Amazon CloudWatch metrics (for example, namespaces, metrics, dimensions, and resolution)

What is a namespace in Amazon CloudWatch, and how are they utilized?

A namespace is a container for CloudWatch metrics that helps differentiate the data by the service or application sources. For example, AWS services use namespaces starting with “AWS/” like “AWS/EC2” for Amazon Elastic Compute Cloud or “AWS/RDS” for Amazon Relational Database Service, whereas custom metrics can have custom namespaces. Using namespaces allows for better organization and easier retrieval of related metrics.

Can you explain what a metric is in the context of Amazon CloudWatch?

In CloudWatch, a metric is the fundamental concept representing a time-ordered set of data points. It is used to monitor specific elements such as CPU utilization, latency, or request counts of AWS resources or applications. Metrics are identified by a unique combination of a namespace, metric name, and optionally, one or more dimensions.

How would you describe the function of dimensions in Amazon CloudWatch?

Dimensions are name-value pairs that uniquely identify a metric within a namespace. They provide additional granularity, allowing users to segment metrics along specific criteria, such as “InstanceId” for an EC2 instance or “LoadBalancerName” for an Application Load Balancer. When combined with metric names and namespaces, dimensions enable targeted data monitoring and statistics collection.

What is the difference between standard resolution and high-resolution metrics in CloudWatch?

Standard resolution metrics in CloudWatch provide data points with a minimum granularity of 1 minute, whereas high-resolution metrics offer granularities down to 1 second. High-resolution metrics allow for more detailed and rapid monitoring, suitable for fast-changing environments that require a quicker response to fluctuations in performance or behavior.

Can you explain the significance of the CloudWatch metric “CPUUtilization” for an EC2 instance, including a typical use case?

“CPUUtilization” is a metric in the AWS/EC2 namespace that measures the percentage of allocated compute units that are currently in use on an Amazon EC2 instance. This metric is significant because it helps determine how much of the compute resources are being used and can indicate when an instance is over-utilized or under-utilized, prompting scaling actions or performance optimization efforts.

When creating a custom metric in CloudWatch, what should you consider regarding the naming and organization of the metric?

When creating a custom metric, you should ensure that the metric name clearly indicates the data it represents and adheres to naming conventions for consistency. Additionally, the metric should be organized into an appropriate namespace that groups similar types of metrics together, facilitating easier navigation and retrieval within CloudWatch.

Describe how you can retrieve a metric’s statistical data using Amazon CloudWatch.

To retrieve statistical data for a metric in CloudWatch, you can use the CloudWatch console, AWS CLI, or SDKs. You specify the metric name, namespace, and the desired statistic, such as average, sum, minimum, maximum, or sample count, over a specified time period. CloudWatch then provides the requested data, which can be used for analysis or to trigger alarms based on thresholds.

What are CloudWatch alarms, and how are they related to metrics?

CloudWatch alarms are automated notifications that trigger whenever a metric crosses a threshold specified by the user. Alarms can perform actions such as sending a message to an SNS topic, triggering auto-scaling policies, or changing the state of a resource. Alarms help proactively manage AWS environments by reacting to metric changes that may signify important events or issues.

Is it possible to publish custom metrics with dimensions in Amazon CloudWatch? If so, how?

Yes, it is possible to publish custom metrics with dimensions in CloudWatch. This can be done using the put-metric-data command in the AWS CLI or by calling the PutMetricData API action via the AWS SDKs. When publishing the data, you include the custom namespace, metric name, value, and one or more dimensions to provide context and granularity.

How can Amazon CloudWatch metrics be used to automate actions in AWS?

Amazon CloudWatch metrics can be used to automate actions by linking them to CloudWatch alarms and AWS services like AWS Auto Scaling or AWS Lambda. For example, you can create an auto-scaling policy that automatically adjusts the desired capacity of your EC2 Auto Scaling group based on CPUUtilization metrics or invoke a Lambda function based on a custom metric threshold breach.

What is the PutMetricData API call, and how is it used with Amazon CloudWatch?

The PutMetricData API call is used to publish custom metrics to Amazon CloudWatch. It allows for manual or automated submission of metric data points to a specified namespace, with options to include timestamp, value, unit, and dimensions. This is commonly used in conjunction with scripts or applications to push custom monitoring data into CloudWatch for tracking and alarming purposes.

In what format do you receive CloudWatch metric data when exporting metrics from the console, and how can you use this data?

When exporting metrics from the CloudWatch console, the data is typically provided in CSV format. This data can be used for offline analysis, imported into other tools for visualization, or integrated into reporting systems. Having this data outside of CloudWatch allows for additional processing, sharing, or archival purposes.