npm install` if those files change, instead of any of the files
in our local directory!
By installing dependencies in earlier layers of the Dockerfile, there is no need
to rebuild those layers when a project file has changed.
### Keep layers small
One of the easiest things you can do to keep your images building quickly is to
just put less stuff into your build! This keeps your image layers thin and
lean, which means that not only will your cache stay smaller, but there should
be fewer things that could be out-of-date and need rebuilding!
One of the best things you can do to speed up image building is to just put less
stuff into your build. Fewer parts means the cache stay smaller, but also that
there should be fewer things that could be out-of-date and need rebuilding.
To get started, here are a few tips and tricks:
- Don't `COPY` unnecessary files into your build environment!
#### Don't include unnecessary files
Running a command like `COPY . /src` will `COPY` your entire build context
into the image! If you've got logs, package manager artifacts, or even
previous build results in your current directory, those will also be copied
over, which will make your image larger than it needs to be (especially as
those files are usually not helpful)!
You can avoid copying these files over by `COPY`ing only the files and
directories that you want, for example, you might only just want a `Makefile`
and your `src` directory - if that's all you need, then you can split up your
`COPY` into `COPY ./Makefile /src` and `COPY ./src /src`. If you do want the
entire current directory, but want to ignore the unnecessary files in it, you
can setup your [`.dockerignore` file](https://docs.docker.com/engine/reference/builder/#dockerignore-file),
to make sure that those files won't be copied over!
Be considerate of what files you add to the image.
- Use your package manager wisely!
Running a command like `COPY . /src` will `COPY` your entire build context into
the image. If you've got logs, package manager artifacts, or even previous build
results in your current directory, those will also be copied over. This could
make your image larger than it needs to be, especially as those files are
usually not useful.
No matter what operating system or programming language you choose to use as
your build's base image, most docker images have some sort of package manager
to help install software into your image. For example, `debian` has `apt`,
`alpine` has `apk`, `python` has `pip`, `node` has `npm`, etc, etc.
Avoid adding unnecessary files to your builds by explicitly stating the files or
directories you intend to copy over. For example, you might only want to add a
`Makefile` and your `src` directory to the image filesystem. In that case,
consider adding this to your Dockerfile:
When installing packages be careful! Make sure to only install the packages
that you need - if you're not going to use them, don't install them. Remember
that this might be a different list for your local development environment
and your production environment. You can use multi-stage builds (which we'll
cover later) to split these up efficiently.
```dockerfile
COPY ./src ./Makefile /src
```
- Try using the `RUN` command dedicated cache!
As opposed to this:
The `RUN` command supports a specialized cache, which can be used when you
need a more fine-grained cache between runs. For example, when installing
packages, you don't always need to fetch all of your packages from the
internet each time, you only need the ones that have changed!
```dockerfile
COPY . /src
```
To solve this problem, you can use `RUN --mount type=cache`. For example, for
your `debian`-based image you might use the following:
You can also create a
[`.dockerignore` file](https://docs.docker.com/engine/reference/builder/#dockerignore-file),
and use that to specify which files and directories to exclude from the build
context.
```dockerfile
RUN \
--mount=type=cache,target=/var/cache/apt \
apt-get update && apt-get install -y git
```
#### Use your package manager wisely
The use of the explicit cache with the `--mount` flag keeps the contents of
the `target` directory preserved between builds - so when this layer needs to
be rebuilt, then it'll be able to use `apt`'s own cache in `/var/cache/apt`.
Most Docker image builds involve using a package manager to help install
software into the image. Debian has `apt`, Alpine has `apk`, Python has `pip`,
NodeJS has `npm`, and so on.
When installing packages, be considerate. Make sure to only install the packages
that you need. If you're not going to use them, don't install them. Remember
that this might be a different list for your local development environment and
your production environment. You can use multi-stage builds to split these up
efficiently.
#### Use the dedicated `RUN` cache
The `RUN` command supports a specialized cache, which you can use when you need
a more fine-grained cache between runs. For example, when installing packages,
you don't always need to fetch all of your packages from the internet each time.
You only need the ones that have changed.
To solve this problem, you can use `RUN --mount type=cache`. For example, for
your Debian-based image you might use the following:
```dockerfile
RUN \
--mount=type=cache,target=/var/cache/apt \
apt-get update && apt-get install -y git
```
Using the explicit cache with the `--mount` flag keeps the contents of the
`target` directory preserved between builds. When this layer needs to be
rebuilt, then it'll use the `apt` cache in `/var/cache/apt`.
### Minimize the number of layers
Keeping your layers small is a good step to getting quick builds - the logical
next step is to reduce the number of layers that you have! Fewer layers mean
that you have less to rebuild, when something in your Dockerfile changes, so
your build will complete faster!
Keeping your layers small is a good first step, and the logical next step is to
reduce the number of layers that you have. Fewer layers mean that you have less
to rebuild, when something in your Dockerfile changes, so your build will
complete faster.
Here are some more tips you can use:
The following sections outline some tips you can use to keep the number of
layers to a minimum.
- Use an appropriate base image!
#### Use an appropriate base image
Docker provides over 170 pre-built [official images](https://hub.docker.com/search?q=&image_filter=official)
for almost every common development scenario! For example, if you're building
a Java web server, then while you could install `java` into any image you
like, it's much quicker (and easier to manage updates) if you use a dedicated
image, for example, [`openjdk`](https://hub.docker.com/_/openjdk/). Even if
there's not an official image for what you might want, Docker provides images
from [verified publishers](https://hub.docker.com/search?q=&image_filter=store)
and [open source partners](https://hub.docker.com/search?q=&image_filter=open_source)
that can help you on your way, and the community often produces third-party
images to use as well.
These pre-built stop you from needing to manually install and manage the
software, which allows you to save valuable build time as well as disk space.
Docker provides over 170 pre-built
[official images](https://hub.docker.com/search?q=&image_filter=official) for
almost every common development scenario. For example, if you're building a Java
web server, use a dedicated image such as
[`openjdk`](https://hub.docker.com/_/openjdk/). Even when there's not an
official image for what you might want, Docker provides images from
[verified publishers](https://hub.docker.com/search?q=&image_filter=store) and
[open source partners](https://hub.docker.com/search?q=&image_filter=open_source)
that can help you on your way. The Docker community often produces third-party
images to use as well.
- Use multi-stage builds to run builds in parallel!
Using official images saves you time and ensures you stay up to date and secure
by default.
<!-- x-link to multi-stage builds once we have some reworked content for that -->
#### Use multi-stage builds
Multi-stage builds let you split up your Dockerfile into multiple distinct
stages, and then provide the tools to combine them all back together again.
The docker builder will work out dependencies between the stages and run them
using the most efficient strategy, even allowing you to run multiple commands at the
same time in this way!
To use a multi-stage build, you can simply use multiple `FROM` commands. For
example, suppose you want to build a simple web server that serves HTML from
your `docs` directory in Git:
```dockerfile
FROM alpine as git
RUN apk add git
FROM git as fetch
WORKDIR /repo
RUN git clone https://github.com/your/repository.git .
FROM nginx as site
COPY --from=fetch /repo/docs/ /usr/share/nginx/html
```
This build has 3 stages - `git`, `fetch` and `site`. In this example, we've
used `git` as the base for the `fetch` stage, and also used `COPY`'s `--from`
flag to copy the data from the `docs/` directory into the NGINX server
directory.
Each stage has only a few instructions, and when possible, docker will run
these stages in parallel. Additionally, only the final instructions in the
`site` stage will end up as layers in our image, so we won't have our entire
`git` history embedded into the final result, which helps keep our images
small and secure.
<!-- x-link to multi-stage builds once we have some reworked content for that -->
- Combine your commands together wherever possible!
Multi-stage builds let you split up your Dockerfile into multiple distinct
stages. Each stage completes a step in the build process, and you can bridge the
different stages to create your final image at the end. The Docker builder will
work out dependencies between the stages and run them using the most efficient
strategy. This even allows you to run multiple builds concurrently.
Most commands in your Dockerfile support being joined together, so that they
can do multiple things all at once! For example, it's fairly common to see
`RUN` commands being used like this:
Multi-stage builds use two or more `FROM` commands. The following example
illustrates building a simple web server that serves HTML from your `docs`
directory in Git:
```dockerfile
RUN echo "the first command"
RUN echo "the second command"
```
```dockerfile
# stage 1
FROM alpine as git
RUN apk add git
But actually, we can run both of these commands inside a single `RUN`, which
means that they will share the same cache! We can do this by using the `&&`
shell operator to run one command after another:
# stage 2
FROM git as fetch
WORKDIR /repo
RUN git clone https://github.com/your/repository.git .
```dockerfile
RUN echo "the first command" && echo "the second command"
# or to split to multiple lines
RUN echo "the first command" && \
echo "the second command"
```
# stage 3
FROM nginx as site
COPY --from=fetch /repo/docs/ /usr/share/nginx/html
```
We can also use [heredocs]() to simplify complex multiline scripts (note the
`set -e` command to exit immediately after any command fails, instead of
continuing):
This build has 3 stages: `git`, `fetch` and `site`. In this example, `git` is
the base for the `fetch` stage. It uses the `COPY --from` flag to copy the data
from the `docs/` directory into the Nginx server directory.
```dockerfile
RUN <<EOF
set -e
echo "the first command"
echo "the second command"
EOF
```
Each stage has only a few instructions, and when possible, Docker will run these
stages in parallel. Only the instructions in the `site` stage will end up as
layers in the final image. The entire `git` history doesn't get embedded into
the final result, which helps keep the image small and secure.
#### Combine commands together wherever possible.
Most Dockerfile commands, and `RUN` commands in particular, can often be joined
together. For example, instead of using `RUN` like this:
```dockerfile
RUN echo "the first command"
RUN echo "the second command"
```
It's possible to run both of these commands inside a single `RUN`, which means
that they will share the same cache! This can is achievable using the `&&` shell
operator to run one command after another:
```dockerfile
RUN echo "the first command" && echo "the second command"
# or to split to multiple lines
RUN echo "the first command" && \
echo "the second command"
```
Another shell feature that allows you to simplify and concatenate commands in a
neat way are [`heredocs`](https://en.wikipedia.org/wiki/Here_document){:
target="blank" rel="noopener" class="\_"}. It enables you to create multi-line
scripts with good readability:
```dockerfile
RUN <<EOF
set -e
echo "the first command"
echo "the second command"
EOF
```
(Note the `set -e` command to exit immediately after any command fails, instead
of continuing.)
## Other resources

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