SaaS Data Backup Framework for Hierarchical Cascading Restore
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Solution Overview
Problem
Existing backup and recovery systems for software-as-a-service (SaaS) data face challenges due to the hierarchical nature of SaaS applications like JIRA, where accessing data involves multiple APIs and complex relationships between computing objects, complicating the provision of efficient backup and recovery services.
Innovation Solution
A data management system (DMS) implements discovery, backup, and restore frameworks that maintain hierarchical relationships between computing objects and tables, organizing them as logical entities and performing granular cascading restores based on API usage, while supporting multiple relational SaaS applications through generic frameworks and APIs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing backup and recovery systems are used for SaaS data, then basic backup functionality is provided, but the hierarchical nature of SaaS applications and complex API relationships cause inefficiency and complexity in the backup and recovery process
Solution Approach 1:
The backup and recovery system segments SaaS data into discrete computing objects (COs) that can be independently identified, backed up, and restored. Each CO represents a distinct unit of data within the hierarchical SaaS application structure, allowing granular control over backup operations and simplifying the management of complex data relationships.
Solution Approach 2:
The system introduces an intermediary backup management layer that sits between the SaaS application's complex API hierarchy and the backup storage. This intermediary layer abstracts the hierarchical relationships and API complexities, translating them into standardized backup operations that can be efficiently managed without directly exposing the underlying complexity.
2Reliability
If granular cascading restores are implemented to maintain data integrity, then data reliability is improved, but the complexity of managing hierarchical relationships and API calls increases
Solution Approach 1:
The system performs preliminary actions by pre-identifying and pre-ordering computing objects based on their hierarchical relationships before the actual restore operation begins. The backup management layer pre-processes the restore request to determine the correct sequence of CO restorations, ensuring data integrity without requiring complex real-time decision-making during the restore process.
Solution Approach 2:
The system implements feedback mechanisms where the backup management layer continuously monitors the restore progress and adjusts subsequent operations based on the state of restored computing objects. This feedback loop ensures that dependent COs are restored in the correct sequence, maintaining data integrity while automating the complexity of hierarchical relationship management.
3Adaptability or versatility
If multiple relational SaaS applications are supported through generic frameworks, then system versatility is improved, but the complexity of implementing and maintaining multiple API integrations increases
Solution Approach 1:
The backup and recovery system implements a universal backup management layer that can interface with multiple different SaaS applications through a common framework. This universal layer provides consistent backup and restore functionality across diverse applications, eliminating the need for separate specialized systems for each SaaS platform and reducing overall integration complexity.
Solution Approach 2:
The system uses parameter changes to adapt to different SaaS applications by configuring the backup management layer with application-specific parameters rather than restructuring the entire system. This allows the same generic framework to support multiple relational SaaS applications by simply changing configuration parameters, thereby maintaining versatility while minimizing integration complexity.
Data Source
AI summary
Methods, systems, and devices for data management are described. Software-as-a-service (SaaS) applications may host customers information in a distributed environment that is not directly accessible to the customers. In some SaaS applications each organization may have a settings computing object, a features computing object, and a set of projects computing objects. The hierarchical relationships in each of the projects computing objects may depend on the tables in the settings and features computing objects. A data management system (DMS) may include discovery, backup, refresh, and restore frameworks that maintain hierarchical relationships between computing objects and tables including the dependency of projects computing objects on settings or features computing objects.