Cloud Platform Automated Patching via Offline Image Validation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current patching techniques in cloud computing environments, such as Microsoft Azure Stack, often cause interruptions and negatively impact user experience due to the need for updating entire files, which can lead to service disruptions and challenges in validating updates.
Innovation Solution
A cloud computing platform with a controller that identifies updates, downloads only the differences between the existing and updated services, merges these differences to create a new image, tests the new image offline, and validates it online, allowing for seamless updates with minimal disruption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If entire service files are updated during patching, then service security and functionality are improved, but service interruptions occur and user experience deteriorates
Solution Approach 1:
The patching process is segmented into distinct phases: offline image creation and validation, followed by online application. The update is first applied to create a new image offline, validated there, and only then applied online to production services. This segmentation allows security updates to be applied without causing service interruptions during the critical online operation phase.
Solution Approach 2:
The new image is created and validated in advance offline before being applied to online services. This preliminary action ensures that the update is tested and verified to be functional and secure before it is deployed to production, preventing service interruptions caused by faulty updates.
2Reliability
If entire service files are updated during patching, then service functionality is improved, but service downtime increases
Solution Approach 1:
The update process is divided into offline image preparation and online application stages. By preparing the complete updated image offline, the actual online update operation becomes a simple deployment of a pre-validated image, significantly reducing service downtime during the critical online phase.
Solution Approach 2:
The service file updates are performed in advance offline to create a complete new image. This preliminary action consolidates all update operations before they are applied online, minimizing the time services are disrupted during the actual deployment.
3Productivity
If automated patching is implemented, then patching efficiency is improved, but validation complexity increases
Solution Approach 1:
Validation is segmented into offline validation and online validation phases. The offline validation checks the new image before deployment, while online validation verifies the update after deployment. This segmentation allows comprehensive validation to be performed systematically without overwhelming complexity at any single stage, maintaining automated efficiency.
Data Source
AI summary
The application is directed to a cloud computing platform. The cloud computing platform includes a memory having instructions stored thereon for managing updates the cloud computing platform. The cloud computing platform also includes a controller, operably coupled to the memory. The controller is configured to execute an instruction of identifying an update for an existing cloud computing service operating on the cloud computing platform. The controller is also configured to download the update for the existing service. The controller is also configured to merge the differences between the downloaded update and the existing service to create a new image. The controller is also configured to test the new image offline. Further, the controller is configured to validate the new image online.