AI Infrastructure Change Management with AWS Config Rules

Question

Pulumi · Accepted Answer

AWS Config is a fully managed service that provides you with an AWS resource inventory, configuration history, and configuration change notifications to enable security and governance. Config Rules enable you to create rules that automatically check the configuration of AWS resources recorded by AWS Config.

To manage your AWS infrastructure changes with AWS Config Rules, you would typically follow these steps:

1. **Enable AWS Config:** To start using AWS Config, you first need to enable it to record and evaluate your AWS resources' configurations.

2. **Create Config Rules:** Config rules are used to evaluate the configuration settings of your AWS resources. You can create custom rules that run your functions, or use managed rules provided by AWS that represent common best practices.

3. **Evaluate resource configurations:** AWS Config will continuously evaluate your resources as they are created and configured, sending their compliance status based on the rules defined.

4. **Review Compliance:** You can review the compliance status of your resources through the AWS Management Console, or programmatically using AWS SDKs.

For the sake of this instruction, I will provide you with a basic Pulumi program that sets up an AWS Config Rule that checks whether the logging is enabled on an S3 bucket. We assume that you already have an S3 bucket whose logging you want to check.

The steps in the code will include:

- Import the required Pulumi and AWS SDK modules.
- Create an AWS Config Rule.
- Define the source of the Config Rule, which will be a managed rule provided by AWS.
- Deploy the Pulumi stack.

Here is how you would implement it with Pulumi in Python:

```python
import pulumi
import pulumi_aws as aws

# We create an AWS Config Rule to check if S3 bucket logging is enabled.
config_rule = aws.cfg.Rule("s3-bucket-logging-enabled",
    name="s3-bucket-logging-enabled",
    source=aws.cfg.RuleSourceArgs(
        owner="AWS",
        source_identifier="S3_BUCKET_LOGGING_ENABLED",  # This is a managed identifier provided by AWS.
    ),
    # Define further properties of the rule, if required.
)

# The program exports the AWS Config Rule ARN.
pulumi.export("config_rule_arn", config_rule.arn)
```

In this program, we create a `Rule` resource from the `pulumi_aws` package.

- The `source` defines what to evaluate against the rule. In this case, we use `"S3_BUCKET_LOGGING_ENABLED"`, which is a managed rule provided by AWS that checks to ensure that logging is enabled on your S3 buckets.
- `owner` is set to `"AWS"` to indicate that it is an AWS-managed rule.

You can find more details on Config Rules ([AWS Config Rule](https://www.pulumi.com/registry/packages/aws/api-docs/cfg/rule/)) and its managed rule identifiers in the Pulumi Registry documentation.

This program can be extended to include multiple rules, define input parameters, and attach remediation actions. You deploy the code with Pulumi, and it will create the resources in your AWS account. Make sure to have AWS credentials configured for Pulumi CLI to successfully deploy the stack.

The compliance status of your resources against the defined rules can be accessed from the AWS Config console, which provides a dashboard to track your resources' compliance state over time.