Reducing Stage/Prod deployment Pipeline execution Time Using GenAI Models in AEM Cloud Manager

We are requesting for the development of a feature in Adobe Experience Manager (AEM) Cloud Manager that leverages Generative AI (GenAI) models to reduce the execution time required for stage and production deployment pipelines in AEM Cloud manager. This feature would fast-track regular deployment tasks in the Adobe Cloud pipeline using GenAI models , including Unit Testing, Code Scanning, Image Building, Product Functional Testing, Custom Functional Testing, Custom UI Testing, and Experience Audits.

Key Benefits:

1. Accelerated Deployment: GenAI models optimize and expedite deployment tasks, significantly reducing the overall pipeline time.
2. Enhanced Efficiency: Automate routine tasks such as unit testing and code scanning, allowing for faster and more reliable deployments.
3. Predictive Analytics: Utilize GenAI to predict potential issues and optimize the sequence of deployment tasks, ensuring smoother and quicker pipelines.
4. Customizable Workflows: Tailor deployment workflows to meet specific organizational needs, providing flexibility and control over the deployment process.
5. Improved Reliability: GenAI models continuously monitor and adjust workflows, ensuring consistent and reliable deployments.

Implementation Details:

• Integration with AEM Cloud Manager: Seamlessly integrate GenAI models within the existing AEM Cloud Manager framework.
• User Interface: Develop an intuitive UI for configuring and managing deployment tasks, allowing users to easily set up and monitor pipeline activities.
• GenAI Workflow Engine: Create a robust workflow engine powered by GenAI to handle the optimization, execution, and monitoring of deployment tasks.
• Analytics Dashboard: Provide a dashboard for users to view pipeline performance metrics, historical data, and predictive analytics.

This feature will significantly enhance the deployment capabilities of AEM Cloud Manager, offering users a powerful tool to manage stage and production pipelines efficiently and effectively. Essentially the idea is to reduce the overall execution time of Stage/Prod pipeline and hence making the deployments faster during the release calls etc. This will also reduce the manual effort/time spend during the release calls.