A company is developing a latency-sensitive application. Part of the application includes several AWS Lambda functions that need to initialize as quickly as possible. The Lambda functions are written in Java and contain initialization code outside the handlers to load libraries, initialize classes, and generate unique IDs.
Which solution will meet the startup performance requirement MOST cost-effectively?
To meet the startup performance requirement most cost-effectively, the best option is to update the Lambda functions by adding a pre-snapshot hook, move the code that generates unique IDs into the handlers, publish a version of each Lambda function, and activate Lambda SnapStart for the published versions of the Lambda functions. This approach leverages Lambda SnapStart to reduce startup time significantly by pre-initializing the function’s execution environment. It avoids the ongoing cost of provisioned concurrency while still providing a mechanism to minimize latency.
While option B improves startup performance, it is generally more expensive than SnapStart because it keeps environments warm continuously.
D Combining provisioned concurrency with SnapStart is redundant While provisioned concurrency reduces cold start latency, it is more costly compared to SnapStart because it keeps a set number of instances warm and ready to handle requests, even when not in use.
It is C
Provisioned concurrency – This is the number of pre-initialized execution environments allocated to your function. These execution environments are ready to respond immediately to incoming function requests. Provisioned concurrency is useful for reducing cold start latencies for functions. Configuring provisioned concurrency incurs additional charges to your AWS account.
"Lambda SnapStart for Java can improve startup performance for latency-sensitive applications by up to 10x at no extra cost". Answer C.
Leverages both versioning and provisioned concurrency. Also Lambda SnapStart for improved startup performance.