"The configurable parameter for all Serverless functions is the memory size. At AWS the CPU is doubled, when the memory is doubled. At Google this is also the case but only for 128 to 512 MB of memory, for 1GB and 2GB you get a little less additional CPU, actually they provide you with concrete numbers for the CPU power. Respective to following memory size 128,256,512,1024,2048 you get 200, 400, 800, 1400 and 2400 MHz. IBM lets you choose between three memory sizes from 128 to 512MB, but the CPU is fixed. Azure will automatically determine the memory need of the function, but assigns all functions the same computational power."
Thursday, September 27, 2018
Cloud Serverless performances compared
The largest benchmark of Serverless providers. – elbstack – Medium
"The configurable parameter for all Serverless functions is the memory size. At AWS the CPU is doubled, when the memory is doubled. At Google this is also the case but only for 128 to 512 MB of memory, for 1GB and 2GB you get a little less additional CPU, actually they provide you with concrete numbers for the CPU power. Respective to following memory size 128,256,512,1024,2048 you get 200, 400, 800, 1400 and 2400 MHz. IBM lets you choose between three memory sizes from 128 to 512MB, but the CPU is fixed. Azure will automatically determine the memory need of the function, but assigns all functions the same computational power."
"The configurable parameter for all Serverless functions is the memory size. At AWS the CPU is doubled, when the memory is doubled. At Google this is also the case but only for 128 to 512 MB of memory, for 1GB and 2GB you get a little less additional CPU, actually they provide you with concrete numbers for the CPU power. Respective to following memory size 128,256,512,1024,2048 you get 200, 400, 800, 1400 and 2400 MHz. IBM lets you choose between three memory sizes from 128 to 512MB, but the CPU is fixed. Azure will automatically determine the memory need of the function, but assigns all functions the same computational power."
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