lambda_layer_builder's Introduction

Create new Lambda Layer

Create S3 bucket for storing lambda layers

By default Lambda deployment package size is limited to 50MB. To overcome this limitation we will store lambda layer packages on S3 bucket.

Use an existing bucket or create a new one using the command below:

aws s3 mb s3://shuraosipov-lambda-layers

Update requirements.txt

Specify a list of packages you want to include to a layer in requirements.txt file.

Default content is:

amazon-textract-prettyprinter==0.0.10
amazon-textract-response-parser==0.1.20
pandas

Configure layer parameters

Provide python version, layer name, layer description and target S3 backet for storing layers in the confg file.

Default content is:

PYTHON_VERSION="python3.9"
LAYER_NAME="pandas-textract-reader"
LAYER_DESCRIPTION="Layer containing pandas, amazon-textract-response-parser and amazon-textract-prettyprinter libraries"
BUCKET_NAME="shuraosipov-lambda-layers"

Create a layer

From the app root folder:

$ cd build_scripts/
$ bash create_new_layer.sh config

You will see the following output:

Checking if necessary system packages is installed... Success!
Python version - python3.9
Package name - pandas-textract-reader-lambda-layer.zip
Building lambda layer in /tmp/tmp.nqoEObnXYl/python/lib/python3.9/site-packages/ folder
S3 bucket for storing lambda layer package - shuraosipov-lambda-layers
Installing dependencies...  Success!
Compiling the .zip file... Success!
Archive size is 45M
Uploading lambda layer package to S3... Success!
Publishing a layer...  Success!
Cleaning up... Success!
Enjoy your newly created layer - arn:aws:lambda:us-east-1:419091122511:layer:pandas-textract-reader:3

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