Using Pulumi with AWS SQS and Lambdas

Posted by Cyrus Najmabadi on Jul 10, 2018 12:14:30 PM
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Two weeks ago Amazon added Simple Queue Service (SQS) as a supported event source for Lambda. SQS is one of AWS’s oldest services, providing access to a powerful message queue that can do things like guarantee messages will be delivered at least once, or messages that will be processed in the same order they were received in. Adding SQS as a supported event source for Lambda means that now it’s possible to use SQS in a serverless computing infrastructure, where Lambdas are triggered in response to messages added to your SQS queue. Now, instead of needing some sort of Service dedicated to polling your SQS queue, or creating Simple Notification Service (SNS) notifications from your messages, you can instead just directly trigger whatever Lambda you want.

Example: Using AWS SQS and Lambda to post messages to Slack

Here’s a simple example of using SQS as an event source with Pulumi: upon receipt of a message via SQS we post a new message into Slack. The full project is available on Github in our examples repo, and includes the instructions to get this up and running.

let aws = require("@pulumi/aws");
let serverless = require("@pulumi/aws-serverless");
let config = require("./config");

let queue = new aws.sqs.Queue("mySlackQueue", { visibilityTimeoutSeconds: 180 });

serverless.queue.subscribe("mySlackPoster", queue, async (e) => {
    let slack = require("@slack/client");
    let client = new slack.WebClient(config.slackToken);
    for (let rec of e.Records) {
            channel: config.slackChannel,
            text: `*SQS message ${rec.messageId}*:\n${rec.body}\n`+
                `(with :love_letter: from Pulumi)`,
            as_user: true,
        console.log(`Posted SQS message ${rec.messageId} to Slack channel ${config.slackChannel}`);
}, { batchSize: 1 });

module.exports = {

Implementing SQS in Pulumi

When we heard about this new functionality, we immediately knew we wanted to let people access this new power from their Pulumi applications. Based on Amazon’s documentation on this new capability we felt it would likely be very easy to provide. Amazon introduced this functionality by reusing existing systems and APIs. Specifically, to create a Lambda trigger off an SQS message you only need to create a new Event Source Mapping mapping between the two. This seemed like it would be very simple, and we set off to expose the right Pulumi API to make this possible.

@pulumi/aws-serverless is Pulumi’s convenience library for creating Serverless computing components. And we added the necessary code to expose the functionality in our simple Pulumi programming model here. With this new API you would now be able to write code in your Pulumi application like so:

import * as aws from "@pulumi/aws";
import * as serverless from "@pulumi/aws-serverless";

// Create the queue.  Provide whatever specific configuration you need here.
const sqsQueue = new aws.sqs.Queue("queue", {
    visibilityTimeoutSeconds: 300,

// Set up a subscription that will fire whenever the queue receives a message.  Here we ask 
// for 'batchSize = 1' so we will only process a single message at a time.
serverless.queue.subscribe("subscription", sqsQueue, async (event) => {
    // Add whatever code you want here to run in the AWS lambda.  'event' will contain the
    // all the necessary data about the message added to the queue.
}, { batchSize: 1 });

This example also demonstrates several of the great capabilities of a Pulumi application. First, the ability to define your infrastructure directly in code (i.e. the AWS Queue, Lambda, and Event Subscriptions), instead of needing to do that separately. Second, the ability to avoid needing to specify every single AWS resource necessary to get up and running. For example, I did not have to supply explicit Roles, Role-Policy-Attachments, or Permissions here as Pulumi took care of that for me by default. Third, the ability to create an AWS Lambda directly from a JavaScript/TypeScript arrow-function. That async (event) => ... is written in code as a normal async-arrow-function, but it will be converted by Pulumi into all the machinery necessary to have a true AWS Lambda running in your infrastructure.

After adding the API and writing up a simple app to test things, we then ran a pulumi update to deploy our application to AWS. Unfortunately, we immediately ran into a problem:

Plan apply failed:
   Error creating Lambda event source mapping: ValidationException: 1 validation error detected: Value '' at
   'startingPosition' failed to satisfy constraint: Member must satisfy enum value set:

So what happened? Well, as it turns out, Pulumi leverages and integrates with many other amazing Open Source projects under the covers. In this case, it was our integration with Terraform that was causing this small snag. It turns out that while Amazon relaxed their API to no longer have that constraint on ‘startingPosition’, Terraform was still referencing an older awssdk API that still contained that constraint.

At Pulumi we think that Terraform is fantastic, and we love using it. So we thought the best thing we could do in this position was to help out that project to support this new functionality as well. We did this around two weeks ago by contributing this PR to their project. We worked with Terraform over a couple over a few days to get the PR up to snuff, and eventually got it in. With this, now both Terraform and Pulumi customers will be able to benefit from these changes in the upcoming releases for both projects!

After getting the change in we went back and tested our example and saw that now everything worked as expected. We also expanded things out in an example to show how you might use this in practice. In this example, we receive the event, and then just write the data of it into an S3 Bucket. Running this example we now successfully see:

pulumi update
Updating stack 'cysqstest'
Performing changes:

Type                                                Name                                        Status
+ pulumi:pulumi:Stack                               queue-cysqstest                             created
+ ├─ aws:serverless:Function                        subscription-queue-subscription             created
+ │ ├─ aws:iam:Role                                 subscription-queue-subscription             created
+ │ ├─ aws:iam:RolePolicyAttachment                 subscription-queue-subscription-32be53a2    created
+ │ ├─ aws:iam:RolePolicyAttachment                 subscription-queue-subscription-7cd09230    created
+ │ └─ aws:lambda:Function                          subscription-queue-subscription             created
+ ├─ aws:sqs:Queue                                  queue                                       created
+ ├─ aws:s3:Bucket                                  testbucket                                  created
+ └─ aws-serverless:queue:QueueEventSubscription    subscription                                created
+   ├─ aws:lambda:Permission                        subscription                                created
+   └─ aws:lambda:EventSourceMapping                subscription                                created

info: 11 changes performed:
+ 11 resources created
Update duration: 28s

Once created, we could then see this Stack at, and we could easily use the functionality there to even navigate to those resources over at our AWS Console. Over there were were able to use the console to both send a message to the Queue, verify our Lambda got triggered, and even check our Bucket to see the data written into it. In only around a dozen lines of code, we were able to provision 11 AWS resources, and create a real end-to-end Serverless message-receiving and processing pipeline. Now, we can expand on this functionality with more resources or more functionality, run pulumi update and just simply and safely update our cloud infrastructure!

You’ll see this functionality lighting up in our next release of @pulumi/pulumi and @pulumi/aws-serverless. We hope it helps you out and makes your cloud life that much easier. Happy coding!

Topics: JavaScript, Serverless, AWS

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