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DevOps your Skill: Deploy

When the code is checked in the previous steps, it is time to deploy the Skill to the Alexa cloud in order to start the next steps that will run different kind of tests. There are some tests like VUI tests, integrations tests, end-to-end tests and validation tests that we cannot run in localhost only with our code. This is why we need to deploy the Alexa Skill to the development stage.

These step are automated in the continuous integration system (GitHub Actions) and are executed in each new version of the software.

Prerequisites

Here you have the technologies used in this project

  1. ASK CLI - Install and configure ASK CLI
  2. GitHub Account - Sign up here
  3. Node.js v10.x
  4. Visual Studio Code

ASK CLI (Alexa Skill Kit CLI)

The Alexa Skills Kit Command Line Interface (ASK CLI) is a tool for you to manage your Alexa skills and related resources, such as AWS Lambda functions. With ASK CLI, you have access to the Skill Management API, which allows you to manage Alexa skills programmatically from the command line. We will use this powerful tool to validate our Alexa Skill. Let's start!

Installation

We need to install the ASK CLI or use it as it is included in the Docker image and the GitHub Action.

Deploy

In this step of the pipeline we are going to deploy our Alexa Skill using the ASK CLI to the development stage. When you deploy your skill to the development stage, it will update the skill manifest, interaction models, buckets, in-skill-purchasing products and lambda to the Alexa Cloud and AWS. We can use the following commands in the ASK CLI to manage this deployment of our Alexa skill:

  1. For ask cli v1:
    ask deploy --debug --force
  1. For ask cli v2:
    ask deploy --debug --ignore-hash

Reports

There are not reports defined in this job.

Integration

It is not necessary to integrate it in package.json file.

Pipeline Job

The deploy job will execute the following tasks:

  1. Checkout the code
  2. Copy the package.json to src/ folder.
  3. Execute the npm run build-production command that will install only the production libraries in the src/ folder.
  4. Run ask deploy --ignore-hash that will deploy all the code in src/ folder as an AWS lambda.
  deploy:
    runs-on: ubuntu-latest
    name: Deploy
    needs: codecov
    steps:
    # To use this repository's private action,
    # you must check out the repository
    - name: Checkout
      uses: actions/checkout@v2
    - run: |
        sudo npm install -g ask-cli;
        sudo apt-get install -y jq
        cd lambda;
        npm install;
        npm run copy-package;
        cd src;
        npm run build-production
    - run: ls -la && ask deploy --ignore-hash  
      env: # Or as an environment variable
        CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
        ASK_ACCESS_TOKEN: ${{ secrets.ASK_ACCESS_TOKEN }}
        ASK_REFRESH_TOKEN: ${{ secrets.ASK_REFRESH_TOKEN }}
        ASK_VENDOR_ID: ${{ secrets.ASK_VENDOR_ID }}
        AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
        AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
        SKILL_ID: ${{ secrets.SKILL_ID }}

NOTE: If you want to run successfully every ASK CLI command, you have to set up 5 secrets on GitHub Actions:

  • ASK_DEFAULT_PROFILE
  • ASK_ACCESS_TOKEN
  • ASK_REFRESH_TOKEN
  • ASK_VENDOR_ID
  • AWS_ACCESS_KEY_ID
  • AWS_SECRET_ACCESS_KEY

And configure the __ENVIRONMENT_ASK_PROFILE__ profile in your ask-resources.json and .ask/ask-states.json file.

How to obtain these variables and how to configure this profile are explained in this post

Resources

Conclusion

Thanks to the ASK CLI we can perform this complex task.

I hope this example project is useful to you.

That's all folks!

Happy coding!