AWS Certified Developer Associate DVA-C02 Practice Question
An application running on AWS Lambda regularly processes records from an Amazon Kinesis Stream and records custom metrics. The developer wants to send custom metric data to Amazon CloudWatch for detailed monitoring and alarm setting. Which method will MOST effectively meet this requirement?
Store custom metrics in an Amazon DynamoDB table and run periodic scans to send them to CloudWatch.
Embed custom metrics into structured log events using the CloudWatch Embedded Metric Format (EMF) before sending them to CloudWatch Logs.
Publish custom metrics directly in the Lambda function code using the CloudWatch PutMetricData API call for every metric.
Create a custom namespace in CloudWatch and use Amazon Kinesis Data Firehose to stream metrics data to this namespace.
Using CloudWatch Embedded Metric Format (EMF) allows the application to publish custom metrics alongside detailed log events within the same payload. The log events are structured in a way that CloudWatch can extract the metric values. This simplifies the process by reducing the need for additional calls to publish metrics and improves performance by batching metric data with logs. Using custom namespaces in CloudWatch does not offer the same level of integration and simplicity. Publishing custom metrics directly in the Lambda function using the PutMetricData API increases the complexity and the cost due to additional API calls. Adding the metrics to DynamoDB for later processing is inefficient and not intended for real-time monitoring.
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