Metrics

5 minutes 5 Questions

Metrics are the fundamental concept in Amazon CloudWatch that represents a time-ordered set of data points. They are used to track and monitor the performance and utilization of AWS resources, such as EC2 instances, EBS volumes, and RDS databases. You can use CloudWatch to collect and analyze these metrics, set alarms based on the metrics' values, and visualize them in the form of graphs. Metrics can either be predefined by AWS for their services, or custom metrics that you can define and collect from your applications and resources. Some common metrics that AWS services provide include CPU Utilization, Network Packets, and Disk Read/Write Ops.

Guide: AWS CloudWatch Metrics

What is AWS CloudWatch Metrics?
AWS CloudWatch Metrics is a scalable AWS service that allows you to collect, view, and analyze metrics for your AWS resources and applications in real-time. It helps you gain system-wide visibility into resource utilization, application performance, and operational health.
Why is AWS CloudWatch Metrics important?
AWS CloudWatch Metrics is important because it allows you to monitor your applications, collect and track metrics, collect and monitor log files, and respond to system-wide performance changes. You can set alarms to notify you when specific thresholds have been breached, and every metric data point can be broken down into a minute or even seconds of granularity.
How does AWS CloudWatch Metrics work?
AWS CloudWatch Metrics works by collecting raw data points from your AWS resources and applications, and turning them into actionable, easy-to-interpret graphs and statistics. It provides you with system-wide visibility into resource utilization, operational performance, and demand patterns-including detailed usage metrics for each service you are provisioned with whether it be EC2 instances, DynamoDB tables, or RDS DB instances.
Exam Tips: Answering Questions on Metrics
1. Make sure to understand the difference between standard and high-resolution metrics: Standard metrics have a minimum granularity of one minute while high-resolution metrics can go down to one second.
2. Keep in mind the different statistic types that CloudWatch provides including Average, Sum, Minimum, Maximum, and SampleCount.
3. Know the limits of CloudWatch such as the fact that data points with a period of less than 60 seconds are available for 3 hours.
4. Remember that metrics are kept for 15 months, so you can retrieve historical data.
5. Finally, understand how to set alarms based on metric thresholds to alert you of potential issues.

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Question 1

You have been asked to create an alarm for when an RDS instance's CPU utilization is above 75% for two consecutive periods of 15 minutes. Which combination should you use?

Evaluation Period: 2, Period Length: 15 minutes Evaluation Period: 2, Period Length: 60 minutes Evaluation Period: 4, Period Length: 60 minutes Evaluation Period: 1, Period Length: 30 minutes

Correct Answer: Evaluation Period: 2, Period Length: 15 minutes

The correct answer requires 2 consecutive evaluation periods of 15 minutes each. Only the correct_answer covers that requirement.

Question 2

A company wants to measure the end-to-end latency of API requests made by external clients. Which metric can help them achieve this?

API Gateway End-to-end Latency Load Balancer Request Processing Time Lambda Function Execution Time API Gateway Request Latency

Correct Answer: API Gateway End-to-end Latency

API Gateway End-to-end Latency measures the total latency from the client, through API Gateway, to the backend services, and back. This is the end-to-end measurement, while other metrics focus on specific components.

Question 3

An application is experiencing sporadic spikes in latency, and AWS X-Ray has narrowed down the issue to a specific service. Which metric can help further identify the cause of the issue?

Concurrent requests Billed time of the Lambda function Duration of Lambda function Request per minute

Correct Answer: Request per minute

Examining requests per minute in CloudWatch will allow us to determine if latency increases with spikes in request rates. The other option does not help to identify the cause of the high latency in specific service.

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