Troubleshooting Okta Log Ingestion with AWS

See the following if you are experiencing issues after setting up the collection and forwarding of Okta logs to LM Logs.

No Logs Display in LM Logs Page

If logs are not appearing on the LM Logs page after completing integration with AWS and entering the required parameters, refer to the following troubleshooting steps.

Requirements for Verifying No Logs Display Issue

If no logs display on the LM Logs page, review the following requirements:

• Okta logs must be integrated with LM Logs using AWS. For more information, see Okta Log Ingestion with AWS Overview.
• You must have LogicMonitor API tokens to authenticate all requests to the log ingestion API. For more information, see API Tokens.
• You must have an Okta API access key. To know how to generate Okta API access key. For more information, see Create the Token from Okta.

Resolving the No Logs Display Issue on the LM Logs Page

If you are still experiencing issues with logs not appearing, try the following troubleshooting items:

• Confirm your LogicMonitor API credentials—Ensure the Access ID and Access Keys are correct. You can verify your API tokens in your User Access > API Tokens in the LogicMonitor portal. 
• Validate the Lambda function name—The FunctionName parameter must match the function name in your AWS CloudFormation stack. For more information, see AWS Lambda function and parameter reference from Amazon.

  Note: Lambda functions are case-sensitive.

• Review CloudWatch logs—Investigate the CloudWatch logs to get more information.

• Verify the Okta API key—Ensure you are using a valid Okta API key with appropriate permissions to fetch logs. For more information, see View Tokens from Okta.

Frequent Lambda Function Timeouts

If the Lambda function in your AWS integration fails to complete within the configured execution timeout, resulting in frequent timeouts, refer to the following troubleshooting steps.

Resolving Frequent Lambda Function Timeout Issues

• Increase the memory size allocation—Increase the memory size value in the FunctionMemorySize parameter. Increasing memory size also scales CPU resources, allowing the function to execute faster.
• Mitigate cold starts with provisioned concurrency—If you are experiencing cold starts when executing functions, enable provisioned concurrency in your AWS environment. For more information, see Configuring provisioned concurrency for a function from Amazon.
• Extend the trigger interval—Increase the trigger time value in the ScheduleExpression parameter. Increasing the trigger time gives the function more time to execute, especially when dealing with complex or large datasets.

If you have reviewed these items and are still experiencing frequent Lambda timeouts, contact Support.