Microservice Centrality Prioritization for Data Center Testing
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Solution Overview
Problem
Data centers face challenges in efficiently managing and monitoring microservices due to limited compute resources, especially during peak activity periods, and determining prioritization among different workloads with varying criticality.
Innovation Solution
A method and system for data center management and monitoring that involves identifying process flows and associated microservices, mapping these microservices, calculating centrality values, and prioritizing chaos testing based on these values to optimize resource allocation and ensure critical workloads are supported.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If chaos testing is performed on all microservices, then system reliability is improved, but compute resources are exhausted during peak activity periods
Solution Approach 1:
The patent segments the microservice testing workload by calculating centrality values for each microservice and dividing them into priority groups. High-centrality microservices are tested first when resources are available, while low-centrality ones are deferred or skipped during peak periods. This segmentation allows the system to maintain reliability for critical services while conserving compute resources overall.
Solution Approach 2:
The patent changes the parameter of testing priority by dynamically calculating centrality values based on process flow mappings. This parameter change enables the system to adaptively adjust which microservices receive testing resources at any given time, optimizing the balance between reliability improvement and resource consumption according to current system state and workload conditions.
2Productivity
If centrality calculation and prioritization is implemented, then resource allocation efficiency is improved, but system complexity increases
Solution Approach 1:
The patent performs preliminary actions by pre-calculating and storing the centrality values of microservices based on their mappings to process flows. This preliminary calculation allows the system to quickly make resource allocation decisions during runtime without performing complex calculations in real-time, thereby improving resource allocation efficiency while managing system complexity through upfront preparation.
Solution Approach 2:
The patent introduces centrality values as an intermediary metric that mediates between the complex many-to-many mappings of microservices to process flows and the simple need for priority-based resource allocation. This intermediary abstraction simplifies the decision-making process by providing a single scalar value that represents the importance of each microservice, making the system more manageable despite the underlying complexity.
Data Source
AI summary
A system, method, and computer-readable medium for performing a data center management and monitoring operation. The data center management and monitoring operation includes: identifying a plurality of process flows; identifying a plurality of microservices associated with each of the plurality of process flows; mapping each of the plurality of microservices associated with each of the plurality of process flows; calculating a centrality value for each of the plurality of microservices associated with each of the plurality of process flows based upon the mapping; and, testing at least some of the plurality of microservices based upon the centrality value for each of the plurality of microservices.