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Testing AWS Lambda Functions (Serverless Framework) with OpenTelemetry and Tracetest

Tracetest is a testing tool based on OpenTelemetry that allows you to test your distributed application. It allows you to use data from distributed traces generated by OpenTelemetry to validate and assert if your application has the desired behavior defined by your test definitions.

AWS Lambda is a serverless, event-driven compute service that lets you run code for virtually any type of application or backend service without provisioning or managing servers. You can trigger Lambda from over 200 AWS services and software as a service (SaaS) applications, and only pay for what you use.

The Serverless Framework is an open-source framework designed to help developers build and deploy serverless applications more efficiently. It abstracts away the underlying infrastructure management tasks, allowing developers to focus solely on writing code and defining the functions that comprise their applications.

Why is this important?

Testing Serverless Functions has been a pain point for years. Not having visibility into the infrastructure and not knowing where a test fails causes the MTTR to be higher than for other tools. Including OpenTelemetry in AWS Lambda functions exposes telemetry that you can use for both production visibility and trace-based testing.

This sample shows how to run integration tests against AWS Lambda Functions with the help of the Serverless Framework to manage resources, and using OpenTelemetry and Tracetest.

The AWS Lambda function will fetch data from an external API, transform the data, and insert it into an AWS DynamoDB table. This particular flow has two failure points that are difficult to test.

  1. Validating that an external API request from an AWS Lambda function is successful.
  2. Validating that the DynamoDB put request is successful.

Prerequisites

Tracetest Account:

  • Copy the .env.template file to .env.
  • Log into the Tracetest app.
  • This example is configured to use the OpenTelemetry Collector. Ensure the environment you will be utilizing to run this example is also configured to use the OpenTelemetry Tracing Backend by clicking on Settings, Tracing Backend, OpenTelemetry, and Save.
  • Configure your environment to use the cloud agent, click the Click the Settings link and from the Agent tab select the "Run Agent in tracetest cloud" option.
  • Fill out the token and agent url details by editing your .env file. You can find these values in the Settings area for your environment.
  • Have your AWS Account with the AWS CLI installed and configured.

AWS Lambda Functions Example:

Clone the Tracetest GitHub Repo to your local machine, and open the Serverless quick start example app.

git clone https://github.com/kubeshop/tracetest.git
cd tracetest/examples/quick-start-serverless

Before moving forward, run npm i in the root folder to install the dependencies.

npm i

Project Structure

This is a Serverless Framework project bootstrapped with serverless.

1. AWS Lambda Function

The AWS Lambda Function code can be found in src/ alongside the OpenTelemetry wrapper configured as explained in the OpenTelemetry docs.

2. Tracetest

The tracetest.ts file contains the script that will execute the trace-based tests based on the serverless deployment.

AWS Lambda Function

The AWS Lambda is a simple API, contained in the src/handler.ts file.

import { APIGatewayEvent, Handler } from "aws-lambda";
import fetch from "node-fetch";
import { Pokemon, RawPokemon } from "./types";
import DynamoDb from "./dynamodb";

const Pokemon = (raw: RawPokemon): Pokemon => ({
id: raw.id,
name: raw.name,
types: raw.types.map((type) => type.type.name),
imageUrl: raw.sprites.front_default,
});

const getPokemon = async (id: string): Promise<Pokemon> => {
const url = `https://pokeapi.co/api/v2/pokemon/${id}`;
const res = await fetch(url);

const raw = await res.json();

return Pokemon(raw);
};

const insertPokemon = async (pokemon: Pokemon) => {
await DynamoDb.put(pokemon);

return DynamoDb.get<Pokemon>(pokemon.id);
};

type TBody = { id: string };

export const importPokemon: Handler<APIGatewayEvent> = async (event) => {
console.log(event);

const { id = "" } = JSON.parse(event.body || "") as TBody;

try {
const pokemon = await getPokemon(id);
const result = await insertPokemon(pokemon);

return {
statusCode: 200,
body: JSON.stringify(result),
};
} catch (error) {
return {
statusCode: 400,
body: error.message,
};
}
};

The OpenTelemetry tracing is contained in the src/lambda-wrapper.ts file. Traces will be sent to the Tracetest Cloud Agent.

const api = require("@opentelemetry/api");
const { BatchSpanProcessor } = require("@opentelemetry/sdk-trace-base");
const { OTLPTraceExporter } = require("@opentelemetry/exporter-trace-otlp-grpc");
const { NodeTracerProvider } = require("@opentelemetry/sdk-trace-node");
const { registerInstrumentations } = require("@opentelemetry/instrumentation");
const { getNodeAutoInstrumentations } = require("@opentelemetry/auto-instrumentations-node");

api.diag.setLogger(new api.DiagConsoleLogger(), api.DiagLogLevel.ALL);

const { COLLECTOR_ENDPOINT = "" } = process.env;

const provider = new NodeTracerProvider();

const spanProcessor = new BatchSpanProcessor(
new OTLPTraceExporter({
url: COLLECTOR_ENDPOINT,
})
);

provider.addSpanProcessor(spanProcessor);
provider.register();

registerInstrumentations({
instrumentations: [
getNodeAutoInstrumentations({
"@opentelemetry/instrumentation-aws-lambda": {
disableAwsContextPropagation: true,
},
}),
],
});

Set up Environment Variables

Copy the .env.template and create a .env file in the same directory. Add token and Cloud Agent endpoint.

TRACETEST_AGENT_ENDPOINT=<my_agent_endpoint>
TRACETEST_API_KEY=<my_token_with_engineer_access>

The Tracetest Script

The tracetest.ts file contains the script that will execute the trace-based tests based on the serverless deployment.

import Tracetest from "@tracetest/client";
import { TestResource } from "@tracetest/client/dist/modules/openapi-client";
import { config } from "dotenv";

config();

const { TRACETEST_API_TOKEN = "", ENDPOINT = "" } = process.env;

const definition: TestResource = {
type: "Test",
spec: {
id: "ZV1G3v2IR",
name: "Serverless: Import Pokemon",
trigger: {
type: "http",
httpRequest: {
method: "POST",
url: "${var:ENDPOINT}/import",
body: '{"id": "${var:POKEMON_ID}"}\n',
headers: [
{
key: "Content-Type",
value: "application/json",
},
],
},
},
specs: [
{
selector: 'span[tracetest.span.type="database"]',
name: "All Database Spans: Processing time is less than 100ms",
assertions: ["attr:tracetest.span.duration < 100ms"],
},
{
selector: 'span[tracetest.span.type="http"]',
name: "All HTTP Spans: Status code is 200",
assertions: ["attr:http.status_code = 200"],
},
{
selector:
'span[name="tracetest-serverless-dev-api"] span[tracetest.span.type="http" name="GET" http.method="GET"]',
name: "The request matches the pokemon Id",
assertions: ['attr:http.url = "https://pokeapi.co/api/v2/pokemon/${var:POKEMON_ID}"'],
},
],
},
};

const main = async () => {
const tracetest = await Tracetest(TRACETEST_API_TOKEN);

const test = await tracetest.newTest(definition);
await tracetest.runTest(test, {
variables: [
{
key: "ENDPOINT",
value: ENDPOINT.trim(),
},
{
key: "POKEMON_ID",
value: `${Math.floor(Math.random() * 100) + 1}`,
},
],
});
console.log(await tracetest.getSummary());
};

main();

The output from the tracetest.ts script will show the test results with links to the Tracetest App.

> tracetest-serverless@1.0.0 test
> ENDPOINT="$(serverless info --verbose | grep HttpApiUrl | sed s/HttpApiUrl\:\ //g)" ts-node tracetest.ts


Successful: 1
Failed: 0

[✔️ Serverless: Import Pokemon] #21 - https://app.tracetest.io/organizations/<YOUR_ORG>/environments/<YOUR_ENV>/test/ZV1G3v2IR/run/21

Tracetest App Results

Tracetest App Results

To run the tests without deploying the serverless stack, you can use the npm test command.

Running the example

Spin up the deployment and test execution.

npm start

This will trigger the serverless deploy command and immediately run the trace-based tests using the Tracetest Typescript integration after completion.

Learn More

Feel free to check out our examples in GitHub and join our Slack Community for more info!