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Metrics

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)
  • Validating your metrics against common metric definitions mistakes (for example, metric unit, values, max dimensions, max metrics)
  • Metrics are created asynchronously by the CloudWatch service. You do not need any custom stacks, and there is no impact to Lambda function latency
  • Context manager to create a one off metric with a different dimension


Screenshot of the Amazon CloudWatch Console showing an example of business metrics in the Metrics Explorer
Metrics showcase - Metrics Explorer

Installation

Powertools for AWS Lambda (.NET) are available as NuGet packages. You can install the packages from NuGet Gallery or from Visual Studio editor by searching AWS.Lambda.Powertools* to see various utilities available.

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. It's the name of the metric, for example: SuccessfulBooking or UpdatedBooking.
  • Unit. It's a value representing the unit of measure for the corresponding metric, for example: Count or Seconds.
  • Resolution. It's a value representing the storage resolution for the corresponding metric. Metrics can be either Standard or High resolution. Read more here.

Visit the AWS documentation for a complete explanation for Amazon CloudWatch concepts.

Metric terminology, visually explained

Getting started

Metrics is implemented as a Singleton to keep track of your aggregate metrics in memory and make them accessible anywhere in your code. To guarantee that metrics are flushed properly the MetricsAttribute must be added on the lambda handler.

Metrics has two global settings that will be used across all metrics emitted. Use your application or main service as the metric namespace to easily group all metrics:

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

Autocomplete Metric Units

All parameters in Metrics Attribute are optional. Following rules apply:

  • Namespace: Empty string by default. You can either specify it in code or environment variable. If not present before flushing metrics, a SchemaValidationException will be thrown.
  • Service: service_undefined by default. You can either specify it in code or environment variable.
  • CaptureColdStart: false by default.
  • RaiseOnEmptyMetrics: false by default.

Example using AWS Serverless Application Model (AWS SAM)

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Resources:
HelloWorldFunction:
    Type: AWS::Serverless::Function 
    Properties:
    ...
    Environment: 
    Variables:
        POWERTOOLS_SERVICE_NAME: ShoppingCartService
        POWERTOOLS_METRICS_NAMESPACE: MyCompanyEcommerce

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using AWS.Lambda.Powertools.Metrics;

public class Function {
  [Metrics(Namespace = "MyCompanyEcommerce", Service = "ShoppingCartService", CaptureColdStart = true, RaiseOnEmptyMetrics = true)]
  public async Task<APIGatewayProxyResponse> FunctionHandler(APIGatewayProxyRequest apigProxyEvent, ILambdaContext context)
  {
    ...
  }
}

Full list of environment variables

Environment variable Description Default
POWERTOOLS_SERVICE_NAME Sets service name used for tracing namespace, metrics dimension and structured logging "service_undefined"
POWERTOOLS_METRICS_NAMESPACE Sets namespace used for metrics None

Creating metrics

You can create metrics using AddMetric, and you can create dimensions for all your aggregate metrics using AddDimension method.

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using AWS.Lambda.Powertools.Metrics;

public class Function {

  [Metrics(Namespace = "ExampleApplication", Service = "Booking")]
  public async Task<APIGatewayProxyResponse> FunctionHandler(APIGatewayProxyRequest apigProxyEvent, ILambdaContext context)
  {
    Metrics.AddMetric("SuccessfulBooking", 1, MetricUnit.Count);
  }
}

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using AWS.Lambda.Powertools.Metrics;

public class Function {

  [Metrics(Namespace = "ExampleApplication", Service = "Booking")]
  public async Task<APIGatewayProxyResponse> FunctionHandler(APIGatewayProxyRequest apigProxyEvent, ILambdaContext context)
  {
    Metrics.AddDimension("Environment","Prod");
    Metrics.AddMetric("SuccessfulBooking", 1, MetricUnit.Count);
  }
}

Autocomplete Metric Units

MetricUnit enum facilitates finding a supported metric unit by CloudWatch.

Metrics overflow

CloudWatch EMF supports a max of 100 metrics per batch. Metrics utility will flush all metrics when adding the 100th metric. Subsequent metrics, e.g. 101th, will be aggregated into a new EMF object, for your convenience.

Metric value must be a positive number

Metric values must be a positive number otherwise an ArgumentException will be thrown.

Do not create metrics or dimensions outside the handler

Metrics or dimensions added in the global scope will only be added during cold start. Disregard if that's the intended behavior.

Adding high-resolution metrics

You can create high-resolution metrics passing MetricResolution as parameter to AddMetric.

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.

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using AWS.Lambda.Powertools.Metrics;

public class Function {

  [Metrics(Namespace = "ExampleApplication", Service = "Booking")]
  public async Task<APIGatewayProxyResponse> FunctionHandler(APIGatewayProxyRequest apigProxyEvent, ILambdaContext context)
  {
    // Publish a metric with standard resolution i.e. StorageResolution = 60
    Metrics.AddMetric("SuccessfulBooking", 1, MetricUnit.Count, MetricResolution.Standard);

    // Publish a metric with high resolution i.e. StorageResolution = 1
    Metrics.AddMetric("FailedBooking", 1, MetricUnit.Count, MetricResolution.High);

    // The last parameter (storage resolution) is optional
    Metrics.AddMetric("SuccessfulUpgrade", 1, MetricUnit.Count);
  }
}

Autocomplete Metric Resolutions

Use the MetricResolution enum to easily find a supported metric resolution by CloudWatch.

Adding default dimensions

You can use SetDefaultDimensions method to persist dimensions across Lambda invocations.

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using AWS.Lambda.Powertools.Metrics;

public class Function {
  private Dictionary<string, string> _defaultDimensions = new Dictionary<string, string>{
        {"Environment", "Prod"},
        {"Another", "One"}
    }; 

  [Metrics(Namespace = "ExampleApplication", Service = "Booking")]
  public async Task<APIGatewayProxyResponse> FunctionHandler(APIGatewayProxyRequest apigProxyEvent, ILambdaContext context)
  {
    Metrics.SetDefaultDimensions(_defaultDimensions);
    Metrics.AddMetric("SuccessfulBooking", 1, MetricUnit.Count);
  }
}

Flushing metrics

With MetricsAttribute all your metrics are validated, serialized and flushed to standard output when lambda handler completes execution or when you had the 100th metric to memory.

During metrics validation, if no metrics are provided then a warning will be logged, but no exception will be raised.

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using AWS.Lambda.Powertools.Metrics;

public class Function {

  [Metrics(Namespace = "ExampleApplication", Service = "Booking")]
  public async Task<APIGatewayProxyResponse> FunctionHandler(APIGatewayProxyRequest apigProxyEvent, ILambdaContext context)
  {
    Metrics.AddMetric("SuccessfulBooking", 1, MetricUnit.Count);
  }
}

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{
"BookingConfirmation": 1.0,
"_aws": {
    "Timestamp": 1592234975665,
    "CloudWatchMetrics": [
        {
    "Namespace": "ExampleApplication",
    "Dimensions": [
        [
        "service"
        ]
    ],
    "Metrics": [
        {
        "Name": "BookingConfirmation",
        "Unit": "Count"
        }
    ]
        }
    ]
    },
"service": "ExampleService"
}

Metric validation

If metrics are provided, and any of the following criteria are not met, SchemaValidationException will be raised:

We do not emit 0 as a value for ColdStart metric for cost reasons. Let us know if you'd prefer a flag to override it

Raising SchemaValidationException on empty metrics

If you want to ensure that at least one metric is emitted, you can pass RaiseOnEmptyMetrics to the Metrics attribute:

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using AWS.Lambda.Powertools.Metrics;

public class Function {

  [Metrics(RaiseOnEmptyMetrics = true)]
  public async Task<APIGatewayProxyResponse> FunctionHandler(APIGatewayProxyRequest apigProxyEvent, ILambdaContext context)
  {
    ...

Capturing cold start metric

You can optionally capture cold start metrics by setting CaptureColdStart parameter to true.

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using AWS.Lambda.Powertools.Metrics;

public class Function {

  [Metrics(CaptureColdStart = true)]
  public async Task<APIGatewayProxyResponse> FunctionHandler(APIGatewayProxyRequest apigProxyEvent, ILambdaContext context)
  {
    ...

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

  • Create a separate EMF blob solely containing a metric named ColdStart
  • Add function_name and service dimensions

This has the advantage of keeping cold start metric separate from your application metrics, where you might have unrelated dimensions.

Advanced

Adding metadata

You can add high-cardinality data as part of your Metrics log with AddMetadata method. This is useful when you want to search highly contextual information along with your metrics in your logs.

Info

This will not be available during metrics visualization - Use dimensions for this purpose

Info

Adding metadata with a key that is the same as an existing metric will be ignored

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using AWS.Lambda.Powertools.Metrics;

public class Function {

  [Metrics(Namespace = ExampleApplication, Service = "Booking")]
  public async Task<APIGatewayProxyResponse> FunctionHandler(APIGatewayProxyRequest apigProxyEvent, ILambdaContext context)
  {
    Metrics.AddMetric("SuccessfulBooking", 1, MetricUnit.Count);
    Metrics.AddMetadata("BookingId", "683EEB2D-B2F3-4075-96EE-788E6E2EED45");
    ...

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{
  "SuccessfulBooking": 1.0,
  "_aws": {
  "Timestamp": 1592234975665,
  "CloudWatchMetrics": [
    {
  "Namespace": "ExampleApplication",
  "Dimensions": [
    [
    "service"
    ]
  ],
  "Metrics": [
    {
    "Name": "SuccessfulBooking",
    "Unit": "Count"
    }
  ]
    }
  ]
  },
  "Service": "Booking",
  "BookingId": "683EEB2D-B2F3-4075-96EE-788E6E2EED45"
}

Single metric with a different dimension

CloudWatch EMF uses the same dimensions across all your metrics. Use PushSingleMetric 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)

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using AWS.Lambda.Powertools.Metrics;

public class Function {

  [Metrics(Namespace = ExampleApplication, Service = "Booking")]
  public async Task<APIGatewayProxyResponse> FunctionHandler(APIGatewayProxyRequest apigProxyEvent, ILambdaContext context)
  {
    Metrics.PushSingleMetric(
                metricName: "ColdStart",
                value: 1,
                unit: MetricUnit.Count,
                nameSpace: "ExampleApplication",
                service: "Booking",
                defaultDimensions: new Dictionary<string, string>
                {
                    {"FunctionContext", "$LATEST"}
                });
    ...

Testing your code

Environment variables

Tip

Ignore this section, if:

  • You are explicitly setting namespace/default dimension via namespace and service parameters
  • You're not instantiating Metrics in the global namespace

For example, Metrics(namespace="ExampleApplication", service="booking")

Make sure to set POWERTOOLS_METRICS_NAMESPACE and POWERTOOLS_SERVICE_NAME before running your tests to prevent failing on SchemaValidation exception. You can set it before you run tests by adding the environment variable.

Injecting Metric Namespace before running tests
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Environment.SetEnvironmentVariable("POWERTOOLS_METRICS_NAMESPACE","AWSLambdaPowertools");