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In AWS lambda environment we can specify only the memory configuration. Is there any documentation as to what the CPU config will be for a given memory configuration?
For example,
ApiLambda:
Type: AWS::Serverless::Function
Properties:
Description: "This function handles the example"
CodeUri: "./app/"
Handler: "app.handle_request"
MemorySize: 128
Timeout: 60
Runtime: python3.7
I am trying to find the minimum MemorySize for a particular number of cores.
Is there any way to know the boundaries of MemorySize where the #Cores changes without bruteforcing MemorySize?
Ref:
https://aws.amazon.com/about-aws/whats-new/2020/12/aws-lambda-supports-10gb-memory-6-vcpu-cores-lambda-functions/ https://docs.aws.amazon.com/lambda/latest/dg/configuration-memory.html
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The Lambda console defaults new functions to the smallest setting and many developers also choose 128 MB for their functions. However, 128 MB should usually only be used for the simplest of Lambda functions, such as those that transform and route events to other AWS services.
Starting today, you can allocate up to 10 GB of memory to a Lambda function. This is more than a 3x increase compared to previous limits. Lambda allocates CPU and other resources linearly in proportion to the amount of memory configured. That means you can now have access to up to 6 vCPUs in each execution environment.
AWS Lambda Functions Powered by AWS Graviton2 Processor – Run Your Functions on Arm and Get Up to 34% Better Price Performance. Many of our customers (such as Formula One, Honeycomb, Intuit, SmugMug, and Snap Inc.) use the Arm-based AWS Graviton2 processor for their workloads and enjoy better price performance.
The more memory, the more CPU resource and network bandwidth the function receives but also the higher cost per millisecond of execution time. For CPU intensive workloads, raising the memory allocation setting is a great way to give the function more power to complete the workload quicker.
In AWS lambda environment we can specify only the memory configuration. Is there any documentation as to what the CPU config will be for a given memory configuration?
AWS Lambda customers can now provision Lambda functions with a maximum of 10,240 MB (10 GB) of memory, a more than 3x increase compared to the previous limit of 3,008 MB. This helps workloads like batch, extract, transform, load (ETL) jobs, and media processing applications perform memory intensive operations at scale.
AWS Lambda runs your code on an highly available and scalable compute infrastructure so that you can focus on what you want to build. Do you want to get the advantages of Lambda for workloads that are memory or computationally intensive? Wait no more! Starting today, you can allocate up to 10 GB of memory to a Lambda function.
Memory is the amount of memory available to your Lambda function at runtime. You can increase or decrease the memory and CPU power allocated to your function using the Memory (MB) setting. To configure the memory for your function, set a value between 128 MB and 10,240 MB in 1-MB increments.
The official thresholds are:
Recent study concludes the following for what is happening in-between:
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