Elastic Cloud Storage Provisioning Automation
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Solution Overview
Problem
Existing cloud storage systems require skilled personnel for error-prone provisioning processes, with disjoint operations for adding resources to live services, leading to potential service interruptions and inefficiencies.
Innovation Solution
Elastic provisioning methods that allow for the seamless addition and decommissioning of compute, storage, and network resources within cloud storage systems, enabling minimal interruption and immediate availability of resources, with resources being managed as atomic operations within the system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If traditional provisioning methods are used, then resources can be added to services, but the process is error-prone and requires skilled personnel
Solution Approach 1:
The system enables self-service provisioning where the provisioning system automatically performs resource allocation, configuration, and service activation without requiring skilled personnel. The automated workflow handles the entire provisioning process from resource reservation to service activation, eliminating manual intervention and associated errors.
Solution Approach 2:
The system changes the state of resources through automated parameter modifications - transitioning resources from Provisioning Pool to Service Pool, updating configuration parameters, and modifying service state from inactive to active. These automated parameter changes replace manual provisioning operations.
2Adaptability or versatility
If resources are added to live services using traditional methods, then service capacity increases, but service interruption occurs
Solution Approach 1:
The system performs preliminary actions by provisioning resources in advance and placing them in a Provisioning Pool before they are needed. When resources are required, they are pre-configured and ready for immediate activation, allowing capacity expansion without interrupting live services.
Solution Approach 2:
The system introduces an intermediary Provisioning Pool that acts as a buffer between resource allocation and service activation. Resources first enter the Provisioning Pool where they are configured and validated, then transition to the Service Pool only when ready, preventing service disruption during the provisioning process.
3Productivity
If provisioning operations are performed sequentially, then resource allocation is straightforward, but provisioning time increases
Solution Approach 1:
The system merges multiple provisioning operations into a single atomic transaction. Resource allocation, configuration, validation, and activation are combined into one unified provisioning operation that executes simultaneously, eliminating sequential processing delays and reducing total provisioning time.
Solution Approach 2:
The system maintains continuous useful action through parallel processing of provisioning tasks. Multiple provisioning operations can execute simultaneously in parallel, and the system continuously monitors and validates resource states without idle waiting periods, maximizing productivity and minimizing time loss.
4Productivity
If multiple provisioning changes are made simultaneously, then service updates are efficient, but system complexity increases
Solution Approach 1:
The system segments the provisioning system into distinct functional modules: Provisioning Pool manager, Service Pool manager, Resource allocator, and Activator. Each module handles specific aspects of provisioning, making the complex batch operations manageable through modular architecture while maintaining high efficiency.
Data Source
AI summary
Methods and apparatus for a cloud storage system to add a first one of a compute, network, and/or storage layer resource to the service, provision the added first one of the compute, network, and/or storage layer resources, and activate the provisioned first one of the compute, network, and/or storage layer resources into the already provisioned service with minimal interruption of the service to elastically add a resource to the service.