Provision Chain Fault Isolation in Cloud Systems
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Solution Overview
Problem
Current cloud architectures face difficulties in isolating the root cause of provision failures due to uncertain relationships between operations in parallel provision requests, making it challenging to identify the exact source of failures.
Innovation Solution
A method is introduced to generate provision chains by collecting information from provisioners during request fulfillment, using correlation rules to analyze events, and aggregating them into chains to identify isolation points of failures, thereby informing clients of the specific cause of the failure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple sub provisioners operate in parallel to fulfill provision requests, then productivity is improved, but difficulty of detecting and measuring worsens due to uncertain relationships between operations
Solution Approach 1:
The patent introduces a correlation engine as an intermediary component that receives events from multiple sub provisioners and correlates them using correlation rules. This mediator transforms the complex parallel operations into a structured provision chain, enabling systematic failure analysis without reducing the parallel processing capability of the sub provisioners.
Solution Approach 2:
The system implements feedback by collecting events from sub provisioners, correlating them to identify isolation points, and providing this diagnostic information back to clients. This feedback loop enables clients to quickly identify and correct specific issues in the provision process, improving both detection capability and overall system efficiency.
2Measurement precision
If correlation rules are applied to aggregate events into provision chains, then measurement precision is improved for failure isolation, but device complexity increases due to additional processing components
Solution Approach 1:
The patent segments the failure analysis process into distinct components: event collection from sub provisioners, correlation rule processing, provision chain generation, and isolation point identification. This segmentation allows each component to be optimized independently while maintaining overall system precision in failure isolation.
Solution Approach 2:
The system performs preliminary actions by pre-defining correlation rules that capture common provision operation relationships. These rules are prepared in advance and applied automatically when events are received, reducing the complexity of real-time analysis while maintaining high measurement precision for failure isolation.
Data Source
AI summary
An approach is provided in which a set of provision information is generated from a set of provisioners that are in process of fulfilling a client's provision request. The approach creates a set of provision events based on the set of provision information and, in response to detecting a failure of the provision request, the approach generates a provision chain from the set of provision events. The provision chain links the set of provision events based on correlation rules and identifies at least one isolation point of the failure. The approach informs the client of the at least one isolation point of the failure identified in the provision chain.