Deployment Engine Pre-Validation for Cloud Application Failures
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Solution Overview
Problem
The complexity of cloud-based application deployments makes it difficult to validate environment requirements and deployment logs, leading to potential failures that are hard to identify until after complete deployment, and existing validation approaches only determine failures post-deployment.
Innovation Solution
Implementing a pre-deployment validation process using a deployment engine that checks system and artifact requirements before deployment, with post-deployment validation and rollback options to ensure successful deployment and immediate error correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If deployment validation is performed only after complete deployment, then the deployment process can proceed without interruptions, but failures cannot be determined until after deployment and troubleshooting time increases
Solution Approach 1:
The patent performs validation checks before deployment (pre-deployment validation) to identify potential failures upfront. This includes validating environment requirements, artifact properties, and system configuration before the actual deployment occurs, preventing failures rather than detecting them after deployment.
Solution Approach 2:
The patent implements continuous feedback mechanisms during deployment by performing post-deployment validation checks immediately after each artifact is deployed. This real-time feedback allows the system to detect failures as they occur and trigger rollbacks or terminations before complete deployment, reducing troubleshooting time.
2Reliability
If pre-deployment validation checks are performed for each artifact, then deployment failures can be detected early, but the deployment process becomes more complex and time-consuming
Solution Approach 1:
The patent divides the validation process into distinct segments: pre-deployment validation of system requirements, pre-deployment validation of each artifact's properties, post-deployment validation of each artifact, and post-deployment validation of the complete system. This segmentation makes the complex validation process manageable and systematic.
Solution Approach 2:
The patent performs preliminary validation of environment requirements and artifact properties before deployment begins. This includes checking if the target environment meets system requirements and if artifacts have the necessary properties, thereby simplifying the overall process by catching issues early.
3Difficulty of detecting and measuring
If deployment validation is performed for each artifact individually, then specific failed artifacts can be identified, but the overall deployment time increases
Solution Approach 1:
The patent performs post-deployment validation immediately after each artifact is deployed, maintaining continuous validation throughout the deployment process. This continuous action ensures failures are detected at the moment they occur without interrupting the overall deployment flow, allowing rapid identification and rollback of specific failed artifacts.
Solution Approach 2:
The patent uses pre-deployment validation to skip unnecessary deployment steps. By validating environment requirements and artifact properties before deployment, the system can identify and terminate failed deployments early, skipping the time-consuming process of deploying and then troubleshooting failed artifacts.
4Reliability
If rollback mechanism is implemented for failed deployments, then system integrity is maintained, but the deployment process becomes more complex
Solution Approach 1:
The patent performs preliminary validation of environment requirements and artifact properties before deployment to prevent failures. This preliminary action reduces the need for rollbacks by catching issues before they occur, thereby maintaining system integrity while minimizing the complexity of rollback mechanisms.
Solution Approach 2:
The patent implements feedback mechanisms that monitor deployment status and automatically trigger rollback actions when validation fails. This automated feedback loop maintains system integrity by ensuring the system returns to a known good state, while the automation reduces the operational complexity of managing rollbacks.
Data Source
AI summary
In deploying a system in a computing environment, before deployment, a deployment engine performs a pre-deployment validation of the system using pre-determined system requirements. When the pre-deployment validation of the system fails, the deployment of the system is terminated. When the pre-deployment validation of the system succeeds, the deployment engine performs the following for each artifact of the system. Before deployment of a given artifact of the system, a pre-deployment validation of the given artifact is performed using pre-determined artifact properties. When the pre-deployment validation of the given artifact fails, the deployment of the system is terminated. When the pre-deployment validation of the given artifact succeeds, the given artifact is deployed. After the deployment of the given artifact, a post-deployment validation of the given artifact is performed using deployment data for the given artifact.