Tutorial / Cram Notes

Amazon CloudWatch is a robust monitoring service designed for AWS cloud resources and the applications that you run on Amazon Web Services. Understanding CloudWatch metrics is an essential component of effectively managing and monitoring systems and applications within the AWS ecosystem, especially for those aiming to achieve the AWS Certified DevOps Engineer – Professional certification.

Namespaces

A namespace is a container for CloudWatch metrics that provides a high-level categorization for the monitoring data. Metrics within different namespaces are isolated from each other, allowing the same metric name to be reused in different namespaces without conflict. For example, AWS services define their namespaces, such as AWS/EC2 for Amazon EC2 metrics or AWS/DynamoDB for Amazon DynamoDB metrics.

Metrics

Metrics are the fundamental concept in CloudWatch and represent a time-ordered set of data points that are published to CloudWatch. These data points can be metrics like CPU utilization, disk throughput, or latency. Amazon Web Services provides many default metrics for their services, and you can also create custom metrics to monitor your own applications.

For instance, the CPUUtilization metric for EC2 instances is a predefined metric provided by AWS. It measures the percentage of allocated EC2 compute units that are currently in use on the instance.

Dimensions

Dimensions are name/value pairs that uniquely identify a metric. You can assign up to 10 dimensions to a metric and they are part of the identity of a metric. AWS automatically adds dimensions to the metrics that it creates, such as InstanceId for EC2, which allows you to differentiate the metrics from different EC2 instances.

An example dimension for the CPUUtilization metric might be:

DimensionName: InstanceId
DimensionValue: i-1234567890abcdef0

This dimension would uniquely identify the CPU utilization metrics for the specified EC2 instance.

Resolution

Resolution refers to the granularity of the data points in a CloudWatch metric. Standard resolution data points are available at one-minute intervals, while high-resolution metrics can record data at intervals of less than one minute, down to one second. High-resolution metrics are useful for applications that require granular data and rapid responsiveness.

Standard vs High-Resolution Metrics:

Metric Property Standard Resolution High Resolution
Data Interval 1 minute Down to 1 second
Retention Period 15 days (1-minute data points),
63 days (5-minute data points),
455 days (1-hour data points)
15 days
API Operations PutMetricData (default) PutMetricData with StorageResolution parameter set
Available Through All CloudWatch APIs CloudWatch PutMetricData, GetMetricStatistics, and recently launched features

To better illustrate the usage of dimensions and resolution with CloudWatch metrics, consider the following example that uses the AWS SDK for Python (Boto3) to publish a custom network packet count metric with one-second resolution:

import boto3

# Initialize CloudWatch client
cloudwatch = boto3.client(‘cloudwatch’)

# Put custom metric data
response = cloudwatch.put_metric_data(
Namespace=’YOUR_CUSTOM_NAMESPACE’,
MetricData=[
{
‘MetricName’: ‘PacketCount’,
‘Dimensions’: [
{
‘Name’: ‘InstanceId’,
‘Value’: ‘i-1234567890abcdef0’
},
],
‘Timestamp’: datetime.datetime.utcnow(),
‘Value’: 100,
‘Unit’: ‘Count’,
‘StorageResolution’: 1 # This is specifying the high-resolution metric
},
]
)

In this example, the PacketCount metric is pushed to the namespace YOUR_CUSTOM_NAMESPACE for the EC2 instance with the ID i-1234567890abcdef0. The 'StorageResolution': 1 signifies that we’re working with a high-resolution metric, which means CloudWatch will accept data points on a one-second granularity.

Understanding and utilizing CloudWatch metrics—including namespaces, metrics, dimensions, and resolution—is critical for DevOps engineers managing AWS infrastructure. High-resolution metrics are particularly important for real-time application monitoring and finding issues quickly. Knowing how to work with these components will help you to efficiently handle complex monitoring tasks, set up alarms, and automate responses to changes in your application performance and health.

Practice Test with Explanation

True or False: Amazon CloudWatch can only monitor AWS resources, not on-premises servers.

  • True
  • False

Answer: False

Explanation: Amazon CloudWatch can monitor both AWS resources and on-premises servers. You can install the CloudWatch agent on your on-premises servers to collect metrics and logs to send to CloudWatch.

Which of the following are valid CloudWatch metric resolutions? (Select TWO)

  • 1-second
  • 5-minute
  • 10-second
  • 60-minute

Answer: 1-second, 10-second

Explanation: CloudWatch supports a high-resolution option that allows for metrics with a 1-second resolution and also standard resolution metrics that have a default granularity of 1 minute. There are no 5-minute or 60-minute resolutions.

True or False: Custom namespaces can be created in CloudWatch to separate the data of different applications.

  • True
  • False

Answer: True

Explanation: Custom namespaces can be created in CloudWatch to help segregate and manage the metrics for different applications or services.

What does a metric dimension in CloudWatch represent?

  • The unit of the metric
  • A label that describes a characteristic of the metric
  • An aggregation function like SUM or AVG applied to the metric
  • The statistical analysis applied to the metric

Answer: A label that describes a characteristic of the metric

Explanation: A dimension is a name/value pair that uniquely identifies a metric. It can be used to further specify what the metric is and what it represents.

Which of the following statements is true regarding Amazon CloudWatch metrics? (Select TWO)

  • All metrics in CloudWatch are retained indefinitely.
  • CloudWatch metrics have a timestamp.
  • Every metric in CloudWatch is associated with a specific AWS service.
  • You can publish your own custom metrics to CloudWatch.

Answer: CloudWatch metrics have a timestamp, You can publish your own custom metrics to CloudWatch.

Explanation: All CloudWatch metrics have a timestamp that indicates the time point for the data point. Additionally, you can publish your own custom metrics to CloudWatch. However, not all metrics are retained indefinitely; they have a retention period depending on their resolution.

True or False: CloudWatch alarms can be set on metrics without any time delay.

  • True
  • False

Answer: False

Explanation: CloudWatch alarms may experience a slight delay because they require metrics to be processed and evaluated before an alarm state change is determined. The time is influenced by the period of the metric.

What is the highest resolution for CloudWatch custom metrics without enabling high-resolution metrics?

  • 1 minute
  • 5 minutes
  • 15 minutes
  • 1 hour

Answer: 1 minute

Explanation: By default, the highest resolution for CloudWatch custom metrics is 1 minute. To obtain higher resolutions, such as 1-second data points, you would need to enable high-resolution metrics.

True or False: CloudWatch metrics support negative numbers.

  • True
  • False

Answer: False

Explanation: CloudWatch metrics do not support negative numbers as they are meant to show the usage or utilization which would not logically be a negative number.

CloudWatch metrics for EC2 instances automatically provide which of the following metrics without additional charges?

  • CPU Usage
  • Memory Utilization
  • Disk Read/Write Data
  • Network Packets In/Out

Answer: CPU Usage, Network Packets In/Out

Explanation: CloudWatch provides basic EC2 instance metrics such as CPU usage, disk read/write operations, and network packets in/out without any additional charges. Memory utilization has to be customly monitored, usually with the CloudWatch agent.

Which AWS service provides a default namespace in CloudWatch?

  • Amazon EC2
  • AWS Direct Connect
  • Amazon RDS
  • All of the above

Answer: All of the above

Explanation: AWS services such as Amazon EC2, AWS Direct Connect, Amazon RDS, and many others provide default namespaces in CloudWatch. Each AWS service reports metrics to its own namespace.

True or False: All custom metrics sent to CloudWatch are aggregated together without respect to the instance from which they come.

  • True
  • False

Answer: False

Explanation: Custom metrics can be provided with dimensions that describe different characteristics to separate metric data into different streams. For example, instance ID can be a dimension to differentiate and aggregate metrics by the instance.

What is the default period for a CloudWatch metric data point if not specified when publishing the metric?

  • 1 second
  • 10 seconds
  • 60 seconds
  • 300 seconds

Answer: 60 seconds

Explanation: The default period for a CloudWatch metric data point is 60 seconds if not specified when publishing the metric. High-resolution metrics can specify periods as low as 1 second.

Interview Questions

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.

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George Ortiz
6 months ago

This blog post on Amazon CloudWatch metrics is really helpful for my DOP-C02 exam prep. Thanks!

Milan Slagter
5 months ago

Can someone explain the importance of namespaces in CloudWatch metrics?

Israel Saldivar
6 months ago

Great overview on dimensions and how to use them for filtering metrics!

Heather Johnston
6 months ago

Does anyone have tips on choosing the right metric resolution for cost and performance optimization?

Vesna Janković
6 months ago

The section on metric granularity is very informative. Thanks!

Ievfimiya Davidchenko
6 months ago

I think the post could include more detailed comparisons between custom and AWS provided metrics.

Emma Manninen
6 months ago

This is exactly what I needed to understand how to use dimensions in CloudWatch!

Joana Grosser
6 months ago

Excellent breakdown of CloudWatch namespaces!

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