Best practices for speeding up builds

This page provides best practices for speeding up Cloud Build builds.

Building leaner containers

When you containerize an application, files that are not needed at runtime, such as build-time dependencies and intermediate files, can be inadvertently included in the container image. These unneeded files can increase the size of the container image and add extra time and cost as the image moves between your container image registry and your container runtime.

To help reduce the size of your container image, separate the building of the application, along with the tools used to build it, from the assembly of the runtime container.

For more information, see Building leaner containers.

Using Kaniko cache

Kaniko cache is a Cloud Build feature that caches container build artifacts by storing and indexing intermediate layers within a container image registry, such as Google's own Container Registry, where they are available for use by subsequent builds. For more information, see Using Kaniko cache.

Using a cached Docker image

The easiest way to increase the speed of your Docker image build is by specifying a cached image that can be used for subsequent builds. You can specify the cached image by adding the --cache-from argument in your build config file, which will instruct Docker to build using that image as a cache source.

Each Docker image is made up of stacked layers. Using --cache-from rebuilds all the layers from the changed layer until the end of the build; therefore using --cache-from is not beneficial if you change a layer in the earlier stages of your Docker build.

It is recommended that you always use --cache-from for your builds, but keep the following caveats in mind:

  • You need a previously built Docker image to cache from.
  • You can use --cache-from only for Docker builds; you cannot use it for builders that create other kind of artifacts.
  • The cached image must be retrieved from a registry, which may add to the time it takes to build.

The following steps explain how to build using a previously cached image:

YAML

  1. In your build config, add instructions to:

    • Pull the cached image from Container Registry. Notice that the docker pull build step below sets the entrypoint to bash, which allows you to run the command and ignore the returned error. This is required when you build an image for the first time, and docker pull does not have an existing image to pull.
    • Add a --cache-from argument to use that image for rebuilds.

      steps:
       - name: 'gcr.io/cloud-builders/docker'
         entrypoint: 'bash'
         args:
         - '-c'
         - |
           docker pull gcr.io/$PROJECT_ID/[IMAGE_NAME]:latest || exit 0
      - name: 'gcr.io/cloud-builders/docker'
        args: [
                  'build',
                  '-t', 'gcr.io/$PROJECT_ID/[IMAGE_NAME]:latest',
                  '--cache-from', 'gcr.io/$PROJECT_ID/[IMAGE_NAME]:latest',
                  '.'
              ]
      images: ['gcr.io/$PROJECT_ID/[IMAGE_NAME]:latest']
      

      where [IMAGE_NAME] is the name of your image.

  2. Build your image using the above build config:

    gcloud builds submit --config cloudbuild.yaml .
    

JSON

  1. In your build config, add instructions to:

    • Pull the cached image from Container Registry. Notice that the docker pull build step below sets the entrypoint to bash, which allows you to run the command and ignore any returned errors. This is required when you build an image for the first time, and docker pull does not have an existing image to pull.
    • Add a --cache-from argument to use that image for rebuilds.

      {
          "steps": [
          {
              "name": "gcr.io/cloud-builders/docker",
              "entrypoint": "bash",
              "args": ["-c", "docker pull gcr.io/$PROJECT_ID/quickstart-image:latest || exit 0"]
          },
          {
              "name": "gcr.io/cloud-builders/docker",
              "args": [
                  "build",
                  "-t",
                  "gcr.io/$PROJECT_ID/[IMAGE_NAME]:latest",
                  "--cache-from",
                  "gcr.io/$PROJECT_ID/[IMAGE_NAME]:latest",
                  "."
              ]
          }
          ],
          "images": ["gcr.io/$PROJECT_ID/[IMAGE_NAME]:latest"]
      }
      

      where [IMAGE_NAME] is the name of your image.

  2. Build your image using the above build config:

    gcloud builds submit --config cloudbuild.json .
    

Caching directories with Google Cloud Storage

To increase the speed of a build, reuse the results from a previous build. You can copy the results of a previous build to a Google Cloud Storage bucket, use the results for faster calculation, and then copy the new results back to the bucket. Use this method when your build takes a long time and produces a small number of files that does not take time to copy to and from Google Cloud Storage.

Unlike --cache-from, which is only for Docker builds, Google Cloud Storage caching can be used for any builder supported by Cloud Build.

Use the following steps to cache directories using Google Cloud Storage:

YAML

  1. In your build config file, add instructions to:

    • Copy the results of a previous build from the Google Cloud Storage bucket.
    • Use the results for the current build.
    • Copy the new results back into the bucket.

      steps:
      - name: gcr.io/cloud-builders/gsutil
        args: ['cp', 'gs://mybucket/results.zip', 'previous_results.zip']
      # operations that use previous_results.zip and produce new_results.zip
      - name: gcr.io/cloud-builders/gsutil
        args: ['cp', 'new_results.zip', 'gs://mybucket/results.zip']
      
  2. Build your code using the above build config:

    gcloud builds submit --config cloudbuild.yaml .
    

JSON

  1. In your build config file, add instructions to:

    • Copy the results of a previous build from the Google Cloud Storage bucket.
    • Use the results for the current build.
    • Copy the new results back into the bucket.

      {
          "steps": [
          {
              "name": "gcr.io/cloud-builders/gsutil",
              "args": ["cp", "gs://mybucket/results.zip", "previous_results.zip"]
          },
          {
              // operations that use previous_results.zip and produce new_results.zip
          },
          {
              "name": "gcr.io/cloud-builders/gsutil",
              "args": ["cp", "new_results.zip", "gs://mybucket/results.zip"]
          }
          ]
      }
      
  2. Build your code using the above build config:

    gcloud builds submit --config cloudbuild.json .
    

Using custom virtual machine sizes

In addition to the standard machine type, Cloud Build provides two high-CPU virtual machine types to run your builds. To increase the speed of your build, select a virtual machine with a higher CPU. Requesting a high-CPU machine may increase the startup time of your build as Cloud Build only starts these machines on demand.

For information on selecting custom disk sizes, see diskSize.

The following steps explain how to specify a custom VM size for a build:

gcloud

To specify a custom VM size, use the --machine-type argument:

gcloud builds submit --config=cloudbuild.yaml \
    --machine-type=n1-highcpu-8 .

YAML

  1. Specify the VM size in your build config file:

    steps:
    - name: 'gcr.io/cloud-builders/docker'
      args: ['build', '-t', 'gcr.io/my-project/image1', '.']
      # operations that take a long time to build
    - name: 'gcr.io/cloud-builders/docker'
      args: ['build', '-t', 'gcr.io/my-project/image2', '.']
    options:
      machineType: 'N1_HIGHCPU_8'
    
  2. Build using the above build config:

    gcloud builds submit --config cloudbuild.yaml .
    

JSON

  1. Specify the VM size in your build config file:

    {
        "steps": [
        {
            "name": "gcr.io/cloud-builders/docker",
            "args": ["build", "-t", "gcr.io/my-project/image1", "."]
        },
        // operations that take a long time to build
        {
            "name": "gcr.io/cloud-builders/docker",
            "args": ["build", "-t", "gcr.io/my-project/image2", "."]
        }
        ],
        "options": {
            "machineType": "N1_HIGHCPU_8"
        }
    }
    
  2. Build using the above build config:

    gcloud builds submit --config cloudbuild.json .
    

Avoiding the upload of unnecessary files

When a build is triggered, your code directory is uploaded for use by Cloud Build.

You can exclude files not needed by your build with a .gcloudignore file to optimize the upload time.

Examples of commonly excluded files include:

  • Documentation and sample code for project developers
  • Generated scaffolding code, binaries, *.jar files, or compiled web assets used for development.
  • Vendored, third-party dependencies for local development

To prepare a .gcloudignore file to address these cases, create a file in your project root with contents such as:

.git
dist
node_modules
vendor
*.jar

Excluding compiled code and third-party dependencies also results in a more consistent build process and a reduced risk of accidental deployment of code that is still under active development.

إرسال تعليقات حول...