Automated Container LCM Testing via API Mediation
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Solution Overview
Problem
Current Life Cycle Management (LCM) testing for containerized applications is inefficient and time-consuming due to reliance on graphical user interfaces (GUIs) and command line interfaces (CLIs, leading to application release delays and potential deployment of unreliable applications.
Innovation Solution
An automated LCM testing system that executes test scripts via API calls to assess the health of containerized applications, including liveliness, readiness, affinity, and high availability, using tools like REST API and Jenkins, to streamline testing and reduce dependency on GUIs and CLIs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated testing systems are implemented, then productivity and reliability are improved, but device complexity increases
Solution Approach 1:
The patent introduces an intermediary automated testing system that acts as a mediator between the containerized application and the testing process. This system receives API calls, executes testing sequences automatically, and returns results without requiring direct human interaction with GUIs or CLIs. The intermediary handles the complexity internally while presenting a simplified interface to users, thereby improving productivity without exposing the underlying system complexity.
Solution Approach 2:
The automated testing system is designed to perform testing operations autonomously without human intervention. It self-manages the entire testing workflow from receiving API calls to executing test sequences and generating results. This self-service capability eliminates the need for manual testing operations, significantly improving productivity while the system's internal automation handles the complexity that would otherwise require human expertise.
2Ease of operation
If manual testing via GUIs and CLIs is used, then ease of operation is maintained, but loss of time increases
Solution Approach 1:
The patent replaces the mechanical interaction required by GUIs and CLIs with automated API-based operations. Instead of requiring users to manually navigate interfaces or type commands, the system accepts structured API calls that automatically trigger testing sequences. This substitution eliminates the time-consuming manual operations while maintaining operational simplicity through standardized API interfaces.
Solution Approach 2:
The automated testing system performs preliminary actions by pre-configuring testing sequences and preparing test environments before actual testing begins. When API calls are received, the system has already prepared the necessary test configurations and can execute tests immediately without requiring users to set up each test manually. This preliminary preparation significantly reduces testing duration while keeping operations simple.
3Reliability
If comprehensive LCM testing is performed, then reliability is improved, but loss of time increases
Solution Approach 1:
The automated testing system enables continuous health assessment of containerized applications through uninterrupted API-based testing. Instead of periodic manual checks, the system continuously monitors application health, liveliness, readiness, and scalability parameters. This continuous automated monitoring maintains high reliability by detecting issues immediately while reducing the overall time investment compared to intermittent manual testing.
Solution Approach 2:
The system changes the parameters of testing by transitioning from manual, discrete test execution to automated, continuous parameter monitoring. It dynamically adjusts testing based on API inputs and application state, monitoring multiple parameters simultaneously (health, liveliness, readiness, scalability). This parameter-based automated approach comprehensively assesses reliability while completing tests faster than manual methods by parallelizing monitoring across multiple parameters.
Data Source
AI summary
Lifecycle Management Testing of a containerized application is conducted by executing a test script by a first containerized application thereby causing an Application Programming Interface (API) call to be issued to at least one automated testing system, running, by the at least one automated testing system, a testing sequence on a second containerized application, different from the first containerized application, based on the API call, and automatically displaying testing sequence results, where the results include an assessment of the health of the second containerized application.