Lambda startup time code#
Lambda startup time zip#

Serverless does not only cover AWS Lambda and other FaaS providers, but basically everything you can use to run the code, host files, and store images and data. Essentially, it lets you focus on your code.

Lambda startup time code#

The serverless paradigm involves running code in the cloud without managing any servers, allowing you to build business logic and create value without ever thinking about the infrastructure or underlying software. Serverless architecture is the new kid on the block, and according to a recent survey by Serverless, Inc., a vast majority of developers will start using it by the end of the year. This means while running in Lambda and you want to use other AWS services you have to handcraft API calls to AWS using the Signature Version 4 Signing. Unfortunately, as of this post, there is no official or unofficial AWS SDK for Dart. With AOT everything required to run your main.dart is included in !

Lambda startup time zip#

For a JIT Lambda you have to zip and upload each file that is used since the Dart VM reads all of them at startup, much like using NodeJS.

BONUS: You only have to ship one compiled file! For me this was.

This means I can consistently use the 128MB memory configuration.

AOT memory consumption dropped from ~150-175MB to ~50MB.

After the cold start, I was seeing response times of <100ms, compared to JIT’s ~250-800ms.

Cold starts improved from ~1-1.5 second(s) to ~500ms.

AOT fixed some my complaints about the JIT approach. I used the same aws_lambda_dart code that I used within my JIT post but instead, I used the dart2aot tool to compile my Dart before uploading to Lambda. TL DR: Dart AOT is a fantastic fit for serverless workloads! I decided to give Dart AOT a shot since I’d already been down the Dart JIT path. This isn’t a huge deal in my apps but who wouldn’t want that experience to be as close to 0 as possible. It’s great that you only pay for 100ms compute intervals, but in my experience using Dart JIT and NodeJS, a cold start can take 1-1.5 seconds. If your process sits idle for a period of time AWS, again, evicts your process. The next time you invoke your function AWS starts a new process to handle your request. AWS evicts your function to make room for others. A cold start occurs when your function hasn’t been invoked for an extended period of time.

Nothing too special there, it has the required response properties Api Gateway requires and again keeping us honest with some type safety.įuture apiGatewaySquareNumber ( ApiGatewayEvent apiRequest, Context context, ) async Cold StartsĪ downside of serverless is cold starts. The second change I made was to add the return type of ApiGatewayResponse. However, with an ApiGatewayEvent, we have a typed input and I dig that! ApiGatewayEvent’s body remains a string and still needs to be parsed since this will be anything your HTTPS request sends in. This is just a parsed version of the Map from before. Now apiGatewaySquareNumber takes in an ApiGatewayEvent. For this reason, I made a small refactor to squareNumber to add Api Gateway support. I like to use AWS Lambda with API Gateway in my mobile apps. With startup time, memory consumption and execution time critical in a serverless environment I turned my focus on Dart’s dart2aot, see docs, to get a speed boost. In my previous post, Run Dart VM with AWS Lambda Custom Runtime, I covered how I got Dart running on AWS Lambda Custom Runtime.