A notable challenge within the realm of serverless architecture lies in the phenomenon known as "cold starts." A cold start occurs when a fresh instance of a function must be generated and initialized before processing an incoming request. While cold starts may not significantly impact applications that don't require an immediate response, such as background tasks or batch processes, they can pose substantial challenges when your AWS Lambda functions are integrated with API Gateway and are expected to deliver responses with minimal latency.
In scenarios where API Gateway and Lambda are closely coupled, cold starts can lead to delays in serving requests, affecting the overall responsiveness and user experience of your application.

There are different ways to prevent Lambda cold start

• Provisioned concurrency
• Cold start times are affected by the memory allocated to your Lambda function. Higher memory allocations come with more CPU power and network bandwidth.
• Reducing the size of your deployment packages generally leads to quicker cold start times. Achieve this by eliminating superfluous dependencies, files, or libraries from your deployment bundle and opting for minimalistic runtime environments whenever feasible.
• Create a specialized warm-up process, like a Lambda warm-up function, that triggers your Lambda function at regular intervals to ensure it remains in a warmed state. Another approach is to schedule recurring CloudWatch Events that invoke your function periodically, preventing it from experiencing full cold starts.

Provisioned Concurrency?

Provisioned concurrency initializes a requested number of execution environments so that they are prepared to respond immediately to your function's invocations. Note that configuring provisioned concurrency incurs charges to your AWS account.
With provisioned concurrency, you don't need to worry about cold starts because your Lambda functions will be in a warm state ready to respond immediately without initializations.

Lambda Warm State Setup with CDK

import * as cdk from 'aws-cdk-lib';
import * as lambda from 'aws-cdk-lib/aws-lambda';
import * as lambdaEventSources from 'aws-cdk-lib/aws-lambda-event-sources';

const myLambda = new lambda.Function(this, 'MyLambda', {
  runtime: lambda.Runtime.NODEJS_14_X,
  handler: 'index.handler',
  code: lambda.Code.fromAsset('path/to/lambda-code'),
  memorySize: 256,
});

const aliasOptions = {
  aliasName: 'MyAlias',
  version: myLambda.currentVersion,
  provisionedConcurrentExecutions: 2 //there will always be at least two Lambda functions running
};

new lambda.Alias(this, 'MyLambdaAlias', aliasOptions);

Conclusion

Apart from using provisioned concurrency, you can spend more time on making sure your Lambda function code is highly efficient by minimizing unnecessary initialization and resource allocation during function execution. You can also minimize the number of external dependencies your Lambda function relies on. Fewer dependencies mean less initialization work when the function starts.