In this guide, you’ll learn how to convert key log events into actionable metrics using Amazon CloudWatch metric filters. After your applications push log events to CloudWatch Logs, metric filters let you scan for patterns and generate custom metrics. You can then graph these metrics, set alarms, and include them in dashboards for real‐time visibility.Documentation Index
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What Is a Metric Filter?
A metric filter inspects each log event in a CloudWatch Logs group against a filter pattern. Whenever an event matches, CloudWatch Logs emits a metric datum—either incrementing a counter or setting a value. Once published, you can:- Trigger CloudWatch Alarms
- Plot the data on CloudWatch Dashboards
- Automate responses with EventBridge or Lambda
Metric filters operate in near real‐time and can be applied to both text and JSON‐formatted logs.
How It Works
- Define a filter pattern (e.g.,
"ERROR","[timestamp, requestId, ...]"). - Attach the filter to a log group in CloudWatch Logs.
- Configure the filter to publish metric data—choose a namespace, metric name, and value.
- Use CloudWatch Metrics to visualize data or set alarms on thresholds.

Example: Tracking HTTP 404 Errors
Monitor spikes in “HTTP 404” errors by turning each occurrence into a custom metric.1. Define the Filter Pattern
2. Associate with Your Log Group
3. Publish Metric Data
Each time a log line containsHTTP 404, CloudWatch Logs will emit a MyApp-404Errors metric with a value of 1.
4. Create an Alarm
Overly broad filter patterns can lead to high metric‐filter charges. Always scope patterns tightly and test with sample logs.
Real-World Use Cases
| Use Case | Filter Pattern | Metric Name |
|---|---|---|
| API Latency | { $.latency = * } | MyApp/APIResponseTime |
| Login Failures | "Authentication failure" | MyApp/LoginFailures |
| Disk Utilization | { $.diskUsage > 80 } | MyApp/DiskUtilization |
| Database Errors | "SQL ERROR" | MyApp/DatabaseErrors |