AWS introduced last year the SQS integration with AWS Lambda. In the following post, I’m going to share a quick-and-simple tutorial on how to get started with message distribution between Lambda functions, using SQS.
In addition, I will also compare between SQS and SNS (i.e. why should we choose one over the other), and present an in-depth performance analysis of using SQS as a message distributor.
Setup: AWS Lambda and SQS
I will use the Serverless Framework to send a message from one Lambda function to another Lambda function via SQS.
- npm installed.
- Serverless Framework installed.
- Python – Feel free to use your favorite programming language.
- AWS account (duh).
Let’s start by creating the serverless project:
serverless create --template aws-python3 --path sqs-lambda-tutorial
At this point, we can configure the
handler.py files. The code can be found in the following GitHub repo.
This yml file configures our functions, permissions and SQS resource.
This is where our code runs. It contains two functions. Each function represents a different AWS Lambda function. One will be triggered manually, and the other one will be triggered by an SQS message.
We will compare the SQS Lambda and the manual Lambda.
This is the magic of Lambda. Just run the following command while you are in the same folder as
The output should look roughly like this:
sls invoke -f start-lambda
sls logs -f start-lambda
sls logs -f end-lambda
We are done. Congrats! ⚡️
If you plan to use SQS in your application, you will need the event structure and data. You can find it in the following Gist.
SQS vs. SNS
When applied to Lambda only, this is a tough call. Up to this moment, only SNS supported triggering Lambda functions. Now both SNS and SQS can trigger. Let’s compare the relevant parameters for Serverless applications:
Performance Analysis: Serverless and SQS
Distributing messages between services can be complicated. Understanding the performance impact on our applications is almost impossible. At Epsagon, we love to see the bigger picture for highly distributed applications.
In a previous post, we compared several methods of distributing messages between functions (direct sync invocation, direct async invocation, SNS and Kinesis), and now, using our serverless performance monitoring tool, it’s a great time to introduce the results for SQS:
Lambda integrations are great. The more, the better. In this post, we learned how to deploy Lambda functions that distribute messages using SQS. We also saw an updated comparison between SQS and SNS for Serverless applications and understood the performance implications of distributing messages between functions.
Considering features, cost, and performance, SQS is the best choice for the task of message distribution between Lambda functions. For recent trends and examples of AWS Lambda and SQS, subscribe to get notified on all the latest insights.
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