1. Centralized Tunning Parameters Storage with Kubernetes ConfigMaps


    In Kubernetes, ConfigMaps are key-value pairs that can be used to store non-confidential data in a centralized way. They allow you to decouple configuration artifacts from image content to keep containerized applications portable. This is useful for storing feature flags, configuration files, command-line arguments, and environment-specific parameters.

    Using ConfigMaps, you can change the configuration of your Kubernetes applications without changing the code of the application and without the need to recreate the container images. This makes your applications easier to configure and manage across different environments like development, staging, and production.

    Here's a basic Pulumi program in Python that demonstrates how to create a Kubernetes ConfigMap to store centralized tuning parameters:

    import pulumi import pulumi_kubernetes as kubernetes # Create a Kubernetes ConfigMap to store tuning parameters tuning_params_config_map = kubernetes.core.v1.ConfigMap( "tuning-params-cm", metadata=kubernetes.meta.v1.ObjectMetaArgs( name="tuning-params" # Name of the ConfigMap ), data={ "workerCount": "5", # Parameter key-value pair "maxConnections": "100", # Parameter key-value pair "logLevel": "info" # Parameter key-value pair } ) # Export the name of the ConfigMap pulumi.export("config_map_name", tuning_params_config_map.metadata["name"])
    • We start by importing Pulumi and the Kubernetes package for Pulumi.
    • We define a ConfigMap resource using the kubernetes.core.v1.ConfigMap class.
    • The metadata field is set with name to specify the ConfigMap's name.
    • The data field includes the key-value pairs with the tuning parameters you want to store.
    • Finally, we export the name of the ConfigMap to easily retrieve it later, for example when deploying other resources that might reference these configuration values.

    To apply this Pulumi program:

    1. Ensure you have Pulumi CLI installed and configured with access to your Kubernetes cluster.
    2. Save this Python code to a file, for example, config_map.py.
    3. Run pulumi up in the command line from the directory where you saved the file to apply the Pulumi code to your Kubernetes cluster.

    This code example doesn't contain any sensitive information in the ConfigMap, but if you need to manage secrets, you should use Kubernetes Secret objects instead. Pulumi also supports the creation of Secret objects if you need to store sensitive data.