Configure your Splunk Observability Cloud account to collect AWS Bedrock metrics

Learn how to configure your Splunk Observability Cloud account to collect AWS Bedrock metrics.

You can monitor the performance of Amazon Web Services (AWS) Bedrock applications by configuring your AWS Bedrock applications to send metrics to Splunk Observability Cloud. This solution creates a cloud connection in your Splunk Observability Cloud account that collects metrics from AWS CloudWatch.

Complete the following steps to collect metrics from and monitor your AWS Bedrock applications.

Connect AWS to Splunk Observability Cloud. For more information on the connection methods and instructions for each method, see Available options to connect with AWS.
To gain permission to collect all AWS Bedrock attributes, add the following permissions to your AWS IAM policy JSON snippet:
```
"bedrock:ListTagsForResource",
"bedrock:ListFoundationModels",
"bedrock:GetFoundationModel",
"bedrock:ListInferenceProfiles"
```
To monitor AWS Bedrock metrics with Splunk Observability Cloud, run your applications that use AWS Bedrock models.

Metrics

Learn about the available metrics for AWS Bedrock.

The following metrics are available for AWS Bedrock applications. For more information on these metrics, see Monitoring the performance of Amazon Bedrock in the AWS documentation and View organization metrics for Splunk Observability Cloud.


Metric name	Type	Unit	Description
`InputTokenCount`	counter	count	Input tokens consumed.
`OutputTokenCount`	counter	count	Output tokens consumed.
`Invocations`	counter	SampleCount	The number of successful requests made to AWS Bedrock API operations.
`InvocationLatency`	histogram	ms	The time taken for an invocation, specifically the latency of the requests to the AWS Bedrock models, typically in milliseconds.
`sf.org.num.awsServiceAuthErrorCount`	gauge	count	Total number of authentication errors thrown by AWS services. Dimension(s): `integrationId`, `orgId`, `namespace` (AWS Cloudwatch namespace), `clientInterface` (AWS SDK Interface), `method` (AWS SDK method) Data resolution: 1 second
`sf.org.num.awsServiceCallThrottles`	gauge	count	Number of calls made to the Amazon API that are being throttled by AWS because you have exceeded your AWS API call limits. Dimension(s): `orgId`, `namespace` (AWS service, such as AWS/Cloudwatch), `method` (the API being called, such as `getMetricStatistics`) Data resolution: 5 seconds
`sf.org.num.awsServiceCallThrottledRetryFailures`	gauge	count	Number of AWS service call throttle retry failures.
`sf.org.num.awsServiceCallCountExceptions`	gauge	count	Number of calls made to the Amazon API that threw exceptions. Dimension(s): `orgId`, `namespace` (AWS service, such as AWS/Cloudwatch), `method` (the API being called, such as `getMetricStatistics`), `location` (where the exception occurred, either `client` or `server`) Data resolution: 5 seconds
`sf.org.num.awsServiceCallCount`	gauge	count	Total number of calls made to the Amazon API. Dimension(s): `orgId`, `namespace` (AWS service, such as AWS/Cloudwatch), `method` (the API being called, such as `getMetricStatistics`) Data resolution: 5 seconds

Attributes

Learn about the available resource attributes for AWS Bedrock applications.

The following resource attribute is available for AWS Bedrock applications.


OpenTelemetry name	Display name	Description
`id`	id	The AWS unique identifier.

Troubleshoot

Learn how to get help if you can't see your data in Splunk Observability Cloud.

If you can't see your data in Splunk Observability Cloud, you can get help in the following ways:

Splunk Observability Cloud customers can submit a case in the Splunk Support Portal or contact Splunk Support.

Prospective customers and free trial users can ask a question and get answers through community support in the Splunk Community.

Next steps

How to monitor your AI components after you set up Observability for AI.

After you set up data collection from supported AI components to Splunk Observability Cloud, the data populates built-in experiences that you can use to monitor and troubleshoot your AI components.

The following table describes the tools you can use to monitor and troubleshoot your AI components.


Monitoring tool	Use this tool to	Link to documentation
Built-in navigators	Orient and explore different layers of your AI tech stack.	Use navigators Monitor LLM costs with navigators
Built-in dashboards	Assess service, endpoint, and system health at a glance.	Built-in dashboards View dashboards in Splunk Observability Cloud
Splunk Application Performance Monitoring (APM) service map and trace view	View all of your LLM service dependency graphs and user interactions in the service map or trace view.	Monitor LLM services with Splunk APM