Amazon Elastic Inference

Dynatrace ingests metrics for multiple preselected namespaces, including Amazon Elastic Inference. You can view graphs per service instance, with a set of dimensions, and create custom graphs that you can pin to your dashboards.

Prerequisites

To enable monitoring for this service, you need

  • An Environment or Cluster ActiveGate version 1.197+
  • Dynatrace version 1.200+
  • An updated AWS monitoring policy to include the additional AWS services.
    To update the AWS IAM policy, use the JSON below, containing the monitoring policy (permissions) for all supporting services.

If you don't want to add permissions to all services, and just select permissions for certain services, consult the table below. The table contains a set of permissions that are required for all services (All monitored Amazon services) and, for each supporting service, a list of optional permissions specific to that service.

Example of JSON policy for one single service.

In this example, from the complete list of permissions you need to select

  • "apigateway:GET" for Amazon API Gateway
  • "cloudwatch:GetMetricData", "cloudwatch:GetMetricStatistics", "cloudwatch:ListMetrics", "sts:GetCallerIdentity", "tag:GetResources", "tag:GetTagKeys", and "ec2:DescribeAvailabilityZones" for All monitored Amazon services.

Enable monitoring

To enable monitoring for this service, you first need to integrate Dynatrace with Amazon Web Services:

Add the service to monitoring

In order to view the service metrics, you must add the service to monitoring in your Dynatrace environment.

Cloud-service monitoring consumption

Beginning in early 2021, all cloud services will consume Davis Data Units (DDUs). The amount of DDU consumption per service instance depends on the number of monitored metrics and their dimensions (each metric dimension results in the ingestion of 1 data point; 1 data point consumes 0.001 DDUs). For DDU consumption estimates per service instance (recommended metrics only, predefined dimensions, and assumed dimension values), see DDU consumption estimates for per cloud service instance.

Monitor resources based on tags

You can choose to monitor resources based on existing AWS tags, as Dynatrace automatically imports them from service instances. Nevertheless, the transition from AWS to Dynatrace tagging isn't supported for all AWS services. Expand the table below to see which supporting services are filtered by tagging.

To monitor resources based on tags

  1. Go to Settings > Cloud and virtualization > AWS and select the AWS instance.
  2. For Resource monitoring method, select Monitor resources based on tags.
  3. Enter the Key and Value.
  4. Select Save.

tags-aws

Configure service metrics

Once you add a service, Dynatrace starts automatically collecting a suite of metrics for this particular service. These are recommended metrics.

Recommended metrics:

  • Are enabled by default
  • Can't be disabled
  • Can have recommended dimensions (enabled by default, can't be disabled)
  • Can have optional dimensions (disabled by default, can be enabled)

Apart from the recommended metrics, most services have the possibility of enabling optional metrics.

Optional metrics:

  • Can be added and configured manually

View service metrics

Once you add the service to monitoring, you can view the service metrics in your Dynatrace environment either on your dashboard page or on the custom device overview page.

Import preset dashboards

Dynatrace provides preset AWS dashboards that you can import from GitHub to your environment's Dashboards page.
Note: To save a preset dashboard locally, create a new JSON file on your local machine and copy-paste the content of the JSON file from GitHub into the new file.
Once you save a preset dashboard locally, there are two ways to import it.

elastic-inference

Available metrics

Name Description Unit Statistics Dimensions Recommended
AcceleratorHealthCheckFailed Reports whether the Elastic Inference accelerator has passed a status health check in the last minute Count Sum InstanceId, ElasticInferenceAcceleratorId ✔️
AcceleratorHealthCheckFailed Count Multi InstanceId, ElasticInferenceAcceleratorId
AcceleratorInferenceWithClientErrorCount The number of inference requests reaching the Elastic Inference accelerator in the last minute that resulted in a 4xx error Count Sum InstanceId, ElasticInferenceAcceleratorId ✔️
AcceleratorInferenceWithClientErrorCount Count Multi InstanceId, ElasticInferenceAcceleratorId
AcceleratorInferenceWithServerErrorCount The number of inference requests reaching the Elastic Inference accelerator in the last minute that resulted in a 5xx error Count Sum InstanceId, ElasticInferenceAcceleratorId ✔️
AcceleratorInferenceWithServerErrorCount Count Multi InstanceId, ElasticInferenceAcceleratorId
AcceleratorMemoryUsage The memory of the Elastic Inference accelerator used in the last minute Bytes Multi InstanceId, ElasticInferenceAcceleratorId ✔️
AcceleratorSuccessfulInferenceCount The number of successful inference requests reaching the Elastic Inference accelerator in the last minute Count Sum InstanceId, ElasticInferenceAcceleratorId ✔️
AcceleratorSuccessfulInferenceCount Count Multi InstanceId, ElasticInferenceAcceleratorId
AcceleratorTotalInferenceCount The number of inference requests reaching the Elastic Inference accelerator in the last minute Count Sum InstanceId, ElasticInferenceAcceleratorId ✔️
AcceleratorTotalInferenceCount Count Multi InstanceId, ElasticInferenceAcceleratorId
AcceleratorUtilization The percentage of the Elastic Inference accelerator used for computation in the last minute Percent Multi InstanceId, ElasticInferenceAcceleratorId ✔️
ConnectivityCheckFailed Reports whether connectivity to the Elastic Inference accelerator is active or has failed in the last minute Count Sum InstanceId, ElasticInferenceAcceleratorId ✔️
ConnectivityCheckFailed Count Multi InstanceId, ElasticInferenceAcceleratorId