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Metrics V2

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
  • Ahead-of-Time compilation to native code support AOT from version 1.7.0
  • Support for AspNetCore middleware and filters to capture metrics for HTTP requests

Breaking changes from V1

  • Dimensions outputs as an array of arrays instead of an array of objects. Example: Dimensions: [["service", "Environment"]] instead of Dimensions: ["service", "Environment"]
  • FunctionName is not added as default dimension and only to cold start metric.
  • Default Dimensions can now be included in Cold Start metrics, this is a potential breaking change if you were relying on the absence of default dimensions in Cold Start metrics when searching.


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 three 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 Decorator parameter
Metric namespace Logical container where all metrics will be placed e.g. MyCompanyEcommerce POWERTOOLS_METRICS_NAMESPACE Namespace
Service Optionally, sets Service metric dimension across all metrics e.g. payment POWERTOOLS_SERVICE_NAME Service
Disable Powertools Metrics Optionally, disables all Powertools metrics POWERTOOLS_METRICS_DISABLED N/A
Info

POWERTOOLS_METRICS_DISABLED will not disable default metrics created by AWS services.

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.

Metrics object

Attribute

The MetricsAttribute is a class-level attribute that can be used to set the namespace and service for all metrics emitted by the lambda handler.

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using AWS.Lambda.Powertools.Metrics;

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

Methods

The Metrics class provides methods to add metrics, dimensions, and metadata to the metrics object.

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using AWS.Lambda.Powertools.Metrics;

public async Task<APIGatewayProxyResponse> FunctionHandler(APIGatewayProxyRequest apigProxyEvent, ILambdaContext context)
{
    Metrics.AddMetric("SuccessfulBooking", 1, MetricUnit.Count);
    Metrics.AddDimension("Environment", "Prod");
    Metrics.AddMetadata("BookingId", "683EEB2D-B2F3-4075-96EE-788E6E2EED45");
    ...
}

Initialization

The Metrics object is initialized as a Singleton and can be accessed anywhere in your code.

But can also be initialize with Configure or Builder patterns in your Lambda constructor, this the best option for testing.

Configure:

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using AWS.Lambda.Powertools.Metrics;

public Function()
{
    Metrics.Configure(options =>
    {
        options.Namespace = "dotnet-powertools-test";
        options.Service = "testService";
        options.CaptureColdStart = true;
        options.DefaultDimensions = new Dictionary<string, string>
        {
            { "Environment", "Prod" },
            { "Another", "One" }
        };
    });
}

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

Builder:

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using AWS.Lambda.Powertools.Metrics;

private readonly IMetrics _metrics;

public Function()
{
    _metrics = new MetricsBuilder()
        .WithCaptureColdStart(true)
        .WithService("testService")
        .WithNamespace("dotnet-powertools-test")
        .WithDefaultDimensions(new Dictionary<string, string>
        {
            { "Environment", "Prod1" },
            { "Another", "One" }
        }).Build();
}

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

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);
  }
}

Adding default dimensions with cold start metric

You can use the Builder or Configure patterns in your Lambda class constructor to set default dimensions.

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using AWS.Lambda.Powertools.Metrics;

public class Function {
  private readonly IMetrics _metrics;

  public Function()
  {
    _metrics = new MetricsBuilder()
        .WithCaptureColdStart(true)
        .WithService("testService")
        .WithNamespace("dotnet-powertools-test")
        .WithDefaultDimensions(new Dictionary<string, string>
        {
            { "Environment", "Prod1" },
            { "Another", "One" }
        }).Build();
  }

  [Metrics]
  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 {

  public Function()
  {
    Metrics.Configure(options =>
    {
        options.Namespace = "dotnet-powertools-test";
        options.Service = "testService";
        options.CaptureColdStart = true;
        options.DefaultDimensions = new Dictionary<string, string>
        {
            { "Environment", "Prod" },
            { "Another", "One" }
        };
    });
  }

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

Adding dimensions

You can add dimensions to your 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.AddDimension("Environment","Prod");
    Metrics.AddMetric("SuccessfulBooking", 1, MetricUnit.Count);
  }
}

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

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.

You can also flush metrics manually by calling Flush method.

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);
    Metrics.Flush();
  }
}

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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)
  {
    ...

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using AWS.Lambda.Powertools.Metrics;

public class Function {
  private readonly IMetrics _metrics;

  public Function()
  {
    _metrics = new MetricsBuilder()
        .WithCaptureColdStart(true)
        .WithService("testService")
        .WithNamespace("dotnet-powertools-test")
  }

  [Metrics]
  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 {

  public Function()
  {
    Metrics.Configure(options =>
    {
        options.Namespace = "dotnet-powertools-test";
        options.Service = "testService";
        options.CaptureColdStart = true;
    });
  }

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

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, 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(
                name: "ColdStart",
                value: 1,
                unit: MetricUnit.Count,
                nameSpace: "ExampleApplication",
                service: "Booking");
    ...

By default it will skip all previously defined dimensions including default dimensions. Use dimensions argument if you want to reuse default dimensions or specify custom dimensions from a dictionary.

  • Metrics.DefaultDimensions: Reuse default dimensions when using static Metrics
  • Options.DefaultDimensions: Reuse default dimensions when using Builder or Configure patterns
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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(
                name: "ColdStart",
                value: 1,
                unit: MetricUnit.Count,
                nameSpace: "ExampleApplication",
                service: "Booking",
                dimensions: new Dictionary<string, string>
                {
                    {"FunctionContext", "$LATEST"}
                });
    ...

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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.SetDefaultDimensions(new Dictionary<string, string> 
    {
        { "Default", "SingleMetric" }
    });
    Metrics.PushSingleMetric("SingleMetric", 1, MetricUnit.Count, dimensions: Metrics.DefaultDimensions );
    ...

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using AWS.Lambda.Powertools.Metrics;

public MetricsnBuilderHandler(IMetrics metrics = null)
{
    _metrics = metrics ?? new MetricsBuilder()
        .WithCaptureColdStart(true)
        .WithService("testService")
        .WithNamespace("dotnet-powertools-test")
        .WithDefaultDimensions(new Dictionary<string, string>
        {
            { "Environment", "Prod1" },
            { "Another", "One" }
        }).Build();
}

public void HandlerSingleMetricDimensions()
{
    _metrics.PushSingleMetric("SuccessfulBooking", 1, MetricUnit.Count, dimensions: _metrics.Options.DefaultDimensions);
}
    ...

Cold start Function Name dimension

In cases where you want to customize the FunctionName dimension in Cold Start metrics.

This is useful where you want to maintain the same name in case of auto generated handler names (cdk, top-level statement functions, etc.)

Example:

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using AWS.Lambda.Powertools.Metrics;

public class Function {

  [Metrics(FunctionName = "MyFunctionName", 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 {

  public Function()
  {
    Metrics.Configure(options =>
    {
        options.Namespace = "dotnet-powertools-test";
        options.Service = "testService";
        options.CaptureColdStart = true;
        options.FunctionName = "MyFunctionName";
    });
  }

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

AspNetCore

Installation

To use the Metrics middleware in an ASP.NET Core application, you need to install the AWS.Lambda.Powertools.Metrics.AspNetCore NuGet package.

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dotnet add package AWS.Lambda.Powertools.Metrics.AspNetCore

UseMetrics() Middleware

The UseMetrics middleware is an extension method for the IApplicationBuilder interface.

It adds a metrics middleware to the specified application builder, which captures cold start metrics (if enabled) and flushes metrics on function exit.

Example

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using AWS.Lambda.Powertools.Metrics.AspNetCore.Http;

var builder = WebApplication.CreateBuilder(args);

// Configure metrics
builder.Services.AddSingleton<IMetrics>(_ => new MetricsBuilder()
    .WithNamespace("MyApi") // Namespace for the metrics
    .WithService("WeatherService") // Service name for the metrics
    .WithCaptureColdStart(true) // Capture cold start metrics
    .WithDefaultDimensions(new Dictionary<string, string> // Default dimensions for the metrics
    {
        {"Environment", "Prod"},
        {"Another", "One"}
    })
    .Build()); // Build the metrics

builder.Services.AddAWSLambdaHosting(LambdaEventSource.RestApi);

var app = builder.Build();

app.UseMetrics(); // Add the metrics middleware

app.MapGet("/powertools", (IMetrics metrics) => 
    {
        // add custom metrics
        metrics.AddMetric("MyCustomMetric", 1, MetricUnit.Count);
        // flush metrics - this is required to ensure metrics are sent to CloudWatch
        metrics.Flush();
    });

app.Run();

Here is the highlighted UseMetrics method:

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/// <summary>
/// Adds a metrics middleware to the specified application builder.
/// This will capture cold start (if CaptureColdStart is enabled) metrics and flush metrics on function exit.
/// </summary>
/// <param name="app">The application builder to add the metrics middleware to.</param>
/// <returns>The application builder with the metrics middleware added.</returns>
public static IApplicationBuilder UseMetrics(this IApplicationBuilder app)
{
    app.UseMiddleware<MetricsMiddleware>();
    return app;
}

Explanation:

  • The method is defined as an extension method for the IApplicationBuilder interface.
  • It adds a MetricsMiddleware to the application builder using the UseMiddleware method.
  • The MetricsMiddleware captures and records metrics for HTTP requests, including cold start metrics if the CaptureColdStart option is enabled.

WithMetrics() filter

The WithMetrics method is an extension method for the RouteHandlerBuilder class.

It adds a metrics filter to the specified route handler builder, which captures cold start metrics (if enabled) and flushes metrics on function exit.

Example

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using AWS.Lambda.Powertools.Metrics;
using AWS.Lambda.Powertools.Metrics.AspNetCore.Http;

var builder = WebApplication.CreateBuilder(args);

// Configure metrics
builder.Services.AddSingleton<IMetrics>(_ => new MetricsBuilder()
    .WithNamespace("MyApi") // Namespace for the metrics
    .WithService("WeatherService") // Service name for the metrics
    .WithCaptureColdStart(true) // Capture cold start metrics
    .WithDefaultDimensions(new Dictionary<string, string> // Default dimensions for the metrics
    {
        {"Environment", "Prod"},
        {"Another", "One"}
    })
    .Build()); // Build the metrics

// Add AWS Lambda support. When the application is run in Lambda, Kestrel is swapped out as the web server with Amazon.Lambda.AspNetCoreServer. This
// package will act as the web server translating requests and responses between the Lambda event source and ASP.NET Core.
builder.Services.AddAWSLambdaHosting(LambdaEventSource.RestApi);

var app = builder.Build();

app.MapGet("/powertools", (IMetrics metrics) => 
    {
        // add custom metrics
        metrics.AddMetric("MyCustomMetric", 1, MetricUnit.Count);
        // flush metrics - this is required to ensure metrics are sent to CloudWatch
        metrics.Flush();
    })
    .WithMetrics();

app.Run();

Here is the highlighted WithMetrics method:

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/// <summary>
/// Adds a metrics filter to the specified route handler builder.
/// This will capture cold start (if CaptureColdStart is enabled) metrics and flush metrics on function exit.
/// </summary>
/// <param name="builder">The route handler builder to add the metrics filter to.</param>
/// <returns>The route handler builder with the metrics filter added.</returns>
public static RouteHandlerBuilder WithMetrics(this RouteHandlerBuilder builder)
{
    builder.AddEndpointFilter<MetricsFilter>();
    return builder;
}

Explanation:

  • The method is defined as an extension method for the RouteHandlerBuilder class.
  • It adds a MetricsFilter to the route handler builder using the AddEndpointFilter method.
  • The MetricsFilter captures and records metrics for HTTP endpoints, including cold start metrics if the CaptureColdStart option is enabled.
  • The method returns the modified RouteHandlerBuilder instance with the metrics filter added.

Testing your code

Unit testing

To test your code that uses the Metrics utility, you can use the TestLambdaContext class from the Amazon.Lambda.TestUtilities package.

You can also use the IMetrics interface to mock the Metrics utility in your tests.

Here is an example of how you can test a Lambda function that uses the Metrics utility:

Lambda Function

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using System.Collections.Generic;
using Amazon.Lambda.Core;

public class MetricsnBuilderHandler
{
    private readonly IMetrics _metrics;

    // Allow injection of IMetrics for testing
    public MetricsnBuilderHandler(IMetrics metrics = null)
    {
        _metrics = metrics ?? new MetricsBuilder()
            .WithCaptureColdStart(true)
            .WithService("testService")
            .WithNamespace("dotnet-powertools-test")
            .WithDefaultDimensions(new Dictionary<string, string>
            {
                { "Environment", "Prod1" },
                { "Another", "One" }
            }).Build();
    }

    [Metrics]
    public void Handler(ILambdaContext context)
    {
        _metrics.AddMetric("SuccessfulBooking", 1, MetricUnit.Count);
    }
}

Unit Tests

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[Fact]
    public void Handler_With_Builder_Should_Configure_In_Constructor()
    {
        // Arrange
        var handler = new MetricsnBuilderHandler();

        // Act
        handler.Handler(new TestLambdaContext
        {
            FunctionName = "My_Function_Name"
        });

        // Get the output and parse it
        var metricsOutput = _consoleOut.ToString();

        // Assert cold start
        Assert.Contains(
            "\"CloudWatchMetrics\":[{\"Namespace\":\"dotnet-powertools-test\",\"Metrics\":[{\"Name\":\"ColdStart\",\"Unit\":\"Count\"}],\"Dimensions\":[[\"Service\",\"Environment\",\"Another\",\"FunctionName\"]]}]},\"Service\":\"testService\",\"Environment\":\"Prod1\",\"Another\":\"One\",\"FunctionName\":\"My_Function_Name\",\"ColdStart\":1}",
            metricsOutput);
        // Assert successful Memory metrics
        Assert.Contains(
            "\"CloudWatchMetrics\":[{\"Namespace\":\"dotnet-powertools-test\",\"Metrics\":[{\"Name\":\"SuccessfulBooking\",\"Unit\":\"Count\"}],\"Dimensions\":[[\"Service\",\"Environment\",\"Another\",\"FunctionName\"]]}]},\"Service\":\"testService\",\"Environment\":\"Prod1\",\"Another\":\"One\",\"FunctionName\":\"My_Function_Name\",\"SuccessfulBooking\":1}",
            metricsOutput);
    }

    [Fact]
    public void Handler_With_Builder_Should_Configure_In_Constructor_Mock()
    {
        var metricsMock = Substitute.For<IMetrics>();

        metricsMock.Options.Returns(new MetricsOptions
        {
            CaptureColdStart = true,
            Namespace = "dotnet-powertools-test",
            Service = "testService",
            DefaultDimensions = new Dictionary<string, string>
            {
                { "Environment", "Prod" },
                { "Another", "One" }
            }
        });

        Metrics.UseMetricsForTests(metricsMock);

        var sut = new MetricsnBuilderHandler(metricsMock);

        // Act
        sut.Handler(new TestLambdaContext
        {
            FunctionName = "My_Function_Name"
        });

        metricsMock.Received(1).PushSingleMetric("ColdStart", 1, MetricUnit.Count, "dotnet-powertools-test",
            service: "testService", Arg.Any<Dictionary<string, string>>());
        metricsMock.Received(1).AddMetric("SuccessfulBooking", 1, MetricUnit.Count);
    }

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");