title: How to use customized docker container with serverless framework
body: <p>I use serverless framework to deploy python function onto aws lambda</p>
  
  <p>my configuration file serverless.yml is following</p>
  
  <pre><code>frameworkVersion: "=1.27.3"
  
  service: recipes
  
  provider:
    name: aws
    endpointType: REGIONAL
    runtime: python3.6
    stage: dev
    region: eu-central-1
    memorySize: 512
    deploymentBucket:
      name: dfki-meta
    versionFunctions: false
    stackTags:
      Project: DFKIAPP
    # Allows updates to all resources except deleting/replacing EC2 instances
    stackPolicy:
      - Effect: Allow
        Principal: "*"
        Action: "Update:*"
        Resource: "*"
      - Effect: Deny
        Principal: "*"
        Action:
          - Update: Replace
          - Update: Delete
        Resource: "*"
        Condition:
          StringEquals:
            ResourceType:
              - AWS::EC2::Instance
    # Access to RDS and S3 Bucket
    iamRoleStatements:
      -  Effect: "Allow"
         Action: "s3:ListBucket"
         Resource: "*"
  
  package:
    individually: true
  
  
  
  functions:
    get_recipes:
      handler: handler.get_recipes
      module: recipes_crud
      package:
        include:
          - db/*
      timeout: 10
      events:
        - http:
            path: recipes
            method: get
            request:
              parameters:
                querystring:
                  persona: true
  
  
  
  plugins:
    # deploy conda package on lambda
    - serverless-python-requirements
  
  custom:
    pythonRequirements:
      dockerizePip: non-linux
      dockerFile: prod_env_dockerfile/Dockerfile
  </code></pre>
  
  <p>and my docker file</p>
  
  <pre><code>lambci/lambda:python3.6
  FROM lambci/lambda-base:build
  
  ENV PATH=/var/lang/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin \
      LD_LIBRARY_PATH=/var/lang/lib:/lib64:/usr/lib64:/var/runtime:/var/runtime/lib:/var/task:/var/task/lib \
      AWS_EXECUTION_ENV=AWS_Lambda_python3.6 \
      PYTHONPATH=/var/runtime \
      PKG_CONFIG_PATH=/var/lang/lib/pkgconfig:/usr/lib64/pkgconfig:/usr/share/pkgconfig
  
  RUN rm -rf /var/runtime /var/lang &amp;&amp; \
    curl https://lambci.s3.amazonaws.com/fs/python3.6.tgz | tar -xz -C / &amp;&amp; \
    sed -i '/^prefix=/c\prefix=/var/lang' /var/lang/lib/pkgconfig/python-3.6.pc &amp;&amp; \
    curl https://www.python.org/ftp/python/3.6.1/Python-3.6.1.tar.xz | tar -xJ &amp;&amp; \
    cd Python-3.6.1 &amp;&amp; \
    LIBS="$LIBS -lutil -lrt" ./configure --prefix=/var/lang &amp;&amp; \
    make -j$(getconf _NPROCESSORS_ONLN) libinstall inclinstall &amp;&amp; \
    cd .. &amp;&amp; \
    rm -rf Python-3.6.1 &amp;&amp; \
    pip3 install -U pip awscli virtualenv --no-cache-dir
  
  RUN yum install -y wget
  RUN wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
  RUN bash Miniconda3-latest-Linux-x86_64.sh -b -p $HOME/miniconda
  RUN export PATH="$HOME/miniconda/bin:$PATH" &amp;&amp; conda install -c prometeia -y pymssql
  </code></pre>
  
  <p>but seemingly sls do not use my dockerfile, it still create a image called sls-py-reqs-custom</p>
  
  <pre><code>(node:43146) ExperimentalWarning: The fs.promises API is experimental
  Serverless: Installing requirements of recipes_crud/requirements.txt in .serverless/recipes_crud...
  Serverless: Building custom docker image from prod_env_dockerfile/Dockerfile...
  Serverless: Docker Image: sls-py-reqs-custom
  Serverless: Packaging function: get_recipes...
  Serverless: Excluding development dependencies...
  Serverless: Injecting required Python packages to package...
  Serverless: Uploading function: get_recipes (29.08 MB)...
  Serverless: Successfully deployed function: get_recipes
  Serverless: Successfully updated function: get_recipes
  </code></pre>
  
  <p>How can I force serverless to use my customized docker ?</p>