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Otterize intents operator

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About

The Otterize intents operator is a tool used to easily automate the creation of network policies and Kafka ACLs in a Kubernetes cluster using a human-readable format, via a custom resource.

Users declare each client's intents to access specific servers (represented as the kind ClientIntents); the operator automatically labels the relevant pods accordingly, and creates the corresponding network policies and Kafka ACLs.

Here is an example of a ClientIntents resource enabling traffic from my-client to web-server and kafka-server:

apiVersion: k8s.otterize.com/v1alpha3
kind: ClientIntents
metadata:
  name: intents-sample
spec:
  service:
    name: my-client
  calls:
    - name: web-server
    - name: kafka-server
      type: kafka

How does the intents operator work?

Network policies

The intents operator automatically creates, updates and deletes network policies, and automatically labels client and server pods, to match declarations in client intents files. The policies created are Ingress-based, so source pods are labeled with a can-access-<target>=true while destination pods are labeled with has-identity=<target>.

The example above results in the following network policy being created:

Name: access-to-web-server
Spec:
  # This label is added to the server by the intents operator
  PodSelector: intents.otterize.com/server=web-server-default-33a0f0
  Allowing ingress traffic:
    To Port: <any> (traffic allowed to all ports)
    From:
      # This label is added to the client by the intents operator
      PodSelector: intents.otterize.com/access-web-server-default-33a0f0=true
  Policy Types: Ingress

For more usage example see the network policy tutorial.

AWS IAM

The intents operator, together with the credentials operator, enables the intent-based declarative management of AWS IAM roles and policies.

To enable AWS access for a pod, follow these steps:

  1. Label a pod to have an AWS role created for it:

    metadata:
 labels:
  "credentials-operator.otterize.com/create-aws-role": "true"

  2. Declare ClientIntents to specify which AWS resources it needs access to:

    apiVersion: k8s.otterize.com/v1alpha3
kind: ClientIntents
metadata:
  name: server
spec:
  service:
    name: server
  calls:
    - name: arn:aws:s3:::otterize-tutorial-bucket-*/*
      type: aws
      awsActions:
        - "s3:PutObject"

Try the AWS IAM tutorial to learn more.

Azure IAM

The intents operator, together with the credentials operator, enables the intent-based declarative management of Azure IAM identities and role assignments.

To enable Azure access for a pod, follow these steps:

  1. Label a pod to have an Azure managed identity created for it:

    metadata:
 labels:
  "credentials-operator.otterize.com/create-azure-workload-identity": "true"

  2. Declare ClientIntents to specify which Azure scopes it needs access to:

    apiVersion: k8s.otterize.com/v1alpha3
kind: ClientIntents
metadata:
  name: server
spec:
  service:
    name: server
  calls:
    # The Azure resource ID that references the resource(s) for the authorization. Subscription & resource group are automatically appended.
    - name: "/providers/Microsoft.Storage/storageAccounts/otterizeazureiamtutorial/blobServices/default/containers/otterizeazureiamtutorialcontainer"
      type: azure
      # one or more Azure roles that will be provided to the specified resources
      azureRoles:
        - "Storage Blob Data Contributor"
    - name: "/providers/Microsoft.KeyVault/vaults/otterizetutorialazureiamkeyvault"
      type: azure
      # Optional - Grant Azure Key Vault data plane access by using Key Vault access policy
      azureKeyVaultPolicy:
        certificatePermissions:
          - "all"
        keyPermissions:
          - "all"
        secretPermissions:
          - "all"
        storagePermissions:
          - "get"
          - "list"

Try the Azure IAM tutorial to learn more.

Google Cloud IAM

The intents operator, together with the credentials operator, enables the intent-based declarative management of Google Cloud service accounts and policies.

To enable Google Cloud access for a pod, follow these steps:

  1. Label a pod to have an GCP service account created for it:

    metadata:
 labels:
  "credentials-operator.otterize.com/create-gcp-sa": "true"

  2. Declare ClientIntents to specify which GCP resources it needs access to:

    apiVersion: k8s.otterize.com/v1alpha3
kind: ClientIntents
metadata:
  name: server
spec:
  service:
    name: server
    calls:
      # The GCP resource name
      # Wildcards can be used in the end of the resource name to match multiple and nested resources
      - name: projects/_/buckets/otterize-demo-bucket*
        type: gcp
        # one or more GCP Roles that will be provided to the specified resources
        gcpPermissions:
          - "storage.admin"
        # Multiple call definitions can be defined for a single service.
      - name: projects/_/buckets/otterize-read-only-bucket*
        type: gcp
        gcpPermissions:
          - "storage.objectViewer"

Try the GCP IAM tutorial to learn more.

Otterize for PostgreSQL & MySQL

Otterize automates PostgreSQL & MySQL access management and secrets for your workloads, all in Kubernetes.

Here is how:

  1. Annotate a pod, requesting a user and a password to be provisioned and bound to the pod, using the following annotation:

    credentials-operator.otterize.com/user-password-secret-name: booking-service-secret`

  2. Apply a PostgreSQLServerConfig or a MySQLServerConfig to the cluster, specifying the database name, user, and password.

    apiVersion: k8s.otterize.com/v1alpha3
kind: PostgreSQLServerConfig
metadata:
  name: bookings
spec:
  address: db.bookings-database.svc.cluster.local:5432
  credentials:
    username: admin
    password: password

  3. Declare your workload’s ClientIntents, specifying desired permissions.

    apiVersion: k8s.otterize.com/v1alpha3
kind: ClientIntents
metadata:
  name: booking-service
  namespace: flight-search
spec:
  service:
    name: booking-service
  calls:
    - name: bookings
      type: database
      databaseResources:
        - databaseName: bookings-db
          table: users
          operations:
            - SELECT
        - databaseName: bookings-db
          table: products
          operations:
            - ALL

Otterize then creates a user and matching grants on the target database.

Try the Just-in-time PostgreSQL users & access or Just-in-time MySQL users & access tutorials to learn more.

Kafka mTLS & ACLs

The intents operator automatically creates, updates, and deletes ACLs in Kafka clusters running within your Kubernetes cluster. It works with the credentials operator to automatically:

  • Establish pod service identities.
  • Generate trusted credentials for each client service.
  • Deliver the credentials to the pod's containers within a locally-mounted volume.

With Kafka, you can also control access to individual topics, like so:

apiVersion: k8s.otterize.com/v1alpha3
kind: ClientIntents
metadata:
  name: kafka-sample
spec:
  service:
    name: my-client
  calls:
    - name: kafka-server
      type: kafka
      kafkaTopics:
        - name: orders
          operations: [ produce ]

Read more about it in the secure Kafka access tutorial.

Istio AuthorizationPolicy

The intents operator automatically creates, updates and deletes Istio authorization policies, automatically looks up service accounts for client pods and labels server pods, to reflect precisely the client-to-server calls declared in client intents files.

The intents operator can also be configured to process client intents without creating and managing network policies, to provide visibility on what would happen once enforcement via Istio authorization policy is activated. More information can be found in the shadow vs active enforcement documentation.

In the example above, the my-client service intends to call the web-server. When the CRD is applied through kubectl apply, the intents operator labels the web-server pod, looks up my-client's service account, and creates an authorization policy for the web-server that references the service account for my-client and allows calls to the web-server from the my-client.

The intents operator uses the resolved identity as the service name, and combines it with the namespace of the pod and hashed to form the value of the label intents.otterize.com/server. This label is used as a selector for servers in Istio authorization policies. The same algorithm is used to look up the client from the service name in the client intents, for whom the service account is looked up.

Finally, an Istio authorization policy is created that allows communication between the client's service account and the server. If the service account covers clients other than the one requested, an event is generated on the ClientIntents to warn about this, and this appears as a warning on Otterize Cloud.

Read more about it in the Istio AuthorizationPolicy tutorial.

Identities

Pods in the cluster are dynamically labeled with their owner's identity. If a ReplicaSet named my-client owns 5 pods and a Deployment named my-server owns 3 pods, and we enable my-client → my-server access via ClientIntents, all 5 source pods would be able to access all 3 target pods.

Pod identities can be overridden by setting the value of the custom annotation intents.otterize.com/service-name to the desired service name. This is useful, for example, for pods without any owner.

Bootstrapping

To bootstrap client intents files for the services running in your cluster, you can use the Otterize network mapper, which automatically detects pod-to-pod calls.

Read more

The Otterize intents operator is a part of Otterize OSS and is an implementation of intent-based access control.

Development

Run the make command inside src/operator directory. Some useful commands are:

  • make build to compile the go code.
  • make deploy to generate Kubernetes Deployment object which deploys the project to your local cluster.

To create a local Docker image, execute make docker-build-local, and deploy it to your local cluster using make deploy-local. For utilizing the locally built Docker image on Minikube running on a VM like macOS arm64, use make minikube-push.

Contributing

  1. Feel free to fork and open a pull request! Include tests and document your code in Godoc style
  2. In your pull request, please refer to an existing issue or open a new one.
  3. Changes to Kubernetes objects will make changes to the Helm chart in the helm-charts repo, which is a submodule in this repository, so you'll need to open a PR there as well.
  4. See our Contributor License Agreement.

Slack

To join the conversation, ask questions, and engage with other users, join the Otterize Slack!

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Usage telemetry

The operator reports anonymous usage information back to the Otterize team, to help the team understand how the software is used in the community and what aspects users find useful. No personal or organizational identifying information is transmitted in these metrics: they only reflect patterns of usage. You may opt out at any time through a single configuration flag.

To disable sending usage information:

  • Via the Otterize OSS Helm chart: --set global.telemetry.enabled=false.
  • Via an environment variable: OTTERIZE_TELEMETRY_ENABLED=false.
  • If running an operator directly: --telemetry-enabled=false.

If the telemetry flag is omitted or set to true, telemetry will be enabled: usage information will be reported.

Read more about it in the Usage telemetry Documentation