Skip to content

lambgeo/docker-lambda

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

docker-lambda

Amazonlinux Docker images and AWS Lambda layers with GDAL.

Test

Docker Images

Based on public.ecr.aws/lambda/provided:al2 (AmazonLinux 2)

  • GDAL 3.8.3
    • ghcr.io/lambgeo/lambda-gdal:3.8 (Fev 2024)

Runtimes images:

  • Python (based on public.ecr.aws/lambda/python:{version})
    • ghcr.io/lambgeo/lambda-gdal:3.8-python3.9
    • ghcr.io/lambgeo/lambda-gdal:3.8-python3.10
    • ghcr.io/lambgeo/lambda-gdal:3.8-python3.11

archived

  • ghcr.io/lambgeo/lambda-gdal:3.6
  • ghcr.io/lambgeo/lambda-gdal:3.6-python3.9
  • ghcr.io/lambgeo/lambda-gdal:3.6-python3.10
  • ghcr.io/lambgeo/lambda-gdal:3.6-python3.11

see: https://github.com/lambgeo/docker-lambda/pkgs/container/lambda-gdal

Creating Lambda packages

Using

1. Create Dockerfile

FROM ghcr.io/lambgeo/lambda-gdal:3.8 AS gdal # We use the official AWS Lambda image FROM public.ecr.aws/lambda/{RUNTIME: python|node|go...}:{RUNTIME version} ENV PACKAGE_PREFIX=/var/task # Bring C libs from lambgeo/lambda-gdal image COPY --from=gdal /opt/lib/ ${PACKAGE_PREFIX}/lib/ COPY --from=gdal /opt/include/ ${PACKAGE_PREFIX}/include/ COPY --from=gdal /opt/share/ ${PACKAGE_PREFIX}/share/ COPY --from=gdal /opt/bin/ ${PACKAGE_PREFIX}/bin/ ENV \ GDAL_DATA=${PACKAGE_PREFIX}/share/gdal \ PROJ_LIB=${PACKAGE_PREFIX}/share/proj \ GDAL_CONFIG=${PACKAGE_PREFIX}/bin/gdal-config \ GEOS_CONFIG=${PACKAGE_PREFIX}/bin/geos-config \ PATH=${PACKAGE_PREFIX}/bin:$PATH # Copy local files or install modules # Create package.zip (we zip the whole content of $PACKAGE_PREFIX because we moved the gdal libs over) RUN cd $PACKAGE_PREFIX && zip -r9q /tmp/package.zip *

If you are working with python3.9|3.10|3.11|3.12|3.13, you can use lambgeo pre-build docker images:

FROM ghcr.io/lambgeo/lambda-gdal:3.8-python3.10 ENV PACKAGE_PREFIX=/var/task # Copy any local files to the package COPY handler.py ${PACKAGE_PREFIX}/handler.py # Install some requirements to `/var/task` (using `-t` otpion) RUN pip install numpy rasterio mercantile --no-binary :all: -t ${PACKAGE_PREFIX}/ # Reduce size of the C libs RUN cd $PREFIX && find lib -name \*.so\* -exec strip {} \; # Create package.zip # Archive python code (installed in $PACKAGE_PREFIX/) RUN cd $PACKAGE_PREFIX && zip -r9q /tmp/package.zip * # Archive GDAL libs (in $PREFIX/lib $PREFIX/bin $PREFIX/share) RUN cd $PREFIX && zip -r9q --symlinks /tmp/package.zip lib/*.so* share RUN cd $PREFIX && zip -r9q --symlinks /tmp/package.zip bin/gdal* bin/ogr* bin/geos* bin/nearblack

2. Build and create package.zip

docker build --tag package:latest . docker run --name lambda -w /var/task --volume $(shell pwd)/:/local -itd package:latest bash docker cp lambda:/tmp/package.zip package.zip docker stop lambda docker rm lambda

Package content should be like:

package.zip | |___ bin/ # GDAL binaries |___ lib/ # Shared libraries (GDAL, PROJ, GEOS...) |___ share/ # GDAL/PROJ data directories |___ rasterio/ .... |___ handler.py |___ other python module 

3. Deploy and Set Environment variables

Libraries might need to be aware of GDAL/PROJ C libraries so you HAVE TO to set up those 2 envs:

  • GDAL_DATA: /var/task/share/gdal
  • PROJ_LIB: /var/task/share/proj

Other variables:

Starting with gdal3.1 (PROJ 7.1), you can set PROJ_NETWORK=ON to use remote grids.

AWS Lambda Layers

gdal amazonlinux version size (Mb) unzipped size (Mb) arn
3.8 4 TBD TBD arn:aws:lambda:{REGION}:524387336408:layer:gdal38:{VERSION}

see /layer.json for the list of arns

Find the arn version

cat layer.json| jq '.[] | select(.region == "us-west-2")' { "region": "us-west-2", "layers": [ { "name": "gdal36", "arn": "arn:aws:lambda:us-west-2:524387336408:layer:gdal38:2", "version": 2 } ] }

archived layers

gdal amazonlinux version size (Mb) unzipped size (Mb) arn
3.6 2 26.8 76.1 arn:aws:lambda:{REGION}:524387336408:layer:gdal36:{VERSION}
3.5 2 30.5 73.4 arn:aws:lambda:{REGION}:524387336408:layer:gdal35:{VERSION}
3.3 2 27.7 67.3 arn:aws:lambda:{REGION}:524387336408:layer:gdal33-al2:{VERSION}
3.2 2 26.7 64.6 arn:aws:lambda:{REGION}:524387336408:layer:gdal32-al2:{VERSION}
3.1 2 25.8 61 arn:aws:lambda:{REGION}:524387336408:layer:gdal31-al2:{VERSION}
2.4 2 19.5 63.6 arn:aws:lambda:{REGION}:524387336408:layer:gdal24-al2:{VERSION}

see /archived_layer.json for the list of arns

Layer content:

layer.zip | |___ bin/ # Binaries |___ lib/ # Shared libraries (GDAL, PROJ, GEOS...) |___ share/ # GDAL/PROJ data directories 

At Lambda runtime, the layer content will be unzipped in the /opt directory. To be able to use the C libraries you HAVE TO make sure to set 2 important environment variables:

  • GDAL_DATA: /opt/share/gdal
  • PROJ_LIB: /opt/share/proj

How To Use (Create a Lambda Package)

There are 2 ways to use the layers:

1. Simple (No dependencies)

If you don't need to add more runtime dependencies, you can just create a lambda package (zip file) with your lambda handler.

Note: This is unlikely, except if you are using GDAL bin (e.g gdal_translate) from a python script.

zip -r9q package.zip handler.py

Content:

package.zip |___ handler.py # aws lambda python handler 

AWS Lambda Config:

  • arn: arn:aws:lambda:us-east-1:524387336408:layer:gdal38:1 (example)
  • env:
    • GDAL_DATA: /opt/share/gdal
    • PROJ_LIB: /opt/share/proj
  • lambda handler: handler.handler

2. Advanced (need other dependencies)

If your lambda handler needs more dependencies you'll have to use the exact same environment to create the package.

Create a Dockerfile
FROM ghcr.io/lambgeo/lambda-gdal:3.8 AS gdal # This example assume that you are creating a lambda package for python 3.10 FROM public.ecr.aws/lambda/python:3.10 # Bring C libs from lambgeo/lambda-gdal image COPY --from=gdal /opt/lib/ /opt/lib/ COPY --from=gdal /opt/include/ /opt/include/ COPY --from=gdal /opt/share/ /opt/share/ COPY --from=gdal /opt/bin/ /opt/bin/ ENV \ GDAL_DATA=/opt/share/gdal \ PROJ_LIB=/opt/share/proj \ GDAL_CONFIG=/opt/bin/gdal-config \ GEOS_CONFIG=/opt/bin/geos-config \ PATH=/opt/bin:$PATH ENV PACKAGE_PREFIX=/var/task # Copy local files COPY handler.py ${PACKAGE_PREFIX}/handler.py # install package # This example shows how to install GDAL python bindings for gdal 3.6 # The GDAL version should be the same as the one provided by the `lambgeo/lambda-gdal` image RUN python -m pip install GDAL==$(gdal-config --version) -t $PACKAGE_PREFIX # Create package.zip RUN cd $PACKAGE_PREFIX && zip -r9q /tmp/package.zip *
  • create package
docker build --tag package:latest . docker run --name lambda -w /var/task -itd package:latest bash docker cp lambda:/tmp/package.zip package.zip docker stop lambda docker rm lambda

Content:

package.zip |___ handler.py # aws lambda python handler |___ module1/ # dependencies |___ module2/ |___ module3/ |___ ... 

AWS Lambda Config:

  • arn: arn:aws:lambda:us-east-1:524387336408:layer:gdal38:1 (example)
  • env:
    • GDAL_DATA: /opt/share/gdal
    • PROJ_LIB: /opt/share/proj
  • lambda handler: handler.handler

About

AWS Lambda friendly GDAL Docker images and AWS Lambda layer

Topics

Resources

License

Stars

Watchers

Forks

Packages

 
 
 

Contributors 5