Setting Up Your Environment
- Create an AWS account if you don't already have one, and set up your IAM credentials for accessing AWS services.
- Install the AWS CLI on your local machine and configure it using your AWS credentials. This will allow CircleCI to interact with AWS services using IAM roles.
aws configure
Create an Amazon AI Service
- Sign in to the AWS Management Console and navigate to the Amazon AI service you want to use (e.g., Amazon Rekognition, Amazon Comprehend, etc.).
- Set up any necessary models or configurations for your chosen Amazon AI service.
- Note down any relevant API endpoints and required credentials or setup details for integration.
Configuring CircleCI
- Create or access your CircleCI account and navigate to your project's Dashboard.
- Ensure your project is linked to a version control system like GitHub or Bitbucket.
- Add AWS credentials to CircleCI as environment variables. Navigate to 'Project Settings' > 'Environment Variables' and add your AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY here.
version: 2.1
executors:
aws-executor:
docker:
- image: circleci/python:3.8
jobs:
build:
executor: aws-executor
steps:
- checkout
- run:
name: Install AWS CLI
command: |
sudo apt-get -qq update
sudo apt-get install -y python3-pip
pip3 install awscli
- run:
name: Configure AWS CLI
command: aws configure list
Writing CircleCI Configurations
- Edit the `.circleci/config.yml` file in your project repository to set up your build and deployment process.
- Make sure to use AWS CLI commands in your CircleCI jobs to interact with Amazon AI services. This can include invoking APIs or managing AWS resources needed for your AI service.
- run:
name: Interact with Amazon AI
command: |
aws rekognition detect-labels --image "S3Object={Bucket=<YOUR-BUCKET>,Name=<YOUR-IMAGE>} --region <REGION>"
Trigger and Test Your Workflow
- Push changes to your main branch to trigger the CircleCI pipeline and ensure that your configurations are properly set up and executing as expected.
- Watch the CircleCI job and logs to confirm that your Amazon AI services are being utilized correctly.
- Review the data returned from Amazon AI APIs and ensure smooth operation and integration.
Advanced Considerations
- Consider setting up stack-specific IAM roles or policies if your project demands stricter access controls or uses multiple AWS services.
- Explore using AWS Lambda with CircleCI for serverless functions that can be triggered as part of your CI/CD pipeline for more extensive AI processing.
- run:
name: Trigger Lambda Function
command: |
aws lambda invoke --function-name <FUNCTION-NAME> output_file.txt