Automated Cloud Stack Validation via Self-Service Job Execution
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Solution Overview
Problem
Manual validation of stacks submitted by Digital Content Distribution Forum (DCDF) partners is complex and resource-intensive due to potential dependencies on external infrastructure, leading to minimal testing and significant time and resource requirements.
Innovation Solution
An automated validation method for application stacks in a cloud computing environment, which includes receiving stack identification, retrieving job information, determining validation status, and designating the stack as valid or invalid, with the ability to test stacks by performing jobs like PLAN, APPLY, and DESTROY, and scanning for viruses before publication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual validation of stacks is performed, then validation thoroughness can be maintained, but time consumption and resource requirements increase significantly
Solution Approach 1:
The validation system performs self-validation by automatically executing jobs within the customer tenancy to test stack functionality. The stack validates itself through automated job execution and result analysis, eliminating the need for external manual validation while maintaining thoroughness.
Solution Approach 2:
Manual validation operations are replaced with automated computational processes. The system uses automated job execution, result retrieval, and analysis algorithms to substitute human operators, thereby reducing time consumption while maintaining validation quality.
2Reliability
If comprehensive stack testing is performed, then validation reliability improves, but resource consumption increases
Solution Approach 1:
The validation process leverages the customer tenancy's own computational resources to execute validation jobs. By using the tenancy's existing infrastructure for self-validation, the system avoids additional external resource consumption while maintaining comprehensive testing capability.
Solution Approach 2:
The validation system is designed to work within the existing customer tenancy environment, utilizing multi-purpose infrastructure that serves both customer workloads and validation testing. This universal resource usage eliminates the need for dedicated validation resources, reducing overall resource consumption.
3Productivity
If automated validation is implemented, then validation efficiency improves, but system complexity increases
Solution Approach 1:
The automated validation system operates autonomously within the customer tenancy, requiring minimal external configuration or management. The self-service nature reduces the operational complexity burden on users while maintaining high validation efficiency through automated job execution and analysis.
4Reliability
If stack validation is performed in isolated tenancy, then tenancy security is maintained, but validation capability is limited
Solution Approach 1:
The customer tenancy acts as an intermediary environment that enables validation capability while maintaining security isolation. The tenancy's internal infrastructure serves as a mediator that allows comprehensive stack testing without compromising the security boundaries between different cloud environments.
Data Source
AI summary
Systems and methods for automated validation of application stacks are described herein. A method for automated validation of application stacks can include receiving identification of a stack for validation at a publication service system from a customer tenancy in a cloud computing environment. The stack can include an associated stack identifier. The method can include retrieving with the publication service system job information from the customer tenancy relevant to the stack and determining validation status of the stack based on the retrieved job information. The method can include designating the stack as a valid stack when it is determined that the stack is valid.