Role-Based Cloud Data Management with Elastic Scaling
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Solution Overview
Problem
Current systems face challenges in efficiently managing and scaling data volumes in a multi-tenant cloud environment, particularly in ensuring role-based access and elastic scaling to meet varying data processing needs of businesses of different sizes, while maintaining cost-effectiveness and operational efficiency.
Innovation Solution
A cloud-based system that enables role-based operations by allowing users to interact with projects through a frontend interface, dynamically scaling index storage and resources based on demand, with features like data volume limits, overflow indexing, and user-controlled resource allocation using sliders or other UI controls, ensuring secure access and optimized resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If cloud-based systems provide software as a service to handle large volumes of data for large corporations, then data processing capability is improved, but development and maintenance expense increases substantially
Solution Approach 1:
The patent segments the cloud system into multiple independent components: frontend interfaces for user interaction, backend processing services for data operations, indexing services for efficient data retrieval, and storage services for data persistence. Each component can be independently scaled and maintained, reducing overall system complexity while handling large data volumes.
Solution Approach 2:
The patent implements universal service components that can handle multiple types of data processing operations (searching, indexing, storage, retrieval) through a common architecture. This multi-functional approach allows a single system to serve diverse business needs without requiring separate specialized software for each function.
2Adaptability or versatility
If the system dynamically scales resources based on demand, then adaptability to varying data needs is improved, but system complexity increases
Solution Approach 1:
The patent implements dynamic resource allocation where computing resources, storage capacity, and indexing power automatically adjust based on real-time demand metrics. The system monitors data volume, query patterns, and resource utilization to dynamically provision or de-provision services, enabling flexible adaptation without manual intervention.
Solution Approach 2:
The system incorporates self-service mechanisms where the cloud platform automatically detects resource requirements and performs scaling operations without user involvement. Load balancers automatically distribute traffic, and resource allocators dynamically provision services based on monitored performance metrics, reducing the complexity burden on users.
3Reliability
If the system implements role-based access control for secure data operations, then security is improved, but operational complexity increases
Solution Approach 1:
The patent introduces role-based access control as an intermediary layer between users and data resources. Instead of managing individual user permissions directly, the system uses role definitions that aggregate permissions and responsibilities. Users are assigned to roles rather than configuring individual access rules, which simplifies operations while maintaining strong security through the role mediation layer.
Data Source
AI summary
Embodiments are directed towards a system and method for a cloud-based front end that may abstract and enable access to the underlying cloud-hosted elements and objects that may be part of a multi-tenant application, such as a search application. Search objects may be employed to access indexed objects. An amount of indexed data accessible to a user may be based on an index storage limit selected by the user, such that data that exceeds the index storage limit may continue to be indexed. Also, one or more projects can be elastically scaled for a user to provide resources that may meet the specific needs of each project.