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Metrics
Core utility

Metrics creates custom metrics asynchronously by logging metrics to standard output following Amazon CloudWatch Embedded Metric Format (EMF).

These metrics can be visualized through Amazon CloudWatch Console.

Key features

  • Aggregate up to 100 metrics using a single CloudWatch EMF object (large JSON blob).
  • Validate against common metric definitions mistakes (metric unit, values, max dimensions, max metrics, etc).
  • Metrics are created asynchronously by the CloudWatch service, no custom stacks needed.
  • Context manager to create a one off metric with a different dimension.

Terminologies

If you're new to Amazon CloudWatch, there are two terminologies you must be aware of before using this utility:

  • Namespace. It's the highest level container that will group multiple metrics from multiple services for a given application, for example ServerlessEcommerce.
  • Dimensions. Metrics metadata in key-value format. They help you slice and dice metrics visualization, for example ColdStart metric by Payment service.

Metric terminology, visually explained

Install

=== "Maven"

```xml hl_lines="3-7 16 18 24-27"
<dependencies>
    ...
    <dependency>
        <groupId>software.amazon.lambda</groupId>
        <artifactId>powertools-metrics</artifactId>
        <version>{{ powertools.version }}</version>
    </dependency>
    ...
</dependencies>
...
<!-- configure the aspectj-maven-plugin to compile-time weave (CTW) the aws-lambda-powertools-java aspects into your project -->
<build>
    <plugins>
        ...
        <plugin>
             <groupId>dev.aspectj</groupId>
             <artifactId>aspectj-maven-plugin</artifactId>
             <version>1.13.1</version>
             <configuration>
                 <source>11</source> <!-- or higher -->
                 <target>11</target> <!-- or higher -->
                 <complianceLevel>11</complianceLevel> <!-- or higher -->
                 <aspectLibraries>
                     <aspectLibrary>
                         <groupId>software.amazon.lambda</groupId>
                         <artifactId>powertools-metrics</artifactId>
                     </aspectLibrary>
                 </aspectLibraries>
             </configuration>
             <executions>
                 <execution>
                     <goals>
                         <goal>compile</goal>
                     </goals>
                 </execution>
             </executions>
        </plugin>
        ...
    </plugins>
</build>
```

=== "Gradle"

```groovy hl_lines="3 11"
    plugins {
        id 'java'
        id 'io.freefair.aspectj.post-compile-weaving' version '8.1.0'
    }
    
    repositories {
        mavenCentral()
    }
    
    dependencies {
        aspect 'software.amazon.lambda:powertools-metrics:{{ powertools.version }}'
    }
    
    sourceCompatibility = 11
    targetCompatibility = 11
```

Getting started

Metric has two global settings that will be used across all metrics emitted:

Setting Description Environment variable Constructor parameter
Metric namespace Logical container where all metrics will be placed e.g. ServerlessAirline POWERTOOLS_METRICS_NAMESPACE namespace
Service Optionally, sets service metric dimension across all metrics e.g. payment POWERTOOLS_SERVICE_NAME service

!!! tip "Use your application or main service as the metric namespace to easily group all metrics"

=== "template.yaml"

```yaml hl_lines="9 10"
Resources:
    HelloWorldFunction:
        Type: AWS::Serverless::Function
        Properties:
        ...
        Runtime: java8
        Environment:
            Variables:
                POWERTOOLS_SERVICE_NAME: payment
                POWERTOOLS_METRICS_NAMESPACE: ServerlessAirline
```

=== "MetricsEnabledHandler.java"

```java hl_lines="8"
import software.amazon.lambda.powertools.metrics.Metrics;

public class MetricsEnabledHandler implements RequestHandler<Object, Object> {

    MetricsLogger metricsLogger = MetricsUtils.metricsLogger();

    @Override
    @Metrics(namespace = "ExampleApplication", service = "booking")
    public Object handleRequest(Object input, Context context) {
        // ...
    }
}
```

You can initialize Metrics anywhere in your code as many times as you need - It'll keep track of your aggregate metrics in memory.

Creating metrics

You can create metrics using putMetric, and manually create dimensions for all your aggregate metrics using putDimensions.

=== "MetricsEnabledHandler.java"

```java hl_lines="11 12"
import software.amazon.lambda.powertools.metrics.Metrics;
import software.amazon.cloudwatchlogs.emf.logger.MetricsLogger;

public class MetricsEnabledHandler implements RequestHandler<Object, Object> {

    MetricsLogger metricsLogger = MetricsUtils.metricsLogger();

    @Override
    @Metrics(namespace = "ExampleApplication", service = "booking")
    public Object handleRequest(Object input, Context context) {
        metricsLogger.putDimensions(DimensionSet.of("environment", "prod"));
        metricsLogger.putMetric("SuccessfulBooking", 1, Unit.COUNT);
        // ...
    }
}
```

!!! tip "The Unit enum facilitate finding a supported metric unit by CloudWatch."

!!! note "Metrics overflow" CloudWatch EMF supports a max of 100 metrics. Metrics utility will flush all metrics when adding the 100th metric while subsequent metrics will be aggregated into a new EMF object, for your convenience.

Adding high-resolution metrics

You can create high-resolution metrics passing a storageResolution to the putMetric method:

=== "HigResMetricsHandler.java"

```java hl_lines="3 13"
import software.amazon.lambda.powertools.metrics.Metrics;
import software.amazon.cloudwatchlogs.emf.logger.MetricsLogger;
import software.amazon.cloudwatchlogs.emf.model.StorageResolution;

public class MetricsEnabledHandler implements RequestHandler<Object, Object> {

    MetricsLogger metricsLogger = MetricsUtils.metricsLogger();

    @Override
    @Metrics(namespace = "ExampleApplication", service = "booking")
    public Object handleRequest(Object input, Context context) {
        // ...
        metricsLogger.putMetric("SuccessfulBooking", 1, Unit.COUNT, StorageResolution.HIGH);
    }
}
```

!!! info "When is it useful?" High-resolution metrics are data with a granularity of one second and are very useful in several situations such as telemetry, time series, real-time incident management, and others.

Flushing metrics

The @Metrics annotation validates, serializes, and flushes all your metrics. During metrics validation, if no metrics are provided no exception will be raised. If metrics are provided, and any of the following criteria are not met, ValidationException exception will be raised.

!!! tip "Metric validation" * Maximum of 9 dimensions

If you want to ensure that at least one metric is emitted, you can pass raiseOnEmptyMetrics = true to the @Metrics annotation:

=== "MetricsRaiseOnEmpty.java"

```java hl_lines="6"
import software.amazon.lambda.powertools.metrics.Metrics;

public class MetricsRaiseOnEmpty implements RequestHandler<Object, Object> {

    @Override
    @Metrics(raiseOnEmptyMetrics = true)
    public Object handleRequest(Object input, Context context) {
    ...
    }
}
```

Capturing cold start metric

You can capture cold start metrics automatically with @Metrics via the captureColdStart variable.

=== "MetricsColdStart.java"

```java hl_lines="6"
import software.amazon.lambda.powertools.metrics.Metrics;

public class MetricsColdStart implements RequestHandler<Object, Object> {

    @Override
    @Metrics(captureColdStart = true)
    public Object handleRequest(Object input, Context context) {
    ...
    }
}
```

If it's a cold start invocation, this feature will:

  • Create a separate EMF blob solely containing a metric named ColdStart
  • Add FunctionName and Service dimensions

This has the advantage of keeping cold start metric separate from your application metrics.

Advanced

Adding metadata

You can use putMetadata for advanced use cases, where you want to metadata as part of the serialized metrics object.

!!! info This will not be available during metrics visualization, use dimensions for this purpose.

=== "App.java"

```java hl_lines="8 9" 
import software.amazon.lambda.powertools.metrics.Metrics;
import software.amazon.cloudwatchlogs.emf.logger.MetricsLogger;

public class App implements RequestHandler<Object, Object> {

    @Override
    @Metrics(namespace = "ServerlessAirline", service = "payment")
    public Object handleRequest(Object input, Context context) {
        metricsLogger().putMetric("CustomMetric1", 1, Unit.COUNT);
        metricsLogger().putMetadata("booking_id", "1234567890");
        ...
    }
}
```

This will be available in CloudWatch Logs to ease operations on high cardinal data.

Overriding default dimension set

By default, all metrics emitted via module captures Service as one of the default dimension. This is either specified via POWERTOOLS_SERVICE_NAME environment variable or via service attribute on Metrics annotation. If you wish to override the default Dimension, it can be done via #!java MetricsUtils.defaultDimensions().

=== "App.java"

```java hl_lines="8 9 10"
import software.amazon.lambda.powertools.metrics.Metrics;
import static software.amazon.lambda.powertools.metrics.MetricsUtils;

public class App implements RequestHandler<Object, Object> {

    MetricsLogger metricsLogger = MetricsUtils.metricsLogger();
    
    static {
        MetricsUtils.defaultDimensions(DimensionSet.of("CustomDimension", "booking"));
    }

    @Override
    @Metrics(namespace = "ExampleApplication", service = "booking")
    public Object handleRequest(Object input, Context context) {
        ...
        MetricsUtils.withSingleMetric("Metric2", 1, Unit.COUNT, log -> {});
    }
}
```

Creating a metric with a different dimension

CloudWatch EMF uses the same dimensions across all your metrics. Use withSingleMetric if you have a metric that should have different dimensions.

!!! info Generally, this would be an edge case since you pay for unique metric. Keep the following formula in mind: unique metric = (metric_name + dimension_name + dimension_value)

=== "App.java"

```java hl_lines="7 8 9" 
import static software.amazon.lambda.powertools.metrics.MetricsUtils.withSingleMetric;

public class App implements RequestHandler<Object, Object> {

    @Override
    public Object handleRequest(Object input, Context context) {
         withSingleMetric("CustomMetrics2", 1, Unit.COUNT, "Another", (metric) -> {
            metric.setDimensions(DimensionSet.of("AnotherService", "CustomService"));
        });
    }
}
```

Creating metrics with different configurations

Use withMetricsLogger if you have one or more metrics that should have different configurations e.g. dimensions or namespace.

=== "App.java"

```java hl_lines="7 8 9 10 11 12 13" 
import static software.amazon.lambda.powertools.metrics.MetricsUtils.withMetricsLogger;

public class App implements RequestHandler<Object, Object> {

    @Override
    public Object handleRequest(Object input, Context context) {
         withMetricsLogger(logger -> {
            // override default dimensions
            logger.setDimensions(DimensionSet.of("AnotherService", "CustomService"));
            // add metrics
            logger.putMetric("CustomMetrics1", 1, Unit.COUNT);
            logger.putMetric("CustomMetrics2", 5, Unit.COUNT);
        });
    }
}
```