Lambda Quotas
In the last classes we saw how to create functions that run serverless, that is, we don't need to worry about the infrastructure needed to execute the functions.
Ideally, we would like to run any function, with any time and memory requirement on AWS Lambda. But there are limits.
Question 1
Answer
You can see the quotas Here
Considering ML applications, it is common for them to use packages such as sklearn
, XGBoost
, lightgbm
, pandas
, etc. Since dependencies need to be packaged in ZIP, it is common to use hundreds of MiB or a few GiB.
Question 2
Answer
50 MB (zipped, for direct upload), 250 MB (unzipped), 3 MB (console editor).
Question 3
Answer
We could split the code into several layers, but notice that there is also limits for number of function layers.
Take a look at Container image code package size quota. Well, it turns out that we can also deploy functions to AWS lambda using containers! As the limit in this case is 10GB, we are able to deploy packages with dependencies larger than the ZIP limit.
Advance to the next topic to continue exploring this topic.