Furthermore, in order to build a comprehensive pipeline, the code quality, unit test, automated test, infrastructure provisioning, artifact building, dependency management and deployment tools involved have to connect using APIs and extend the required capabilities using IaC.
Vital components of a pipeline
we employed a three-stage strategy for validating and deploying the latest binary of the Real-time Prediction Service: staging integration test, canary integration test, and production rollout. The staging integration test and canary integration tests are run against non-production environments. Staging integration tests are used to verify the basic functionalities. Once the staging integration tests have been passed, we run canary integration tests to ensure the serving performance across all production models. After ensuring that the behavior for production models will be unchanged, the release is deployed onto all Real-time Prediction Service production instances, in a rolling deployment fashion.
3-stage strategy for validating and deploying the latest binary of the Real-time Prediction Service:
Private registry with AWS Secrets Manager sample for CodeBuild PDF Kindle RSS This sample shows you how to use a Docker image that is stored in a private registry as your AWS CodeBuild runtime environment. The credentials for the private registry are stored in AWS Secrets Manager. Any private registry works with CodeBuild. This sample uses Docker Hub.