Customers use AWS Lambda to build Serverless applications for a wide variety of use cases, from simple API backends to complex data processing pipelines. Lambda’s flexibility makes it an excellent choice for many workloads, and with support for up to 10,240 MB of memory, you can now tackle compute-intensive tasks that were previously challenging in a Serverless environment. When you configure a Lambda function’s memory size, you allocate RAM and Lambda automatically provides proportional CPU power. When you configure 10,240 MB, your Lambda function has access to up to 6 vCPUs.
However, there’s an important consideration that many developers discover: simply allocating more memory may not automatically make your function faster. If your code runs sequentially, it will only use one vCPU regardless of how many are available. The remaining vCPUs sit idle while you’re still paying for the full memory allocation.
To help benefit from Lambda’s multi-core…
