1. Observability for AI Services using AWS AMP


    AWS Amplify Managed Prometheus (AMP) is a service that provides secure, scalable, and highly available Prometheus-compatible monitoring and alerting. It is a fully managed service that makes it easy to monitor containerized applications at scale. Observability for AI services using AWS AMP could involve setting up an AMP workspace and configuring metric collection, alerting rules, and potentially integrating with AWS Observability Access Manager (OAM) for secure access management.

    Below is a Pulumi Python program that sets up an AMP workspace and configures an alert manager definition, which is a component of observability. The alert manager handles alerts sent by client applications such as Prometheus and routes them to a receiver such as Slack, PagerDuty, or an Email.

    This program does the following:

    1. Creates an AMP workspace where all the Prometheus server metrics will be stored.
    2. Sets up an AlertManagerDefinition resource to manage alerts within the AMP workspace.
    3. Optionally, it could integrate with OAM for managing access policies, but for simplicity, this program will not include that setup.

    Make sure you have the AWS Pulumi provider configured before running this program.

    import pulumi import pulumi_aws as aws # Create an AMP workspace for observing metrics. # Refer to the documentation: https://www.pulumi.com/registry/packages/aws/api-docs/amp/workspace/ amp_workspace = aws.amp.Workspace("ampWorkspace") # Create an AlertManager definition to handle alerts. # The alert manager's configuration is defined in YAML format, which is standard for Prometheus configurations. # This configuration would be specific to your application's needs. # Refer to the documentation: https://www.pulumi.com/registry/packages/aws/api-docs/amp/alertmanagerdefinition/ alert_manager_config = """ global: resolve_timeout: 5m route: group_by: ['alertname'] group_wait: 10s group_interval: 10s repeat_interval: 1h receiver: 'web.hook' receivers: - name: 'web.hook' webhook_configs: - url: 'http://example.com/' """ alert_manager_definition = aws.amp.AlertManagerDefinition("alertManagerDefinition", workspace_id=amp_workspace.id, definition=alert_manager_config ) # The output is the AMP workspace ID, which you might use to configure your application's Prometheus server. pulumi.export('ampWorkspaceId', amp_workspace.id)

    After running the above program using Pulumi CLI, a workspace will be created in AWS AMP, which you can use for observability over AI Services. The alert manager definition allows you to set exactly how you want to route your alerts.

    If your AI services are running on Kubernetes or are containerized in some way, you would configure the service to export metrics to the AMP workspace. This usually involves configuring your Prometheus server or equivalent to point to your new AMP workspace as a remote write endpoint.

    Please remember that the provided alert manager configuration is basic. For production systems, you would craft a configuration that matches your observability and alerting needs, such as integrating with your incident management systems, setting up proper routing, grouping, and more sophisticated alert definitions.