1. Automating AI Environment Variables with Kubernetes External Secrets


    Automating the management of environment variables for AI applications running on Kubernetes can dramatically simplify operations, especially when sensitive data is involved. Instead of hardcoding credentials or other secrets into your application code or configuration files, you can use Kubernetes Secrets to externally manage this data. However, directly managing Kubernetes Secrets can still pose challenges, such as syncing secrets from external secret stores like AWS Secrets Manager or HashiCorp Vault.

    Pulumi, in conjunction with Kubernetes and external secrets management tools, can help automate the task of syncing these secrets to Kubernetes. External Secrets are custom resources that act as a bridge between external secret stores and Kubernetes. They enable you to manage your secrets in a secure secret store and then declaratively use them in your Kubernetes cluster.

    Below is a Pulumi Python program that demonstrates how you could automate AI environment variables with Kubernetes External Secrets. This program uses a Kubernetes Secret resource to create a new secret in your cluster.

    1. Kubernetes Secret: It's a Kubernetes core API resource used to store and manage sensitive information, such as passwords, OAuth tokens, and ssh keys.

    Before using the following program, make sure you have:

    • The pulumi CLI installed and configured for Python
    • Access to a Kubernetes cluster where you have rights to create resources
    • The pulumi_kubernetes Python module installed
    import pulumi import pulumi_kubernetes as kubernetes # Define the Kubernetes Secret to hold external configuration data. # Pulumi will manage the Secret object in the Kubernetes cluster, # allowing it to be used as environment variables or other configuration data for Pods. ai_environment_secret = kubernetes.core.v1.Secret( "ai-environment-secret", metadata=kubernetes.meta.v1.ObjectMetaArgs( name="ai-environment-variables", ), type="Opaque", # Use 'Opaque' for arbitrary user-defined data string_data={ "API_KEY": "supersecretapikey", # Placeholder, replace with real keys "API_SECRET": "supersecretpassword", # Placeholder, replace with real passwords # ... additional environment variables } ) # Export the Secret name for easy access pulumi.export("ai_secret_name", ai_environment_secret.metadata["name"])

    This example creates a Kubernetes Secret named ai-environment-variables containing two dummy key-value pairs representing an API key and secret. In a real scenario, the string_data should fetch sensitive data from external secrets management systems rather than being hardcoded. The Pulumi program manages this secret in a declarative way, allowing Pods or other Kubernetes resources to reference this secret for their configuration.

    To actually connect to external secrets management systems, you would use an operator specifically designed for this purpose, such as the External Secrets Operator, which currently isn't directly exposed through Pulumi's Kubernetes resources, but can be applied via Pulumi from YAML or custom resource definitions (CRD).

    If you want deeper integration with an external secret management system, such as AWS Secrets Manager or HashiCorp Vault, you may need to define a CustomResource in Pulumi to interact with the CRDs provided by tools like the External Secrets Operator. Integrating these tools would extend beyond the scope of this example and might require specific knowledge of the tool you intend to use.

    Remember, when working with sensitive data, always ensure best security practices, like restricting access to the secrets and following the principle of least privilege.