AWS Cloud Development Kit - From Beginner to Professional - CloudWatch Custom Metrics, Filter Patterns, and Alarms

The video tutorial explains how to create custom metrics in AWS for applications running on platforms like Lambda, EC2, and Beanstalk. It covers setting up a Lambda function to log errors, creating metric filters and alarms in CloudWatch, and building a custom metric namespace. The tutorial also demonstrates testing and deploying the setup to monitor third-party API failures and trigger notifications.

Why might default AWS metrics be insufficient for some applications?

• They are too detailed.

• They do not cover all possible scenarios.

• They are only available for EC2 instances.

• They are too expensive to use.

What is the primary purpose of creating a custom metric in a Lambda service?

• To increase the speed of API calls.

• To monitor when a service is breaking.

• To reduce the cost of AWS services.

• To automatically scale the service.

In the given scenario, what triggers the logging of information into CloudWatch logs?

• Lambda function end.

• Successful API calls.

• API call failures.

• Lambda function start.

What type of pattern is used in the metric filter for the Lambda function?

• Date pattern

• Numeric pattern

• Boolean pattern

• String pattern

What is the role of the custom metric namespace in AWS?

• To store logs from all AWS services.

• To organize metrics under a specific category.

• To manage user access to AWS services.

• To automate the deployment of AWS resources.

What is the default value set for the metric filter when there is no match?

• 1

• 0

• False

• True

What happens when the alarm condition is met in the AWS setup?

• The AWS account is locked.

• The API call is retried.

• An SMS notification is sent to the OPS team.

• The Lambda function is terminated.

How many errors in the last two minutes will trigger an alarm?

• One error

• Two errors

• Four errors

• Three errors

What is the purpose of testing the Lambda function multiple times?

• To ensure the function is fast.

• To verify the alarm triggers correctly.

• To reduce the cost of AWS services.

• To increase the function's memory.

What should you do if you encounter problems while creating custom metrics?

• Contact AWS support immediately.

• Ignore the issues.

• Reboot the AWS server.

• Consult the AWS documentation.