Hybrid Cloud Storage API Dependency Mapping for Fault Recovery
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Solution Overview
Problem
In a hybrid cloud environment where multiple storage sets are managed using both low-level and high-level APIs, identifying the cause of storage read errors and conducting fault recovery is difficult due to unclear interdependence between APIs and jobs, making it challenging for the high-level API to effectively manage and recover from faults.
Innovation Solution
A storage management system that includes a configuration with a storage management interface interdependence data generation unit, job interdependence data generation unit, and fault identification unit to generate and utilize interdependence data, enabling clear identification of faulty jobs and facilitating recovery by generating interdependence meta data and using an interdependence data structure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple APIs (low-level and high-level) are used to manage storage sets at multiple sites, then integral control and management capability is improved, but fault identification and recovery capability deteriorates due to unclear interdependence between APIs
Solution Approach 1:
The system performs preliminary actions by generating interdependence data structures and job interdependence metadata before faults occur. This pre-establishment of dependency relationships enables the fault identification unit to quickly trace and identify faulty jobs when errors happen, resolving the contradiction between comprehensive API management and fault detection difficulty
Solution Approach 2:
The patent introduces an intermediary mechanism (interdependence data structure and metadata generation units) that mediates between multiple APIs and the fault identification process. This intermediary layer captures and structures the relationships between APIs and jobs, making fault identification feasible without simplifying the multi-API management architecture
2Difficulty of detecting and measuring
If interdependence data and metadata are generated and maintained to enable fault identification, then fault identification capability is improved, but system complexity increases
Solution Approach 1:
The interdependence data structure and metadata generation units serve multiple functions: they track API dependencies, record job execution relationships, and enable fault identification. This multi-functionality reduces the need for separate specialized components, managing system complexity while improving fault identification capability
Data Source
AI summary
In a hybrid cloud environment, a faulty job is identified and fault recovery is conducted under integrated control of storage set up at multiple sites. A system manages storage set up at multiple sites, using a low-level API for each set of storage, and has a high-level API integrally controlling the low-level APIs. The system includes an API interdependence data generation unit generating interdependence data describing API interdependence-related information upon calling of a low-level API, depending on low-level API use status, a job interdependence data generation unit that generates interdependence meta data upon successful job execution by the high-level API, and a fault identification unit that identifies a fault of the low-level API upon failure of the high-level API to execute a job, by using an interdependence data structure generated by the API interdependence data generation unit and the interdependence meta data generated by the job interdependence data generation unit.