Using split cost allocation data with Amazon Managed Service for Prometheus - AWS Data Exports
PrerequisitesForwarding EKS metrics to Amazon Managed Service for PrometheusEstimating your Amazon Managed Service for Prometheus costs

Using split cost allocation data with Amazon Managed Service for Prometheus

Splitting the cost data for Amazon EKS requires that you collect and store metrics from your clusters, including memory and CPU usage. Amazon Managed Service for Prometheus can be used for this purpose.

Once you're opted in to split cost allocation data and your Amazon Managed Service for Prometheus workspace starts receiving the two required metrics (container_cpu_usage_seconds_total and container_memory_working_set_bytes), split cost allocation data recognizes the metrics and uses them automatically.

Note

The two required metrics (container_cpu_usage_seconds_total and container_memory_working_set_bytes) are present in the default Prometheus scrape configuration and the default configuration provided with an AWS managed collector. However, if you customize these configurations, do not relabel, modify, or remove the following labels from the container_cpu_usage_seconds_total and container_memory_working_set_bytes metrics: name, namespace, and pod. If you relabel, modify, or remove these labels, it can impact the ingestion of your metrics.

You can use Amazon Managed Service for Prometheus to collect EKS metrics from a single usage account, in a single Region. The Amazon Managed Service for Prometheus workspace must be in that account and Region. You need one Amazon Managed Service for Prometheus instance for each usage account and Region for which you want to monitor the costs. You can collect metrics for multiple clusters in the Amazon Managed Service for Prometheus workspace, as long as they're in the same usage account and Region.

The following sections describe how to send the correct metrics from your EKS cluster to the Amazon Managed Service for Prometheus workspace.

Prerequisites

As prerequisites for using Amazon Managed Service for Prometheus with split cost allocation data:

  • You need to enable split cost allocation data in the AWS Billing and Cost Management console. For details, see Enabling split cost allocation data. Opting in to split cost allocation data creates a service-linked role in each usage account to query Amazon Managed Service for Prometheus for the Amazon EKS cluster metrics in that account. For more information, see Service-linked roles for split cost allocation data.

  • You need an EKS cluster for which you want to track split cost allocation data. This can be an existing cluster, or you can create a new one. For more information, see Create an Amazon EKS cluster in the Amazon EKS User Guide.

    Note

    You will need the EKS cluster ARN, security group IDs, and at least two subnet IDs (in different availability zones) for use in later steps.

    (optional) Set your EKS cluster’s authentication mode to either API or API_AND_CONFIG_MAP.

  • You need an Amazon Managed Service for Prometheus instance in the same account and Region as your EKS cluster. If you do not already have one, you can create one. For more information on creating an Amazon Managed Service for Prometheus instance, see Create a workspace in the Amazon Managed Service for Prometheus User Guide.

    Note

    You will need the Amazon Managed Service for Prometheus workspace ARN for use in later steps.

Forwarding EKS metrics to Amazon Managed Service for Prometheus

Once you have an EKS cluster and an Amazon Managed Service for Prometheus instance, you can forward the metrics from the cluster to the instance. You can send metrics in two ways.

Option 1: Using an AWS managed collector

Using an AWS managed collector (a scraper) is the simplest way to send metrics from an EKS cluster to an Amazon Managed Service for Prometheus instance. The following procedure steps you through creating an AWS managed collector. For more detailed information, see AWS managed collectors in the Amazon Managed Service for Prometheus User Guide.

Note

AWS managed collectors have a minimum scrape interval of 30 seconds. If you have short-lived pods, the recommendation is to set your scraper interval to 15 seconds. To use a 15 second scraper interval, use option 2 to create your own Prometheus agent.

There are three steps to create an AWS managed collector:

  1. Create a scraper configuration.

  2. Create the scraper.

  3. Configure your EKS cluster to allow the scraper to access metrics.

Step 1: Create a scraper configuration

In order to create a scraper, you must have a scraper configuration. You can use a default configuration, or create your own. The following are three ways to get a scraper configuration:

  • Get the default configuration using the AWS CLI, by calling:

    aws amp get-default-scraper-configuration

  • Create your own configuration. For details, see the Scraper configuration instructions in the Amazon Managed Service for Prometheus User Guide.

  • Copy the sample configuration provided in that same Scraper configuration instructions in the Amazon Managed Service for Prometheus User Guide.

You can edit the scraper configuration, to modify the scrape interval or to filter the metrics that are scraped, for example.

To filter the metrics that are scraped to just include the two that are needed for split cost allocation data, use the following scraper configuration:

scrape_configs:
    - bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
      job_name: kubernetes-nodes-cadvisor
      scrape_interval: 30s
      scrape_timeout: 10s
      kubernetes_sd_configs:
      - role: node
      relabel_configs:
      - regex: (.+)
        replacement: /api/v1/nodes/$1/proxy/metrics/cadvisor
        source_labels:
        - __meta_kubernetes_node_name
        target_label: __metrics_path__
      - replacement: kubernetes.default.svc:443
        target_label: __address__
      metric_relabel_configs:
      - source_labels: [__name__]
        regex: 'container_cpu_usage_seconds_total|container_memory_working_set_bytes'
        action: keep

Once you have the scraper configuration, you must base64 encode it for use in step 2. The configuration is a text YAML file. To encode the file, use a website such as https://www.base64encode.org/.

Step 2: Create the scraper

Now that you have a configuration file, you need to create your scraper. Create a scraper using the following AWS CLI command, based on the variables outlined in the prerequisites section. You must use information from your EKS cluster for the <EKS-CLUSTER-ARN>, <SG-SECURITY-GROUP-ID>, and <SUBNET-ID> fields, replace <BASE64-CONFIGURATION-BLOB> with the scraper configuration you created in the previous step, and replace <AMP_WORKSPACE_ARN> with your Amazon Managed Service for Prometheus workspace ARN.

aws amp create-scraper \ 
--source eksConfiguration="{clusterArn=<EKS-CLUSTER-ARN>,securityGroupIds=[<SG-SECURITY-GROUP-ID>],subnetIds=[<SUBNET-ID>]}" \ 
--scrape-configuration configurationBlob=<BASE64-CONFIGURATION-BLOB> \ 
--destination ampConfiguration={workspaceArn="<AMP_WORKSPACE_ARN>"}

Note down the scraperId that is returned for use in step 3.

Step 3: Configure your EKS cluster to allow the scraper to access metrics

If your EKS cluster’s authentication mode is set to either API or API_AND_CONFIG_MAP, then your scraper will automatically have the correct in-cluster access policy, and the scrapers will have access to your cluster. No further configuration is required, and metrics should be flowing to Amazon Managed Service for Prometheus.

If your EKS cluster’s authentication mode is not set to API or API_AND_CONFIG_MAP, you will need to manually configure the cluster to allow the scraper to access your metrics through a ClusterRole and ClusterRoleBinding. To learn how to enable these permissions, see Manually configuring an EKS cluster for scraper access in the Amazon Managed Service for Prometheus User Guide.

Option 2: Creating your own Prometheus agent

If you can’t use the AWS managed collector, or already have your own Prometheus server, you can use your own Prometheus instance as an agent to scrape metrics from your EKS cluster and send them to Amazon Managed Service for Prometheus.

For detailed instructions on how to use your own Prometheus instance as an agent, see Using a Prometheus instance as a collector in the Amazon Managed Service for Prometheus User Guide.

The following is a sample Prometheus scrape configuration that includes the Prometheus server scrape interval and the container metrics required for split cost allocation data. If you have short-lived pods, the recommendation is to lower the default Prometheus server scrape interval from 30 seconds to 15 seconds. Note that this can result in high Prometheus server memory usage.

scrape_configs:
    - bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
      job_name: kubernetes-nodes-cadvisor
      scrape_interval: 30s
      scrape_timeout: 10s
      kubernetes_sd_configs:
      - role: node
      relabel_configs:
      - regex: (.+)
        replacement: /api/v1/nodes/$1/proxy/metrics/cadvisor
        source_labels:
        - __meta_kubernetes_node_name
        target_label: __metrics_path__
      - replacement: kubernetes.default.svc:443
        target_label: __address__
      metric_relabel_configs:
      - source_labels: [__name__]
        regex: 'container_cpu_usage_seconds_total|container_memory_working_set_bytes'
        action: keep

If you followed Set up ingestion from a new Prometheus server using Helm in the in the Amazon Managed Service for Prometheus User Guide, then you can update your scrape configuration.

To update your scrape configuration

  1. Edit my_prometheus_values_yaml from the guide and include the sample scrape config in the server block.

  2. Run the following command, using prometheus-chart-name and prometheus-namespace from the Amazon Managed Service for Prometheus User Guide.

helm upgrade prometheus-chart-name prometheus-community/prometheus -n prometheus-namespace -f my_prometheus_values_yaml

To learn more about scrape_intervalor how to use a non-global scrape_interval, refer to Prometheus scrape configuration.

Alternatively, you can use the AWS Distro for OpenTelemetry collector that has a Prometheus Receiver, a Prometheus Remote Write Exporter, and the AWS Sigv4 Authentication Extension to achieve remote write access to Amazon Managed Service for Prometheus.

Note

Once you have set up your Prometheus agent, unlike AWS managed collectors, you are responsible for keeping the agent up to date and running to collect metrics.

Estimating your Amazon Managed Service for Prometheus costs

You can use AWS Pricing Calculator to estimate the cost of using Amazon Managed Service for Prometheus for split cost allocation data.

To configure Amazon Managed Service for Prometheus for your estimate

  1. Open AWS Pricing Calculator at https://calculator.aws/#/.

  2. Choose Create estimate.

  3. On the Add service page, enter Amazon Managed Service for Prometheus in the search field, and then choose Configure.

  4. In the Description field, enter a description for your estimate.

  5. Choose a Region.

  6. Select Calculate the cost using your infrastructure details. This option allows you to estimate your ingestion, storage, and query sample costs based on your current or proposed infrastructure setup.

  7. For Number of EC2 instances, enter the total number of EC2 instances across all your clusters for your entire consolidated billing family (including all accounts and Regions). If you use AWS Fargate, use the number of Fargate tasks as a proxy for your EC2 instance count.

  8. Split cost allocation data requires two metrics: container_cpu_usage_seconds_total and container_memory_working_set_bytes. For Prometheus metrics per EC2 instances, enter 2.

  9. Split cost allocation data suggests a scrape interval of 15 seconds. For Metric collection interval (in seconds), enter 15. If you used a different interval (for example, 30 seconds), change this to the interval you set up.

  10. Split cost allocation data does not impose any specific requirements for the other parameters so enter appropriate values for the rest of the input parameters as per your business requirements.

  11. Choose Save and add service.