Collecting custom metrics (for example, using the CloudWatch agent)

Explain what custom metrics are, and why you would need to collect them in AWS CloudWatch?

Custom metrics are user-defined metrics that provide additional granularity beyond the default metrics provided by AWS services. They allow you to monitor application-specific events, performance, or operational health that are unique to your system. You might need to collect custom metrics in AWS CloudWatch to gain insights into specific aspects of your application or infrastructure that are not covered by standard metrics, thus allowing you to make more informed decisions on scaling, performance tuning, and fault diagnosis.

What is the CloudWatch agent, and how does it differ from the default CloudWatch monitoring?

The CloudWatch agent is a software application that enables you to collect extended system-level metrics from Amazon EC2 instances and on-premises servers. While default CloudWatch monitoring collects basic metrics like CPU usage, disk I/O, and network usage, the CloudWatch agent allows for the collection of additional system-level metrics such as memory usage, disk swap utilization, and detailed network metrics, as well as custom metrics defined by the user.

Can you describe the process of installing and configuring the CloudWatch agent on an EC2 instance?

To install the CloudWatch agent on an EC2 instance, you would typically download and install the CloudWatch agent package, create or modify the CloudWatch agent configuration file to specify the metrics you want to collect, and then start the agent. You can also use AWS Systems Manager or manually run commands on your instance to install and configure the agent. The configuration file supports both standard and custom metrics, and it can be updated as needs evolve.

How can you use IAM roles to manage permissions for the CloudWatch agent?

IAM roles can be used to securely provide the CloudWatch agent with the necessary permissions to send metrics to CloudWatch. You would create an IAM role with a policy that grants the agent permission to PutMetricData, and then assign this role to the EC2 instance or on-premises server where the agent is installed. This removes the need to store AWS credentials on individual servers and is a best practice for security.

What are some of the custom metrics you might want to collect from your application servers, and why would these be important?

Some custom metrics you might want to collect include application transaction times, queue lengths, the number of active threads or processes, error rates, or application-specific events like user logins or in-app purchases. These metrics can provide deep insights into the performance and behavior of your application, helping you to quickly detect and react to potential issues or bottlenecks, and to understand usage patterns for capacity planning.

How can you aggregate and filter custom metrics collected by the CloudWatch agent for better insights?

Custom metrics can be aggregated and filtered using dimensions, which are name/value pairs that uniquely identify a metric. You can use dimensions to segment your metrics by various attributes such as instance type, environment, application version, or any other relevant identifier. By using the CloudWatch console or API, you can then create filters and aggregations based on these dimensions to visualize and analyze your metrics at different granularities.

Describe how to secure the data transmission from the CloudWatch agent to CloudWatch.

To secure the data transmission from the CloudWatch agent to CloudWatch, confirm that the agent uses the Secure Socket Layer (SSL)/Transport Layer Security (TLS) protocols to encrypt the data in transit. Also, control network access using security groups and network ACLs to restrict traffic to the necessary AWS endpoints. Additionally, regularly update the agent to ensure it has the latest security fixes.

How would you troubleshoot issues with the CloudWatch agent not reporting custom metrics?

To troubleshoot the CloudWatch agent, you should first check the agent’s log files for any errors according to the configured log level. Verify that the agent configuration file is correctly formatted and contains the correct definitions for the custom metrics. Ensure the IAM role or user has the necessary permissions to send metrics to CloudWatch. Additionally, confirm that the agent is running and that there are no network connectivity issues preventing it from reaching CloudWatch.

Can you explain how you would monitor memory and disk space utilization on an on-premises server using the CloudWatch agent?

To monitor memory and disk space utilization on an on-premises server, you need to install the CloudWatch agent on the server, just as you would on an EC2 instance. Configure the agent with a custom metrics section in the configuration file to specify memory and disk space metrics to collect. Assign the necessary permissions through an IAM role or IAM user credentials, and ensure the server has internet access to reach AWS CloudWatch endpoints.

What are some best practices for optimizing the performance and cost-impact of collecting and storing custom metrics in CloudWatch?

Best practices include aggregating metrics at the source where possible to reduce the volume of metric data sent to CloudWatch, which can reduce costs. Collect metrics at a frequency that balances granularity and cost, considering the CloudWatch charge for custom metric storage and data points requests. Minimize the use of high-resolution metrics where not necessary, and regularly review and prune unnecessary metrics. Lastly, create alarms thoughtfully to avoid excessive charges from too many evaluations.