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AWS Amazon MQ Monitoring via CloudWatch Metrics Stream

Overview​

This guide will walk you through collecting rich telemetry data from your Amazon MQ using CloudWatch Metrics Stream. We recommend using CloudWatch Metrics Stream over Prometheus exporters as it provides faster metric delivery (2-3 minute latency) and is more efficient for AWS services.

Collecting Amazon MQ Metrics​

For collecting Amazon MQ metrics, we recommend using CloudWatch Metrics Stream instead of Prometheus exporters. CloudWatch Metrics Stream provides:

  • Faster delivery: 2-3 minute latency vs 5+ minutes with polling
  • Lower cost: No need to run dedicated exporters
  • Better scalability: Native AWS service integration
  • Automatic metric discovery: No need to manually configure metric lists

Step 1: Set up CloudWatch Metrics Stream​

Follow our comprehensive CloudWatch Metrics Stream guide to set up the infrastructure.

Step 2: Configure Amazon MQ metrics filtering​

When configuring your CloudWatch Metrics Stream in Step 3 of the setup guide, make sure to:

  1. Select specific namespaces instead of "All namespaces"
  2. Choose only AWS/AmazonMQ from the namespace list
  3. This ensures you only collect Amazon MQ metrics, reducing costs and data volume

Step 3: Create OTEL Collector config for RabbitMQ metrics (Optional)​

If you're using RabbitMQ as your broker engine and need detailed broker-specific metrics, create amazon-mq-metrics-collection-config.yaml:

receivers:
  rabbitmq:
    endpoint: ${env:RABBITMQ_ENDPOINT}
    username: ${env:RABBITMQ_USERNAME}
    password: ${env:RABBITMQ_PASSWORD}
    collection_interval: 10s
    metrics:
      rabbitmq.node.disk_free:
        enabled: true
      rabbitmq.node.disk_free_limit:
        enabled: true
      rabbitmq.node.disk_free_alarm:
        enabled: true
      rabbitmq.node.mem_used:
        enabled: true
      rabbitmq.node.mem_limit:
        enabled: true
      rabbitmq.node.mem_alarm:
        enabled: true
      rabbitmq.node.fd_used:
        enabled: true
      rabbitmq.node.fd_total:
        enabled: true
      rabbitmq.node.sockets_used:
        enabled: true
      rabbitmq.node.sockets_total:
        enabled: true
      rabbitmq.node.proc_used:
        enabled: true
      rabbitmq.node.proc_total:
        enabled: true
      rabbitmq.node.disk_free_details.rate:
        enabled: true
      rabbitmq.node.fd_used_details.rate:
        enabled: true
      rabbitmq.node.mem_used_details.rate:
        enabled: true
      rabbitmq.node.proc_used_details.rate:
        enabled: true
      rabbitmq.node.sockets_used_details.rate:
        enabled: true

exporters:
  otlp:
    endpoint: "<SCOUT_ENDPOINT>:4317"
    tls:
      insecure: true

service:
  pipelines:
    metrics/amazon_mq:
      receivers: [rabbitmq]
      exporters: [otlp]

Note: CloudWatch Metrics Stream will automatically deliver AWS/AmazonMQ metrics (CPU utilization, connection counts, message counts, etc.), while the RabbitMQ receiver collects detailed broker-specific metrics if needed.

Collecting Amazon MQ Logs​

The log collection of Amazon MQ requires specifying the list of log group names. From the AWS CloudWatch console, please find the log group(s) relevant to the integration.

Create the Collector config file​

receivers:
  awscloudwatch/amazon_mq_logs:
    region: us-east-1
    logs:
      poll_interval: 1m
      groups:
        named:
          # replace with your Amazon MQ log group name
          /aws/amazonmq/:

processors:
  attributes/add_source_amazon_mq:
    actions:
      - key: source
        value: "amazonMQ"
        action: insert
  batch:
    send_batch_size: 10000
    send_batch_max_size: 11000
    timeout: 10s

exporters:
  otlp:
    endpoint: "<SCOUT_ENDPOINT>:4317"
    tls:
      insecure: false

service:
  pipelines:
    logs/amazonmq:
      receivers: [awscloudwatch/amazon_mq_logs]
      processors: [attributes/add_source_amazon_mq, batch]
      exporters: [otlp]

After deploying these changes, generate some traffic to your Amazon MQ and check in Scout to see your Amazon MQ's metrics and logs.

With this setup, your Amazon MQ broker becomes fully observable through Scout. You'll gain real-time visibility into performance metrics and logs without any changes to your application code.