AWS Lambda Cold Start

Giriş

Cold Start probleminin sebebi Scale To Zero

Scale To Zero

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What is “Scale to Zero”?

Simply put, “Scale to Zero” is a regular container deployment that automatically scales to zero instances when there is no incoming traffic. The moment a request hits the service, an instance is started to handle it. This is also commonly referred to as “cold start,” similar to e.g., AWS Lambdas.

Nearly all major cloud providers support “Scale to Zero” in some form or the other.

Cold Start Problemi

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When Lambda receives a request to execute a task, it starts by downloading the code from S3 buckets and creating an execution environment based on the predefined memory and its corresponding compute resources. If there is any initialization code, Lambda runs it outside the environment and then runs the handler code. The time required for downloading the code and preparing the execution environment is counted as the cold start duration. After executing the code, Lambda freezes the environment so that the same function can run quickly if invoked again. If you run the function concurrently, each invocation gets a cold start. There will also be a code start if the code is updated. The typical time for cold starts falls between 100 ms and 1 second. In light of the foregoing, Lambda falls short in the Lambda vs Fargate race regarding cold starts. However, Provisioned Concurrency is a solution to reduce cold starts.

The runtime choice will also have an impact on Lambda cold starts. For instance, Java runtime involves multiple resources to run the JVM environment, which delays the start. On the other hand, C# or Node.js runtime environments offer lower latencies.

Çözümler şöyle

1. Lambda Provisioned Concurrency

2. SnapStart

1. Lambda Provisioned Concurrency

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In other words, this facilitates the creation of pre-warmed Lambdas waiting to serve incoming requests. As this is pre-provisioned, the configured number of provisioned environments will be up and running all the time even if there are no requests to cater to. Therefore, this contradicts the very essence of serverless environments. Also, since environments are provisioned upfront, this feature is not free and comes with a considerable price.

2. SnapStart

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With SnapStart, Lambda initializes your function when you publish a function version. Lambda takes a Firecracker micro VM snapshot of the memory and disk state of the initialized execution environment, encrypts the snapshot, and caches it for low-latency access. When you invoke the function version for the first time, and as the invocations scale up, Lambda resumes new execution environments from the cached snapshot instead of initializing them from scratch, improving startup latency. The best part is that, unlike provisioned concurrency, there is no additional cost for SnapStart. SnapStart is currently only available for Java 11 (Corretto) runtime.

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Lambda SnapStart for Java is a new feature that enables you to resume new execution environments from cached snapshots without initializing them from scratch. It helps improve startup latency. However, this feature is only available for Java 11-managed runtime environments. There are other limitations as well. It does not support provisioned concurrency, Amazon X-Ray, Amazon EFS, or arm64 architecture. Moreover, you cannot use ephemeral storage of more than 512 MB.