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ℹ️  SignalFx was acquired by Splunk in October 2019. See Splunk SignalFx for more information.

⚠️ Deprecation Notice

The SignalFx Node.js Lambda Wrapper has reached End of Support and has been permanently archived.

The Splunk OpenTelemetry Lambda Layer is the successor. To learn how to migrate, see the supporting documentation


GitHub branch checks state npm

SignalFx Node.js Lambda Wrapper

Overview

You can use this document to add a SignalFx wrapper to your AWS Lambda for Node.js.

The SignalFx Node.js Lambda Wrapper wraps around an AWS Lambda Node.js function handler, which allows metrics and traces to be sent to SignalFx.

At a high-level, to add a SignalFx Node.js Lambda wrapper, you can:

  • Package the code yourself; or
  • Use a Lambda layer containing the wrapper, and then attach the layer to a Lambda function.

To learn more about Lambda Layers, please visit the AWS documentation site.

Step 1: Add the Lambda wrapper in AWS

To add the SignalFx wrapper, you have the following options:

  • Option 1: In AWS, create a Lambda function, then attach a SignalFx-hosted layer with a wrapper.
    • If you are already using Lambda layers, then SignalFx recommends that you follow this option.
    • In this option, you will use a Lambda layer created and hosted by SignalFx.
  • Option 2: In AWS, create a Lambda function, then create and attach a layer based on a SignalFx SAM (Serverless Application Model) template.
    • If you are already using Lambda layers, then SignalFx also recommends that you follow this option.
    • In this option, you will choose a SignalFx template, and then deploy a copy of the layer.
  • Option 3: Use the wrapper as a regular dependency, and then create a Lambda function based on your artifact containing both code and dependencies.

For advanced users who want to reduce the size of deployment packages, you can use the wrapper as a developer dependency, but in production, you would add the wrapper to layer in the Lambda environment. This option allows you to work with the wrapper in a local setting and reduce the size of deployment packages at the same time. Please note that this option is not fully documented.

Option 1: Create a Lambda function, then attach the SignalFx-hosted Lambda layer

In this option, you will use a Lambda layer created and hosted by SignalFx.

  1. To verify compatibility, review the list of supported regions. See Lambda Layer Versions.
  2. Open your AWS console. 
  3. In the landing page, under Compute, click Lambda.
  4. Click Create function to create a layer with SignalFx's capabilities.
  5. Click Author from scratch.
  6. In Function name, enter a descriptive name for the wrapper. 
  7. In Runtime, select the desired language.
  8. Click Create function
  9. Click Layers, then add a layer.
  10. Mark Provide a layer version.
  11. Enter an ARN number.

Option 2: Create a Lambda function, then create and attach a layer based on a SignalFx template

In this option, you will choose a SignalFx template, and then deploy a copy of the layer.

  1. Open your AWS console.
  2. In the landing page, under Compute, click Lambda.
  3. Click Create function to create a layer with SignalFx's capabilities.
  4. Click Browse serverless app repository.
  5. Click Public applications.
  6. In the search field, enter and select wrapper-node-sfx-app.
  7. Review the template, permissions, licenses, and then click Deploy.
    • A copy of the layer will now be deployed into your account.
  8. Return to the previous screen to add a layer to the function, select from list of runtime compatible layers, and then select the name of the copy.

Option 3: Install the wrapper package with npm

Run the following installation script in your command line to install latest version of the wrapper:

npm install signalfx-lambda

Make sure the package is saved to your package.json. (Newer versions of npm perform this function automatically.)

Step 2: Locate the ingest endpoint

By default, this function wrapper will send data to the us0 realm. As a result, if you are not in the us0 realm and you want to use the ingest endpoint directly, then you must explicitly set your realm.

To locate your realm:

  1. Open SignalFx and in the top, right corner, click your profile icon.
  2. Click My Profile.
  3. Next to Organizations, review the listed realm.

To set your realm, use a subdomain, such as ingest.us1.signalfx.com or ingest.eu0.signalfx.com. You will use the realm subdomain to set SIGNALFX_ENDPOINT_URL and SIGNALFX_METRICS_URL variables in the next step.

Step 3: Set environment variables

  1. Set SIGNALFX_ACCESS_TOKEN with your correct access token. Review the following example.
     SIGNALFX_ACCESS_TOKEN=access-token
  2. Set the service name and environment name as in the following example:
    SIGNALFX_SERVICE_NAME=<service_name>
    SIGNALFX_SPAN_TAGS=deployment.environment:<your-environment-name>
    
  3. If you use OpenTelemetry Collector, or want to ingest directly from a realm other than us0, then you must set at least one endpoint variable. (For environment variables, SignalFx defaults to the us0 realm. As a result, if you are not in the us0 realm, you may need to set your environment variables.) There are two options:

Option 1.

You can update SIGNALFX_ENDPOINT_URL and SIGNALFX_METRICS_URL where traces will be sent to the Otel collector and metrics will go directly to the ingest endpoint, respectively.

SIGNALFX_METRICS_URL=https://ingest.<realm>.signalfx.com
SIGNALFX_ENDPOINT_URL=http://<otel-collector-host>:9411/api/v2/spans

Note that the you'll need to specify the full path when sending to Otel collector i.e, `http://:9411/api/v2/spans.

Option 2.

You can update SIGNALFX_ENDPOINT_URL and SIGNALFX_METRICS_URL to send spans and metrics respectively directly to the SignalFx backend. Refer step 2 above (locate the ingest endpoint) to figure out the SignalFx ingest URL.

SIGNALFX_METRICS_URL=https://ingest.<realm>.signalfx.com
SIGNALFX_ENDPOINT_URL=https://ingest.<realm>.signalfx.com/v2/trace

To learn more, see: Deploying the OpenTelemetry Collector

  1. (Optional) Update SIGNALFX_SEND_TIMEOUT. Review the following example.

    SIGNALFX_SEND_TIMEOUT=milliseconds for signalfx client timeout [1000]
  2. (Optional) Globally disable metrics or tracing by setting SIGNALFX_TRACING_ENABLED and/or SIGNALFX_METRICS_ENABLED to "false".

    SIGNALFX_TRACING_ENABLED=false [defaults to true]
    SIGNALFX_METRICS_ENABLED=false [defaults to true]

Step 4: Wrap a function

  1. Wrap your function handler to enable both metrics and traces. Review the following example.

    'use strict';
    
    const signalFxLambda = require('signalfx-lambda');
    
    exports.handler = signalFxLambda.wrapper((event, context, callback) => {
    ...
    });

    You can also use signalFxLambda.wrapperMetrics or signalFxLambda.wrapperTracing to enable only either metrics or tracing.

  2. Use async/await. Review the following example.

    'use strict';
    
    const signalFxLambda = require('signalfx-lambda');
    
    exports.handler = signalFxLambda.asyncWrapper(async (event, context) => {
    ...
    });

    You can also use signalFxLambda.asyncWrapperMetrics or signalFxLambda.asyncWrapperTracing to enable only either metrics or tracing.

(Optional) Step 5: Send custom metrics from a Lambda function

  1. If you use synchronous wrapper, review the following example.

    'use strict';
    
    const signalFxLambda = require('signalfx-lambda');
    
    exports.handler = signalFxLambda.wrapper((event, context, callback) => {
      ...
      signalFxLambda.helper.sendGauge('gauge.name', value);
      callback(null, 'Done');
    });
  2. If you use async/await, review the following example.

    'use strict';
    
    const signalFxLambda = require('signalfx-lambda');
    
    exports.handler = signalFxLambda.asyncWrapper(async (event, context) => {
      ...
      signalFxLambda.helper.sendGauge('gauge.name', value);
    });

(Optional) Step 6: Send custom events or CloudWatch events from a Lambda function

  1. If you use synchronous wrapper, review the following example.

    'use strict';
    
    const signalFxLambda = require('signalfx-lambda');
    
    exports.handler = signalFxLambda.wrapper((event, context, callback) => {
      ...
      // to send custom event:
      signalFxLambda.helper.sendCustomEvent('Custom', {functionName: context.functionName}, {description: 'Custom event'});
    
      // to transform & forward CloudWatch event:
      signalFxLambda.helper.sendCloudWatchEvent(event);
    
      callback(null, 'Done');
    });
  2. If you use async/await, review the following example.

    'use strict';
    
    const signalFxLambda = require('signalfx-lambda');
    
    exports.handler = signalFxLambda.asyncWrapper(async (event, context) => {
      ...
      // to send custom event:
      signalFxLambda.helper.sendCustomEvent('Custom', {functionName: context.functionName}, {description: 'Custom event'});
    
      // to transform & forward CloudWatch event:
      signalFxLambda.helper.sendCloudWatchEvent(event);
      ...
    });

For additional examples see sample functions forwarding events to SignalFx.

Additional information and optional steps

Metrics and dimensions sent by the wrapper

The Lambda wrapper sends the following metrics to SignalFx:

Metric Name Type Description
function.invocations Counter Count number of Lambda invocations
function.cold_starts Counter Count number of cold starts
function.errors Counter Count number of errors from underlying Lambda handler
function.duration Gauge Milliseconds in execution time of underlying Lambda handler

The Lambda wrapper adds the following dimensions to all data points sent to SignalFx:

Dimension Description
lambda_arn ARN of the Lambda function instance
aws_region AWS Region
aws_account_id AWS Account ID
aws_function_name AWS Function Name
aws_function_version AWS Function Version
aws_function_qualifier AWS Function Version Qualifier (version or version alias if it is not an event source mapping Lambda invocation)
event_source_mappings AWS Function Name (if it is an event source mapping Lambda invocation)
aws_execution_env AWS execution environment (e.g. AWS_Lambda_nodejs10.x)
function_wrapper_version SignalFx function wrapper qualifier (e.g. signalfx-lambda-0.0.9)
metric_source The literal value of 'lambda_wrapper'

Tags sent by the tracing wrapper

The tracing wrapper creates a span for the wrapper handler. This span contains the following tags:

Tag Description
aws_request_id AWS Request ID
lambda_arn ARN of the Lambda function instance
aws_region AWS region
aws_account_id AWS account ID
aws_function_name AWS function name
aws_function_version AWS function version
aws_function_qualifier AWS function version qualifier (version or version alias if it is not an event source mapping Lambda invocation)
event_source_mappings AWS function name (if it is an event source mapping Lambda invocation)
aws_execution_env AWS execution environment (e.g., AWS_Lambda_nodejs12.x)
function_wrapper_version SignalFx function wrapper qualifier (e.g., signalfx_lambda_0.0.2)
component The literal value of 'nodejs-lambda-wrapper'

Adding Extra Tags

Extra tags can be added to all spans by setting the SIGNALFX_SPAN_TAGS environment variable to a comma-separated string of key value pairs. For example, if you set SIGNALFX_SPAN_TAGS environment variable to environment: production, build_id: 5842, then all spans generated by the Lambda function (both manual and ones generated by auto-instrumentation) will contain the following tags:

  environment = production
  build_id = 5843

Adding tags manually

If you want to add extra tags to specific spans instead of all spans, use the following snippet inside your lambda handler (i.e. this code has to run during lambda handler invocation, not as a part of the cold start logic):

const tracing = require("signalfx-lambda/tracing");

// this sample uses asyncWrapper but the logic is the same when
// the synchronous wrapper is used
exports.handler = signalFxLambda.asyncWrapper(async (event, context) => {
  const tracer = tracing.tracer();
  tracer.scope().active().setTag("my-custom-tag", "some-value");
});

Trace context propagation

The wrapper provides some support for trace context propagation across service boundaries. By default, you can propagate trace context across Lambda boundaries in these situations:

  • Events are coming in from an Amazon API Gateway and outgoing requests use HTTP/S.
  • You programatically execute events with a payload that includes B3-compatible key-value pairs in headers.

Other situations, such as receiving requests from Amazon CloudFront or sending output to Lambda destinations, aren't supported by default. In these cases, configure trace context propagation manually.

This example shows you how to manually configure trace context propagation when you're calling another service using a method that's not HTTP/S:

const tracing = require("signalfx-lambda/tracing");

// this sample uses asyncWrapper but the logic is the same when
// the synchronous wrapper is used
exports.handler = signalFxLambda.asyncWrapper(async (event, context) => {
  const contextCarrier = {}; // any writeable object
  tracing.inject(contextCarrier);
  // contextCarrier is now extended with "X-B3-*" fields, which should be extracted on the receiving end
  // no fields will be added unless there's an active span at the time when inject() is called

  // inject contextCarrier such that it can be accessed as `event.headers` from within the invoked lambda.
});

contextCarrier must be injected into the headers or payload of your outgoing request. Context propagation will work correctly as long as the context you injected can be accessed as event.headers from within the invoked Lambda.

Asynchronous Metrics and Events Delivery

Although the following signalFxLambda.helper.send* methods all return promises that resolve when send operation completes it is recommended to ignore those promises as the wrapper is going to wait for their completion internally.

This way multiple send operations may run concurrently without blocking your lambda handler code.

You can still await any of those promises if your use case forces you to do so.

function sendGauge(metricName, metricValue, dimensions);
function sendCounter(metricName, metricValue, dimensions);
function sendCustomEvent(type, dimensions, properties, timestamp);
function sendCloudWatchEvent(cwevent);

Deployment

  1. Run npm pack to package the module with the configuration in package.json.

Test

  1. Install node-lambda via npm install -g node-lambda (globally) or npm install node-lambda (locally).

Test locally

  1. Create deploy.env to submit data to SignalFx, which will include the required and optional environment variables mentioned above.

  2. Run node-lambda run -f deploy.env.

Test from AWS

  1. Run node-lambda deploy -f deploy.env to deploy to AWS, which will use any environment variables configured in .env. For example:

Unit Tests in IntelliJ IDEA

  1. Install Jasmine IDE plugin

  2. Create a new run configuration and point it to Jasmine config file .../signalfx/lambda-nodejs/spec/config/jasmine.json

AWS_ENVIRONMENT=
AWS_PROFILE=
AWS_SESSION_TOKEN=
AWS_HANDLER=index.handler
AWS_MEMORY_SIZE=128
AWS_TIMEOUT=3
AWS_DESCRIPTION=
AWS_RUNTIME=nodejs10.x
AWS_VPC_SUBNETS=
AWS_VPC_SECURITY_GROUPS=
AWS_TRACING_CONFIG=
AWS_REGION=us-east-2
AWS_FUNCTION_NAME=my-function
AWS_ROLE_ARN=arn:aws:iam::someAccountId:role/someRole
PACKAGE_DIRECTORY=build

License

Apache Software License v2. Copyright © 2014-2020 Splunk, Inc.