Using container image digests in Kubernetes manifests

Last reviewed 2023-07-21 UTC

Autopilot Standard

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This tutorial shows developers and operators who deploy containers to Kubernetes how to use container image digests to identify container images. A container image digest uniquely and immutably identifies a container image.

Deploying containers images by using the image digest provides several benefits compared to using image tags. For more information on image digests, see the accompanying document on using container image digests before you continue this tutorial.

The image argument for containers in a Kubernetes Pod specification accepts images with digests. This argument applies everywhere you use a Pod specification, such as in the template section of Deployment, StatefulSet, DaemonSet, ReplicaSet, CronJob, and Job resources.

To deploy an image by using the digest, you use the image name, followed by @sha256: and the digest value. The following is an example of a Deployment resource that uses an image with a digest:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: echo-deployment
spec:
  selector:
    matchLabels:
      app: echo
  template:
    metadata:
      labels:
        app: echo
    spec:
      containers:
      - name: echoserver
        image: gcr.io/google-containers/echoserver@sha256:cb5c1bddd1b5665e1867a7fa1b5fa843a47ee433bbb75d4293888b71def53229
        ports:
        - containerPort: 8080

One downside of using image digests is that you don't know the digest value until after you have published your image to a registry. As you build new images, the digest value changes, and you need a way to update your Kubernetes manifests each time you deploy.

This tutorial shows how you can use tools such as Skaffold, kpt, digester, kustomize, gke-deploy, and ko to use image digests in your manifests.

Recommendations

This document presents several ways to use image digests in Kubernetes deployments. The tools described in this document are complementary. For example, you can use the output of a kpt function with kustomize to create variants for different environments. Skaffold can build images using ko and deploy the images to your Kubernetes clusters using kubectl or kpt.

The reason the tools are complementary is that they perform structured edits based on the Kubernetes resource model (KRM). This model makes the tools pluggable, and you can evolve your use of the tools to create processes and pipelines that help you deploy your apps and services.

To get started, we recommend the approach that works best with your existing tools and processes:

• Skaffold can add digests to image references. You enable this function with a small configuration change. Adopting Skaffold provides additional benefits, such as abstracting away how different tools build and deploy container images.

• By using the digester tool as a mutating admission webhook in your Kubernetes clusters, you can add digests to all your deployments with minimal impact on your current processes for building and deployment container images. The digester webhook also simplifies adoption of Binary Authorization, because it only requires a label to be added to a namespace.

• kpt is a great option if you need a flexible tool to manipulate Kubernetes manifests. The digester tool can be used as a client-side KRM function in a kpt pipeline.

• If you already use kustomize to manage Kubernetes manifests across environments, we recommend that you take advantage of its image transformers to deploy images by digest.

• ko is a great way to build and publish images for Go apps, and it is used by open source projects such as Knative, Tekton, and sigstore.

If you don't use any of the tools described in this document, we recommend that you start with Skaffold and the digester webhook. Skaffold is a common tool used by both developers and release teams, and it integrates with the other tools described in this tutorial. You can take advantage of these integration options as your requirements evolve. The digester Kubernetes webhook complements Skaffold by enabling digest-based deployments for an entire cluster.

Objectives

• Use Skaffold to build and push an image, and to insert the image name and digest in a Kubernetes manifest.
• Use the digester client-side function and mutating admission webhook to add digests to images in Kubernetes Pods and Pod templates.
• Use kpt setters to replace an image tag in a Kubernetes manifest with an image digest.
• Use kustomize to generate a Kubernetes manifest with an image digest.
• Use gke-deploy to resolve an image tag to a digest in a Kubernetes manifest.
• Use ko to build and push an image, and to insert the image name and digest in a Kubernetes manifest.

Costs

In this document, you use the following billable components of Google Cloud:

• Artifact Registry

To generate a cost estimate based on your projected usage, use the pricing calculator. New Google Cloud users might be eligible for a free trial.

When you finish the tasks that are described in this document, you can avoid continued billing by deleting the resources that you created. For more information, see Clean up.

Before you begin

1. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

   Go to project selector

2. Make sure that billing is enabled for your Google Cloud project.

3. Enable the Artifact Registry API.

   Enable the API

4. In the Google Cloud console, activate Cloud Shell.

   Activate Cloud Shell

5. In Cloud Shell, set the default project for Google Cloud CLI:

   gcloud config set project PROJECT_ID
   

   Replace PROJECT_ID with your [project ID].

6. Create a container image repository in Artifact Registry:

   gcloud artifacts repositories create REPOSITORY \
       --location=LOCATION \
       --repository-format=docker
   

   Replace the following:

   • REPOSITORY: the name you want to use for your repository, for instance digest-tutorial.
   • LOCATION: an Artifact Registry location, for instance us-central1.

7. Configure authentication to the Artifact Registry location for the CLI tools used in this tutorial:

   gcloud auth configure-docker LOCATION-docker.pkg.dev
   

Using Skaffold

Skaffold is a command-line tool for continuous development and deployment of applications to Kubernetes clusters.

Use Skaffold to build an image, push the image to Artifact Registry, and replace the image placeholder value in a Kubernetes manifest template with the name, tag, and digest of the pushed image:

1. In Cloud Shell, create and go to a directory to store the files that you create in this section:

   mkdir -p ~/container-image-digests-tutorial/skaffold
   cd ~/container-image-digests-tutorial/skaffold
   

2. Clone the Skaffold Git repository:

   git clone https://github.com/GoogleContainerTools/skaffold.git
   

3. Go to the directory of the getting-started example:

   cd skaffold/examples/getting-started
   

4. Checkout the Git tag that matches your version of Skaffold:

   git checkout $(skaffold version)
   

5. View the skaffold.yaml configuration file:

   cat skaffold.yaml
   

   The file resembles the following:

   apiVersion: skaffold/v4beta6
   kind: Config
   build:
     artifacts:
     - image: skaffold-example
   manifests:
     rawYaml:
     - k8s-pod.yaml

   The build.artifacts section contains a placeholder image name. Skaffold looks for this placeholder in the input manifest files.

   The manifests section tells Skaffold to read an input manifest from the current directory with the name k8s-pod.yaml.

   For an overview of all available options, see the skaffold.yaml reference documentation.

6. View the Kubernetes manifest template:

   cat k8s-pod.yaml
   

   The file is the following:

   apiVersion: v1
   kind: Pod
   metadata:
     name: getting-started
   spec:
     containers:
     - name: getting-started
       image: skaffold-example

   The skaffold-example placeholder value in the image field matches the value of the image field in the skaffold.yaml file. Skaffold replaces this placeholder value with the full image name and digest in the rendered output.

7. Build and push the image to Artifact Registry:

   skaffold build \
       --default-repo=LOCATION-docker.pkg.dev/PROJECT_ID/REPOSITORY \
       --file-output=artifacts.json \
       --interactive=false \
       --push=true \
       --update-check=false
   

   This command uses the following flags:

   • The --file-output flag specifies the file where Skaffold saves information about the built image, including the digest value.
   • The --push flag instructs Skaffold to push the built image to the container image registry specified by the --default-repo flag.
   • The --interactive and --update-check flags are both set to false. Set these flags to false in non-interactive environments, such as build pipelines, but leave them as their default values (true for both flags) for local development.

   If you use Cloud Deploy to deploy to GKE, use the file from the --file-output flag as the value of the --build-artifacts flag when you create a release.

8. Render the expanded Kubernetes manifest with the name, tag, and digest of the container image from the previous step:

   skaffold render \
       --build-artifacts=artifacts.json \
       --digest-source=none \
       --interactive=false \
       --offline=true \
       --output=rendered.yaml \
       --update-check=false
   

   This command uses the following flags:

   • The --build-artifacts flag references the output file from the skaffold build command in the previous step.
   • The --digest-source=none flag means that Skaffold uses the digest value from the file provided in the --build-artifacts flag, instead of resolving the digest from the container image registry.
   • The --offline=true flag means that you can run the command without requiring access to a Kubernetes cluster.
   • The --output flag specifies the output file for the rendered manifest.

9. View the rendered manifest:

   cat rendered.yaml
   

   The output resembles the following:

   apiVersion: v1
   kind: Pod
   metadata:
     name: getting-started
   spec:
     containers:
     - image: LOCATION-docker.pkg.dev/PROJECT_ID/REPOSITORY/skaffold-example:TAG@sha256:DIGEST
       name: getting-started

   In this output, you see the following values:

   • TAG: the tag that Skaffold assigned to the image.
   • DIGEST: the image digest value

Using digester

Digester adds digests to container and init container images in Kubernetes Pod and Pod template specifications. Digester replaces container image references that use tags:

spec:
  containers:
  - image: gcr.io/google-containers/echoserver:1.10

With references that use the image digest:

spec:
  containers:
  - image: gcr.io/google-containers/echoserver:1.10@sha256:cb5c1bddd1b5665e1867a7fa1b5fa843a47ee433bbb75d4293888b71def53229

Digester can run either as a mutating admission webhook in a Kubernetes cluster, or as a client-side KRM function with the kpt or kustomize command-line tools.

Using the digester KRM function

1. In Cloud Shell, create and go to a directory to store the files that you create in this section:

   mkdir -p ~/container-image-digests-tutorial/digester-fn
   cd ~/container-image-digests-tutorial/digester-fn
   

2. Download the digester binary:

   mkdir -p ${HOME}/bin
   export PATH=${HOME}/bin:${PATH}
   DIGESTER_VERSION=$(curl -sL https://api.github.com/repos/google/k8s-digester/releases/latest | jq -r .tag_name)
   curl -L "https://github.com/google/k8s-digester/releases/download/${DIGESTER_VERSION}/digester_$(uname -s)_$(uname -m)" --output ${HOME}/bin/digester
   chmod +x ${HOME}/bin/digester
   

3. Create a Kubernetes Pod manifest that references the image gcr.io/google-containers/echoserver using the tag 1.10:

   cat << EOF > pod.yaml
   apiVersion: v1
   kind: Pod
   metadata:
     name: echo
   spec:
     containers:
     - name: echoserver
       image: gcr.io/google-containers/echoserver:1.10
       ports:
       - containerPort: 8080
   EOF
   

4. Run the digester KRM function using kpt with the manifests in the current directory (.):

   kpt fn eval . --exec digester
   

   When you run this command, kpt performs an in-place update of the manifests in the current directory. If you want kpt to show the updated manifest on the console and leave the manifest file unchanged, add the --output unwrap flag.

5. View the updated manifest:

   cat pod.yaml
   

   The file is the following:

   apiVersion: v1
   kind: Pod
   metadata:
     name: echo
   spec:
     containers:
       - name: echoserver
         image: gcr.io/google-containers/echoserver:1.10@sha256:cb5c1bddd1b5665e1867a7fa1b5fa843a47ee433bbb75d4293888b71def53229
         ports:
           - containerPort: 8080

Using the digester admission webhook

1. In Cloud Shell, create and go to a directory to store the files that you create in this section:

   mkdir -p ~/container-image-digests-tutorial/digester-webhook
   cd ~/container-image-digests-tutorial/digester-webhook
   

2. Create a local Kubernetes cluster using kind:

   kind create cluster
   

   kind is a command-line tool to run local Kubernetes clusters using Docker.

3. Deploy the digester webhook:

   DIGESTER_VERSION=$(curl -sL https://api.github.com/repos/google/k8s-digester/releases/latest | jq -r .tag_name)
   kustomize build "https://github.com/google/k8s-digester.git/manifests?ref=${DIGESTER_VERSION}" | kubectl apply -f -
   

4. Create a Kubernetes namespace called digester-demo in the kind cluster:

   kubectl create namespace digester-demo
   

5. Add the digest-resolution: enabled label to the digester-demo namespace:

   kubectl label namespace digester-demo digest-resolution=enabled
   

   The digester webhook adds digests to Pods in namespaces with this label.

6. Create a Kubernetes Deployment manifest that references the image gcr.io/google-containers/echoserver using the tag 1.10:

   cat << EOF > deployment.yaml
   apiVersion: apps/v1
   kind: Deployment
   metadata:
     name: echo-deployment
   spec:
     selector:
       matchLabels:
         app: echo
     template:
       metadata:
         labels:
           app: echo
       spec:
         containers:
         - name: echoserver
           image: gcr.io/google-containers/echoserver:1.10
           ports:
           - containerPort: 8080
   EOF
   

7. Apply the manifest in the digester-demo namespace:

   kubectl apply --filename deployment.yaml --namespace digester-demo \
       --output jsonpath='{.spec.template.spec.containers[].image}{"\n"}'
   

   The --output flag instructs kubectl to output the image name to the console, followed by a newline character. The output is the following:

   gcr.io/google-containers/echoserver:1.10@sha256:cb5c1bddd1b5665e1867a7fa1b5fa843a47ee433bbb75d4293888b71def53229

   This output shows that the digester webhook added the image digest to the Pod template specification in the Deployment resource.

8. Delete the kind cluster to free up resources in your Cloud Shell session:

   kind delete cluster
   

Using kpt setters

kpt is a command-line tool to manage, manipulate, customize, and apply Kubernetes resource manifests.

You can use the create-setters and apply-setters KRM functions from the kpt Functions Catalog to update image digests in your Kubernetes manifests when you build new images.

1. In Cloud Shell, create and go to a directory to store the files that you create in this section:

   mkdir -p ~/container-image-digests-tutorial/kpt
   cd ~/container-image-digests-tutorial/kpt
   

2. Create a kpt package in the current directory:

   kpt pkg init --description "Container image digest tutorial"
   

3. Create a Kubernetes Pod manifest that references the image gcr.io/google-containers/echoserver using the tag 1.10:

   cat << EOF > pod.yaml
   apiVersion: v1
   kind: Pod
   metadata:
     name: echo
   spec:
     containers:
     - name: echoserver
       image: gcr.io/google-containers/echoserver:1.10
       ports:
       - containerPort: 8080
   EOF
   

4. Use kpt to create a setter called echoimage for the manifest field, where the existing value is gcr.io/google-containers/echoserver:1.10:

   kpt fn eval . \
       --image gcr.io/kpt-fn/create-setters@sha256:0220cc87f29ff9abfa3a3b5643aa50f18d355d5e9dc9e1f518119633ddc4895c \
       -- "echoimage=gcr.io/google-containers/echoserver:1.10"
   

5. View the manifest:

   cat pod.yaml
   

   The file is the following:

   apiVersion: v1
   kind: Pod
   metadata:
     name: echo
   spec:
     containers:
     - name: echoserver
       image: gcr.io/google-containers/echoserver:1.10 # kpt-set: ${echoimage}
       ports:
       - containerPort: 8080

6. Get the digest value of the container image:

   DIGEST=$(gcloud container images describe \
       gcr.io/google-containers/echoserver:1.10 \
       --format='value(image_summary.digest)')
   

7. Set the new field value:

   kpt fn eval . \
       --image gcr.io/kpt-fn/apply-setters@sha256:4d4295727183396f0c3c6a75d2560254c2f9041a39e95dc1e5beffeb49cc1a12 \
       -- "echoimage=gcr.io/google-containers/echoserver:1.10@$DIGEST"
   

   When you run this command, kpt performs an in-place replacement of the image field value in the manifest.

8. View the updated manifest:

   cat pod.yaml
   

   The file is the following:

   apiVersion: v1
   kind: Pod
   metadata:
     name: echo
   spec:
     containers:
     - name: echoserver
       image: gcr.io/google-containers/echoserver:1.10@sha256:cb5c1bddd1b5665e1867a7fa1b5fa843a47ee433bbb75d4293888b71def53229 # kpt-set: ${echoimage}
       ports:
       - containerPort: 8080

Using kustomize image transformers

kustomize is a command-line tool that lets you customize Kubernetes manifests by using overlays, patches, and transformers.

You can use the kustomize image transformer to update the image name, tag, and digest in your existing manifest.

The following kustomization.yaml snippet shows you how to configure the image transformer to use the transformer digest value for images where the Pod specification image value matches the transformer name value:

images:
- name: gcr.io/google-containers/echoserver
  digest: sha256:cb5c1bddd1b5665e1867a7fa1b5fa843a47ee433bbb75d4293888b71def53229

To use a kustomize image transformer with an image digest, do the following:

1. In Cloud Shell, create and go to a directory to store the files that you create in this section:

   mkdir -p ~/container-image-digests-tutorial/kustomize
   cd ~/container-image-digests-tutorial/kustomize
   

2. Create a kustomization.yaml file:

   kustomize init
   

3. Create a Kubernetes manifest with a Pod specification that references the image gcr.io/google-containers/echoserver using the tag 1.10:

   cat << EOF > pod.yaml
   apiVersion: v1
   kind: Pod
   metadata:
     name: echo
   spec:
     containers:
     - name: echoserver
       image: gcr.io/google-containers/echoserver:1.10
       ports:
       - containerPort: 8080
   EOF
   

4. Add the manifest as a resource in the kustomization.yaml file:

   kustomize edit add resource pod.yaml
   

5. Use an image transformer to update the digest of the image:

   kustomize edit set image \
       gcr.io/google-containers/echoserver@sha256:cb5c1bddd1b5665e1867a7fa1b5fa843a47ee433bbb75d4293888b71def53229
   

6. View the image transformer in the kustomization.yaml file:

   cat kustomization.yaml
   

   The file is the following:

   apiVersion: kustomize.config.k8s.io/v1beta1
   kind: Kustomization
   resources:
   - pod.yaml
   images:
   - digest: sha256:cb5c1bddd1b5665e1867a7fa1b5fa843a47ee433bbb75d4293888b71def53229
     name: gcr.io/google-containers/echoserver

7. View the resulting manifest:

   kustomize build .
   

   The output is the following:

   apiVersion: v1
   kind: Pod
   metadata:
     name: echo
   spec:
     containers:
     - image: gcr.io/google-containers/echoserver@sha256:cb5c1bddd1b5665e1867a7fa1b5fa843a47ee433bbb75d4293888b71def53229
       name: echoserver
       ports:
       - containerPort: 8080

8. To run the kustomize transformer and apply the resulting manifest to a Kubernetes cluster in one step, you can use the kubectl apply command with the --kustomize flag:

   kubectl apply --kustomize .
   

   If you want to apply the output later, you can redirect the output of the kustomize build command to a file.

Using gke-deploy

gke-deploy is a command-line tool that you use with Google Kubernetes Engine (GKE). gke-deploy wraps the kubectl command-line tool and can modify the resources that you create following Google's recommended practices.

If you use the gke-deploy sub-commands prepare or run, gke-deploy resolves your image tags to digests and saves the expanded manifests with the image digests in the file output/expanded/aggregated-resources.yaml by default.

You can use gke-deploy run to both substitute the image tag for a digest and apply the expanded manifest to your GKE cluster. Although this command is convenient, there is a downside: the image tag is substituted at deployment time. The image associated with the tag might have changed in the time between when you decided to deploy, and when you deployed, resulting in deploying an unexpected image. For production deployments, we recommend separate steps for generating and applying manifests.

To replace an image tag in a Kubernetes deployment manifest with the image digest, do the following:

1. In Cloud Shell, create and go to a directory to store the files that you create in this section:

   mkdir -p ~/container-image-digests-tutorial/gke-deploy
   cd ~/container-image-digests-tutorial/gke-deploy
   

2. Install gke-deploy:

   go install github.com/GoogleCloudPlatform/cloud-builders/gke-deploy@latest
   

3. Create a Kubernetes Deployment manifest that references the image gcr.io/google-containers/echoserver using the tag 1.10:

   cat << EOF > deployment.yaml
   apiVersion: apps/v1
   kind: Deployment
   metadata:
     name: echo-deployment
   spec:
     selector:
       matchLabels:
         app: echo
     template:
       metadata:
         labels:
           app: echo
       spec:
         containers:
         - name: echoserver
           image: gcr.io/google-containers/echoserver:1.10
           ports:
           - containerPort: 8080
   EOF
   

4. Generate an expanded manifest based on the deployment.yaml manifest:

   gke-deploy prepare \
       --filename deployment.yaml \
       --image gcr.io/google-containers/echoserver:1.10 \
       --version 1.10
   

5. View the expanded manifest:

   cat output/expanded/aggregated-resources.yaml
   

   The output is the following:

   apiVersion: apps/v1
   kind: Deployment
   metadata:
     labels:
       app.kubernetes.io/managed-by: gcp-cloud-build-deploy
       app.kubernetes.io/version: "1.10"
     name: echo-deployment
     namespace: default
   spec:
     selector:
       matchLabels:
         app: echo
     template:
       metadata:
         labels:
           app: echo
           app.kubernetes.io/managed-by: gcp-cloud-build-deploy
           app.kubernetes.io/version: "1.10"
       spec:
         containers:
         - image: gcr.io/google-containers/echoserver@sha256:cb5c1bddd1b5665e1867a7fa1b5fa843a47ee433bbb75d4293888b71def53229
           name: echoserver
           ports:
           - containerPort: 8080

   In the expanded manifest, the image tag is replaced by the digest.

   The --version argument you used with the gke-deploy command sets the value of the app.kubernetes.io/version label in the deployment and the Pod template metadata of the expanded manifest.

   To learn how to use gke-deploy with Cloud Build, see the Cloud Build documentation for gke-deploy.

Using ko

ko is a command-line tool and library for building Go container images and deploying them to Kubernetes clusters. ko builds images without using the Docker daemon, so you can use it in environments where you can't install Docker.

The ko sub-command build builds images and publishes them to a container image registry or loads them into your local Docker daemon.

The ko sub-command resolve does the following:

• Identifies the images to build by finding placeholders in the image fields of the Kubernetes manifests that you provide by using the --filename argument.
• Builds and publishes your images.
• Replaces the image value placeholders with the names and digests of the images it built.
• Prints the expanded manifests.

The ko sub-commands apply, create, and run perform the same steps as resolve, and then execute kubectl apply, create, or run with the expanded manifests.

To build an image from Go source code, and add the digest of the image to a Kubernetes deployment manifest, do the following

1. In Cloud Shell, create and go to a directory to store the files that you create in this section:

   mkdir -p ~/container-image-digests-tutorial/ko
   cd ~/container-image-digests-tutorial/ko
   

2. Download ko and add it to your PATH:

   mkdir -p ${HOME}/bin
   export PATH=${HOME}/bin:${PATH}
   KO_VERSION=$(curl -sL https://api.github.com/repos/ko-build/ko/releases/latest | jq -r .tag_name | cut -c2-)
   curl -L "https://github.com/ko-build/ko/releases/download/v${KO_VERSION}/ko_${KO_VERSION}_$(uname -s)_$(uname -m).tar.gz" | tar -zxC ${HOME}/bin ko
   

3. Create a Go app with the module name example.com/hello-world in a new directory called app:

   mkdir -p app/cmd/ko-example
   
   cd app
   
   go mod init example.com/hello-world
   
   cat << EOF > cmd/ko-example/main.go
   package main
   
   import "fmt"
   
   func main() {
       fmt.Println("hello world")
   }
   EOF
   

4. Define the image repository that ko uses to publish images:

   export KO_DOCKER_REPO=LOCATION-docker.pkg.dev/PROJECT_ID/REPOSITORY
   

   This example uses Artifact Registry, but you can use ko with a different container image registry.

5. To build and publish an image for your app, do one of the following steps:

   • Build and publish an image for your app by providing the path to your Go main package:

     ko build --base-import-paths ./cmd/ko-example
     

     The optional argument --base-import-paths means that ko uses the short name of the main package directory as the image name.

     ko prints the image name and digest to stdout in the following format:

     LOCATION-docker.pkg.dev/PROJECT_ID/ko-example@sha256:DIGEST

     In this output, DIGEST is the image digest value.

     Note: All other ko output goes to stderr. If you want to capture the image name and digest, you can capture stdout in an environment variable:

     IMAGE_AND_DIGEST=$(ko build --base-import-paths ./cmd/ko-example)
     

   • Use ko to replace a manifest placeholder with the name and digest of the image it builds and publishes:

     1. Create a Kubernetes Pod manifest. The manifest uses the placeholder ko://IMPORT_PATH_OF_YOUR_MAIN_PACKAGE as the value of the image field:

        cat << EOF > ko-pod.yaml
        apiVersion: v1
        kind: Pod
        metadata:
          name: ko-example
        spec:
          containers:
          - name: hello-world
            image: ko://example.com/hello-world/cmd/ko-example
        EOF
        

     2. Build and publish an image for your app, and replace the manifest placeholder with the image name and digest:

        ko resolve --base-import-paths --filename ko-pod.yaml
        

        ko prints the manifest with the image name and digest to stdout:

        apiVersion: v1
        kind: Pod
        metadata:
          name: ko-example
        spec:
          containers:
          - name: hello-world
            image: LOCATION-docker.pkg.dev/PROJECT_ID/ko-example@sha256:DIGEST

        In this output, DIGEST is the image digest value.

Clean up

The easiest way to eliminate billing is to delete the Google Cloud project that you created for the tutorial. Alternatively, you can delete the individual resources.

Delete the project

Caution: Deleting a project has the following effects:
• Everything in the project is deleted. If you used an existing project for the tasks in this document, when you delete it, you also delete any other work you've done in the project.
• Custom project IDs are lost. When you created this project, you might have created a custom project ID that you want to use in the future. To preserve the URLs that use the project ID, such as an appspot.com URL, delete selected resources inside the project instead of deleting the whole project.
1. In the Google Cloud console, go to the Manage resources page.

   Go to Manage resources

2. In the project list, select the project that you want to delete, and then click Delete.
3. In the dialog, type the project ID, and then click Shut down to delete the project.

Delete the resources

If you want to keep the Google Cloud project that you used in this tutorial, delete the individual resources:

1. In Cloud Shell, delete the files you created in this tutorial:

   cd
   rm -rf ~/container-image-digests-tutorial
   

2. Delete the container image repository in Artifact Registry:

   gcloud artifacts repositories delete REPOSITORY \
       --location=LOCATION --async --quiet
   

What's next

• Learn more about container image digests.
• Learn more about the digester client-side KRM function and Kubernetes mutating webhook.
• Explore GitOps-style continuous delivery with Cloud Build.