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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, 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

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AWS Lambda friendly GDAL Docker images and AWS Lambda layer

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aws-lambda serverless gdal geospatial-processing amazonlinux lambda-layers

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