Answer: Configure and push high-resolution custom metrics to CloudWatch that record the failures of the external payment processing API calls. Create a CloudWatch alarm that sends a notification via the existing SNS topic when the error rate exceeds the specified rate

Configure and push high-resolution custom metrics to CloudWatch that record the failures of the external payment processing API calls. Create a CloudWatch alarm that sends a notification via the existing SNS topic when the error rate exceeds the specified rate You can publish your own metrics, known as custom metrics, to CloudWatch using the AWS CLI or an API. Each metric is one of the following: Standard resolution, with data having a one-minute granularity High resolution, with data at a granularity of one second Metrics produced by AWS services are standard resolution by default. When you publish a custom metric, you can define it as either standard resolution or high resolution. When you publish a high-resolution metric, CloudWatch stores it with a resolution of 1 second, and you can read and retrieve it with a period of 1 second, 5 seconds, 10 seconds, 30 seconds, or any multiple of 60 seconds. High-resolution metrics can give you more immediate insight into your application's sub-minute activity. Keep in mind that every PutMetricData call for a custom metric is charged, so calling PutMetricData more often on a high-resolution metric can lead to higher charges. You can create metric and composite alarms in Amazon CloudWatch. For the given use case, you can set up a CloudWatch metric alarm that watches the custom metric that captures the API errors and then triggers the alarm when the API error rate exceeds the 5% threshold. The alarm then sends a notification via the existing SNS topic. Incorrect options: Configure CloudWatch metrics with detailed monitoring for the external payment processing API calls. Create a CloudWatch alarm that sends a notification via the existing SNS topic when the error rate exceeds the specified rate - CloudWatch provides two categories of monitoring: basic monitoring and detailed monitoring. Detailed monitoring options differ based on the services that offer it. For example, Amazon EC2 detailed monitoring provides more frequent metrics, published at one-minute intervals, instead of the five-minute intervals used in Amazon EC2 basic monitoring. Detailed monitoring is offered by only some services. As explained above, you need to use custom metrics to capture data for the external payment processing API calls since detailed monitoring for the standard CloudWatch metrics cannot be used for this scenario. Log the results of payment processing API calls to Amazon CloudWatch. Leverage Amazon CloudWatch Logs Insights to query the CloudWatch logs. Set up the Lambda function to check the output from CloudWatch Logs Insights on a schedule and send notification via the existing SNS topic when the error rate exceeds the specified rate - CloudWatch Logs Insights enables you to interactively search and analyze your log data in Amazon CloudWatch Logs. You can perform queries to help you more efficiently and effectively respond to operational issues. This option is not the right fit for the given use case since Lambda cannot monitor the output of the CloudWatch Logs Insights on a real-time basis since it is being invoked on a schedule. Also, it is not an efficient solution since Lambda will need significant custom code to parse and compute the external API error rate from the CloudWatch Logs Insights data. Log the results of payment processing API calls to Amazon CloudWatch. Leverage Amazon CloudWatch Metric Filter to look at the CloudWatch logs. Set up the Lambda function to check the output from CloudWatch Metric Filter on a schedule and send notification via the existing SNS topic when the error rate exceeds the specified rate - You can search and filter the log data coming into CloudWatch Logs by creating one or more metric filters. Metric filters define the terms and patterns to look for in log data as it is sent to CloudWatch Logs. CloudWatch Logs uses these metric filters to turn log data into numerical CloudWatch metrics that you can graph or set an alarm on. This option is not the best fit for the given use case since Lambda cannot monitor the output of the CloudWatch Metric Filter on a real-time basis since it is being invoked on a schedule. Also, it is not an efficient solution since Lambda will need significant custom code to parse and compute the external API error rate from the CloudWatch Metric Filter data.