CloudWatch custom metrics allow AWS users to publish their own application-specific metrics to Amazon CloudWatch for monitoring purposes beyond the default metrics provided by AWS services. While AWS automatically collects standard metrics like CPU utilization, network traffic, and disk operations,…CloudWatch custom metrics allow AWS users to publish their own application-specific metrics to Amazon CloudWatch for monitoring purposes beyond the default metrics provided by AWS services. While AWS automatically collects standard metrics like CPU utilization, network traffic, and disk operations, custom metrics enable you to track business-specific data points that matter to your organization.
To create custom metrics, you can use the AWS CLI, SDKs, or the CloudWatch API with the PutMetricData action. Common use cases include monitoring application performance indicators, tracking user activity, measuring queue depths, or capturing memory utilization on EC2 instances (which is not collected by default).
Key components of custom metrics include:
1. **Namespace**: A container for metrics that helps organize and isolate your custom metrics from others. AWS services use namespaces like AWS/EC2.
2. **Metric Name**: The identifier for your specific measurement.
3. **Dimensions**: Name-value pairs that uniquely identify a metric, allowing you to filter and aggregate data.
4. **Timestamp**: When the data point was recorded.
5. **Value and Unit**: The actual measurement and its unit type (Bytes, Seconds, Count, etc.).
Custom metrics support two resolution types: standard resolution (one-minute granularity) and high resolution (one-second granularity) for time-sensitive applications.
The CloudWatch agent simplifies custom metric collection by gathering system-level metrics from EC2 instances and on-premises servers, including memory usage, disk space, and custom application logs.
Pricing for custom metrics is based on the number of metrics stored and API requests made. Each custom metric costs approximately $0.30 per month for standard resolution.
For the SysOps exam, understanding how to configure, publish, and create alarms based on custom metrics is essential for implementing comprehensive monitoring solutions that address specific operational requirements.
CloudWatch Custom Metrics: Complete Guide for AWS SysOps Administrator Associate
Why CloudWatch Custom Metrics Are Important
CloudWatch custom metrics are essential because the default metrics provided by AWS do not cover every aspect of your application or infrastructure. While AWS automatically collects metrics like CPU utilization and network traffic, critical business-specific data such as memory usage, disk space, application-level performance, and custom business KPIs require custom metrics. As a SysOps Administrator, understanding custom metrics enables you to implement comprehensive monitoring solutions that provide complete visibility into your systems.
What Are CloudWatch Custom Metrics?
Custom metrics are user-defined metrics that you publish to Amazon CloudWatch. Unlike standard metrics that AWS services automatically send to CloudWatch, custom metrics allow you to monitor any data point relevant to your application or business. Examples include:
• Memory utilization (not collected by default on EC2) • Disk space usage • Application response times • Number of logged-in users • Business transaction counts • Custom application errors
How CloudWatch Custom Metrics Work
1. Publishing Custom Metrics You can publish custom metrics using: • AWS CLI - Using the put-metric-data command • AWS SDKs - Programmatically from your applications • CloudWatch Agent - For system-level metrics like memory and disk • CloudWatch API - RESTful API calls
2. Metric Resolution Custom metrics support two resolution levels: • Standard Resolution - 1-minute granularity (default) • High Resolution - Up to 1-second granularity (additional cost)
3. Metric Dimensions Dimensions are name-value pairs that uniquely identify a metric. You can specify up to 30 dimensions per metric. For example, a metric named RequestCount could have dimensions like Environment=Production and Region=us-east-1.
4. Metric Data Points Each data point consists of: • Timestamp • Value • Unit (optional but recommended) • Storage Resolution
5. CloudWatch Agent The CloudWatch Agent is the recommended method for collecting system-level custom metrics. It can be installed on both EC2 instances and on-premises servers. The agent collects: • Memory metrics • Disk metrics • Network metrics • Custom log data
6. Aggregation and Statistics CloudWatch aggregates custom metrics using statistics such as: • Sum • Average • Minimum • Maximum • SampleCount • Percentiles (p99, p95, etc.)
Cost Considerations
Custom metrics incur charges based on: • Number of custom metrics • Number of API requests (PutMetricData calls) • High-resolution metrics cost more than standard resolution • Detailed monitoring versus basic monitoring
Best Practice: Use metric batching to reduce API calls - you can send up to 1,000 values in a single PutMetricData request.
Exam Tips: Answering Questions on CloudWatch Custom Metrics
Key Points to Remember:
1. Memory and disk metrics are NOT collected by default - You need the CloudWatch Agent or custom scripts to collect these metrics on EC2 instances.
2. High-resolution metrics - When questions mention sub-minute monitoring or 1-second granularity, think high-resolution custom metrics.
3. CloudWatch Agent is the preferred solution - For questions about collecting memory, disk, or additional system metrics, the CloudWatch Agent is typically the correct answer.
4. Dimensions limit - Remember the maximum of 30 dimensions per metric.
5. Data retention - Custom metric data points are stored for 15 months, with aggregation occurring at different intervals over time.
6. Namespace - Custom metrics should use a custom namespace (not AWS/ prefix, which is reserved for AWS services).
7. PutMetricData API - This is the API call used to publish custom metrics to CloudWatch.
8. Timestamps - Metric data timestamps can be up to 2 weeks in the past and up to 2 hours in the future.
9. IAM Permissions - The CloudWatch Agent and applications need cloudwatch:PutMetricData permission to publish custom metrics.
10. Unified CloudWatch Agent - Can collect both metrics and logs, making it versatile for monitoring scenarios.
Common Exam Scenarios:
• Scenario: Monitor EC2 memory usage - Answer: Install and configure the CloudWatch Agent