Distributed Testing Environment Pods for Power-Outage Continuity
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Solution Overview
Problem
Testing centers face interruptions due to power shutdowns or other disruptions, leading to discontinuation of testing operations and inability to update testing protocols.
Innovation Solution
A system and method for performing distributed and collected testing operations on-demand, utilizing cloud and network resources, dynamically assigning testing tasks to available pods based on preconfigured roles, and reallocating tasks to ensure continuous operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If testing operations are performed at specific testing centers, then testing can be conducted with dedicated resources, but the testing operations cannot continue if the testing centers are unavailable due to power shutdowns or interruptions
Solution Approach 1:
The patent divides testing operations into distributed pods that can operate independently across multiple locations. Each pod is a segmented unit that can be assigned to different testing centers or cloud resources, allowing the system to continue operating even when one specific center is unavailable due to power shutdowns or interruptions.
Solution Approach 2:
The patent introduces a cloud-based intermediary layer that mediates between testing operations and physical testing centers. This intermediary enables dynamic assignment of pods to available resources, allowing testing operations to be redirected to alternative locations when a specific center becomes unavailable, thus maintaining continuity despite harmful factors like power outages.
2Power
If testing centers maintain dedicated resources for testing operations, then testing can be performed with sufficient computational power, but processor and memory usage increases when multiple operations are assigned to the same center
Solution Approach 1:
The patent segments testing operations into separate pods that can be distributed across multiple testing centers. This segmentation allows the system to balance the workload dynamically, assigning pods to centers based on available resources, thereby maintaining sufficient computational power for each operation while improving overall resource utilization efficiency.
Solution Approach 2:
The patent implements dynamic resource allocation where pods can be reassigned to different testing centers based on real-time availability and resource usage. This dynamic approach ensures that computational power is allocated efficiently, preventing overload at any single center while maintaining the ability to handle multiple operations simultaneously.
3Adaptability or versatility
If testing operations are assigned to specific pods with preconfigured roles, then testing can be performed with specialized resources, but the system becomes more complex with multiple pods and resource assignments
Solution Approach 1:
The patent applies preliminary action by preconfiguring pods with specific roles and resource requirements before they are assigned to testing operations. This preconfiguration includes defining the specialized resources needed for different testing types, allowing the system to maintain adaptability and versatility while simplifying the assignment process through standardized templates rather than complex custom configurations.
Solution Approach 2:
The patent creates universal pod templates that can serve multiple functions through configuration rather than requiring separate specialized infrastructure for each testing type. These multi-functional templates reduce the number of distinct pod types needed, thereby reducing management complexity while maintaining the ability to perform specialized testing operations through configurable parameters.
Data Source
AI summary
An apparatus comprises a memory communicatively coupled to a processor. The memory is configured to store multiple deployment operations configured to control access to one or more portions of application data. The processor is configured to determine a deployment operation associated with a portion of the application data, perform multiple collected testing operations for the portion of the application data based at least in part upon the deployment operation, and determine pod data indicating multiple role parameters based at least in part upon the deployment operation. The role parameters are configured to indicate multiple testing operations on the portion of the application data. Further, the processor is configured to identify a pod that at least partially matches the pod data and trigger one or more distributed testing operations at the pod.


