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EMR Instances Should Use Latest Generation

More Info:​

Ensure that all Amazon Elastic MapReduce (EMR) clusters provisioned within your AWS account are using the latest generation of instances in order to get better performance at lower cost.

Risk Level​

Medium

Address​

Cost Optimisation, Security

Compliance Standards​

  • CSA Cloud Controls Matrix v4
  • Cloudanix Best Practice
  • Digital Operational Resilience Act (EU)
  • MAS Technology Risk Management (Singapore)
  • UK NCSC Cyber Assessment Framework

Triage and Remediation​

Remediation​

Using Console

To remediate the misconfiguration of EMR instances not using the latest generation in AWS, you can follow these steps using the AWS Management Console:

  1. Access the AWS Management Console:

  2. Navigate to Amazon EMR Service:

    • Click on the "Services" dropdown menu at the top left corner.
    • Under the "Analytics" section, click on "EMR" to access the Amazon EMR service.

  3. Identify the EMR Cluster:

    • In the Amazon EMR dashboard, identify the EMR cluster that you want to update to use the latest generation of instances.

  4. Modify the EMR Cluster:

    • Select the EMR cluster by clicking on the checkbox next to it.
    • Click on the "Modify" button at the top of the dashboard to modify the cluster configuration.

  5. Update Instance Types:

    • In the "Hardware Configuration" section, you will see the current instance types being used by the cluster nodes.
    • Click on the "Edit" button next to the instance types to update them.

  6. Select Latest Generation Instance Types:

    • In the instance types selection window, choose the latest generation instance types available in the dropdown menu.
    • Select the instance types that meet your requirements in terms of performance, capacity, and cost.

  7. Save Changes:

    • After selecting the new instance types, click on the "Save" or "Update" button to apply the changes to the EMR cluster.

  8. Monitor Cluster Status:

    • Once the changes are saved, monitor the cluster status to ensure that the new instance types are provisioned and the cluster is running successfully.

By following these steps, you can remediate the misconfiguration of EMR instances not using the latest generation in AWS and update your EMR cluster to use the latest generation of instances for improved performance and efficiency.

Using CLI

To remediate the misconfiguration of EMR instances not using the latest generation for AWS Redshift using AWS CLI, follow these steps:

  1. List the existing EMR instances to identify the instance types that are not using the latest generation:
aws emr list-clusters --query "Clusters[*].[Id, Name, Status.State, Ec2InstanceAttributes.InstanceType]" --output table

  1. Identify the instance types that are not using the latest generation and note down the cluster ID.

  2. Modify the EMR cluster configuration to use the latest generation instance type. You can do this by modifying the cluster using the following command:

aws emr modify-instance-fleet --cluster-id <cluster-id> --instance-fleet InstanceFleetType=MASTER,TargetOnDemandCapacity=1,InstanceTypeConfigs=[{InstanceType=<latest-instance-type>}]

Replace <cluster-id> with the actual cluster ID noted in step 2 and <latest-instance-type> with the latest generation instance type you want to use.

  1. Verify the changes by listing the EMR instances again:
aws emr list-clusters --query "Clusters[*].[Id, Name, Status.State, Ec2InstanceAttributes.InstanceType]" --output table

By following these steps, you can remediate the misconfiguration of EMR instances not using the latest generation for AWS Redshift using AWS CLI.

Using Python

To remediate the misconfiguration of EMR instances not using the latest generation for AWS Redshift using Python, you can follow these steps:

  1. Use the AWS SDK for Python (Boto3) to interact with AWS services programmatically. Make sure you have Boto3 installed in your Python environment.

  2. Write a Python script to identify the existing EMR instances that are not using the latest generation.

  3. Update the configuration of the existing EMR instances to use the latest generation.

Here is a sample Python script to remediate this misconfiguration:

import boto3

# Initialize the EMR client
emr_client = boto3.client('emr', region_name='your_region')

# Get a list of existing EMR clusters
response = emr_client.list_clusters()

# Iterate through each cluster
for cluster in response['Clusters']:
    cluster_id = cluster['Id']
    
    # Describe the cluster to get detailed information
    cluster_details = emr_client.describe_cluster(ClusterId=cluster_id)
    
    # Check if the instance type is not the latest generation
    if cluster_details['Instances']['MasterInstanceType'] != 'm5.xlarge':
        # Update the cluster to use the latest generation instance type
        emr_client.modify_instance_fleet(ClusterId=cluster_id, InstanceFleet= {
            'InstanceFleetType': 'MASTER',
            'TargetOnDemandCapacity': 1,
            'InstanceTypeConfigs': [
                {
                    'InstanceType': 'm5.xlarge'
                }
            ]
        })
        
        print(f"Updated EMR cluster {cluster_id} to use the latest generation instance type.")

Make sure to replace 'your_region' with the appropriate AWS region where your EMR clusters are located. Also, adjust the instance type ('m5.xlarge') to the latest generation instance type that you want to use.

Run this script periodically or integrate it into your existing automation workflows to ensure that all EMR instances are using the latest generation.

Using Terraform
resource "aws_redshift_cluster" "this" {
  cluster_identifier = "REDSHIFT_CLUSTER_IDENTIFIER" # e.g. "analytics-prod"

  # Use a latest-generation node type (RA3 family at time of writing).
  # Replace LATEST_GENERATION_NODE_TYPE with a valid RA3 type, e.g. "ra3.xlplus" or "ra3.4xlarge".
  node_type = "LATEST_GENERATION_NODE_TYPE"

  master_username = "MASTER_USERNAME"
  master_password = "MASTER_PASSWORD"

  number_of_nodes = 2
  cluster_type    = "multi-node"

  # ...any other required arguments...
}

Substitute:

  • REDSHIFT_CLUSTER_IDENTIFIER with your cluster name.
  • LATEST_GENERATION_NODE_TYPE with a current-generation Redshift node type (for example, ra3.xlplus, ra3.4xlarge, or ra3.16xlarge, depending on workload and region).
  • MASTER_USERNAME / MASTER_PASSWORD with your credentials (or use aws_redshift_cluster + AWS Secrets Manager integration as appropriate).

Changing node_type on an existing aws_redshift_cluster forces replacement of the cluster; this is an outage and you must rely on snapshots/backups to avoid data loss.

Verification: terraform plan should show the aws_redshift_cluster.this resource being replaced with node_type changing from the older generation (for example, dc2.large or ds2.xlarge) to your chosen RA3 latest-generation node type.