AWS S3 Workroom Storage

Kamiwaza uses S3-compatible object storage for two platform workflows:

• workroom context file persistence
• Skills Library package import and download

If object storage is not configured, file-backed user workflows can fail with errors such as:

Workroom storage is not configured for Skills Library.

Use this guide when your deployment stores workroom content in AWS S3.

When You Need This

Configure AWS S3 if you want any of the following to work reliably:

• context file upload and persistence
• Skills Library package import
• Skills Library package download

Prerequisites

Before you start, make sure you have:

• an AWS S3 bucket
• an IAM user or role with access to that bucket
• kubectl access to the target cluster
• a values override file for the deployment configuration

The IAM identity should be allowed to perform at least:

• s3:ListBucket
• s3:GetObject
• s3:PutObject
• s3:DeleteObject

Configuration Model

The core chart exposes a single object-storage configuration block:

context:
  objectStorage:
    defaultBucket: ""
    defaultRegion: ""
    defaultPrefix: "context/raw"
    endpointUrl: ""
    credentialsSecretRef:
      name: ""
      accessKeyIdKey: "access_key_id"
      secretAccessKeyKey: "secret_access_key"
      sessionTokenKey: "session_token"

This configuration is rendered into:

• the core-config ConfigMap for non-secret S3 settings
• the core-scheduler deployment for secret-backed AWS credentials
• the Ray head and worker pods for the same credentials

Option 1: Static AWS Access Keys

Use this option when your cluster does not already provide AWS credentials to the pods.

1. Create a Kubernetes Secret

Create a Secret in the kamiwaza namespace:

kubectl create secret generic core-s3 \
  -n kamiwaza \
  --from-literal=access_key_id="<aws-access-key-id>" \
  --from-literal=secret_access_key="<aws-secret-access-key>"

If you are using temporary session credentials, include the session token:

kubectl create secret generic core-s3 \
  -n kamiwaza \
  --from-literal=access_key_id="<aws-access-key-id>" \
  --from-literal=secret_access_key="<aws-secret-access-key>" \
  --from-literal=session_token="<aws-session-token>"

2. Prepare a Configuration Override

Create a configuration override file for your deployment workflow, for example aws-s3.yaml:

context:
  objectStorage:
    defaultBucket: "my-kamiwaza-artifacts"
    defaultRegion: "us-west-2"
    defaultPrefix: "context/raw"
    credentialsSecretRef:
      name: "core-s3"
      accessKeyIdKey: "access_key_id"
      secretAccessKeyKey: "secret_access_key"
      sessionTokenKey: "session_token"

For AWS S3, leave endpointUrl empty.

3. Apply the Updated Configuration

Apply the updated values through your standard Helm or cluster release workflow.

Option 2: Ambient AWS Credentials

Use this option if your cluster already provides AWS credentials to pods through IAM roles or another AWS-native mechanism.

In this case, do not create a Secret. Only set the bucket and region:

context:
  objectStorage:
    defaultBucket: "my-kamiwaza-artifacts"
    defaultRegion: "us-west-2"
    defaultPrefix: "context/raw"
    credentialsSecretRef:
      name: ""

Apply the updated values through your standard Helm or cluster release workflow.

Restart Existing Deployments

If the cluster is already running, restart the core workloads after applying the updated config:

kubectl rollout restart deployment/core-scheduler -n kamiwaza
kubectl delete pod -n kamiwaza -l ray.io/node-type=head
kubectl delete pod -n kamiwaza -l ray.io/node-type=worker

The Ray operator recreates the deleted head and worker pods.

Verify the Configuration

Check the ConfigMap

Verify that the non-secret S3 settings are present:

kubectl get configmap core-config -n kamiwaza -o yaml | grep CONTEXT_SERVICE_S3

You should see values like:

CONTEXT_SERVICE_S3_DEFAULT_BUCKET: my-kamiwaza-artifacts
CONTEXT_SERVICE_S3_DEFAULT_REGION: us-west-2
CONTEXT_SERVICE_S3_DEFAULT_PREFIX: context/raw

Check the Scheduler Pod

Verify the scheduler sees the expected environment variables:

kubectl exec -n kamiwaza deploy/core-scheduler -- env | grep CONTEXT_SERVICE_S3

If you are using Secret-backed credentials, also verify the credential variables exist:

kubectl exec -n kamiwaza deploy/core-scheduler -- env | grep '^CONTEXT_SERVICE_S3_'

Check the Ray Head Pod

Verify the Ray head pod also has the S3 configuration:

kubectl exec -n kamiwaza "$(kubectl get pod -n kamiwaza -l ray.io/node-type=head -o name | head -1)" -- env | grep CONTEXT_SERVICE_S3

Validate in the Product

Retry a workflow that depends on workroom storage:

• import a Skills Library package
• upload a context file
• reopen the affected workflow and confirm the asset is still available

Troubleshooting

Error: Workroom storage is not configured for Skills Library

This usually means core does not see CONTEXT_SERVICE_S3_DEFAULT_BUCKET.

Check:

• your Helm values file includes context.objectStorage.defaultBucket
• the core-config ConfigMap contains CONTEXT_SERVICE_S3_DEFAULT_BUCKET
• the scheduler and Ray pods were restarted after the config change

Error: Unable to locate credentials

This means the bucket settings are present but AWS authentication is not.

Check:

• the Secret exists in the kamiwaza namespace
• credentialsSecretRef.name matches the Secret name
• the Secret keys match the configured key names
• the scheduler and Ray pods were restarted after the Secret was created

Error: AccessDenied or SignatureDoesNotMatch

This usually means the credentials are present but not valid for the target bucket or region.

Check:

• the bucket name
• the AWS region
• the IAM policy attached to the user or role
• whether the credentials belong to the AWS account that owns the bucket

Security Notes

• Do not store AWS secrets in workroom attributes or user-editable metadata.
• Prefer Kubernetes Secrets or ambient AWS identity over plain-text credentials in values files.
• Leave endpointUrl empty for AWS S3. Set it only when using a non-AWS S3-compatible service.