Multi-Cloud Capacity Planning via Distributed Ledger
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Solution Overview
Problem
Managing capacity planning and data placement in multi-cloud computing environments is challenging due to complex data growth prediction, fluctuating pricing models, varying data movement costs, differing compliance rules, and tiered pricing models across multiple cloud providers, making it difficult to remain compliant while reducing costs.
Innovation Solution
A distributed ledger system is implemented across multiple cloud platforms to track pricing models and regulatory policies, enabling an environment-wide view for capacity planning and data placement optimization, using a capacity planning and compliance engine to manage transactions and make recommendations based on pricing and compliance data stored in the ledger.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored across multiple cloud platforms to ensure compliance and redundancy, then reliability and compliance adherence are improved, but device complexity and management difficulty increase
Solution Approach 1:
A distributed ledger system acts as an intermediary layer between multiple cloud platforms and the enterprise. The ledger records and tracks data placement, pricing models, and regulatory policies across all clouds, providing a unified view that simplifies management while maintaining compliance across the complex multi-cloud environment.
Solution Approach 2:
The distributed ledger system serves multiple functions simultaneously: it tracks data placement locations, monitors compliance with regulatory policies, records pricing models for cost optimization, and provides an environment-wide view of the multi-cloud ecosystem. This multi-functionality reduces the need for separate management systems for each concern.
2Ease of operation
If traditional centralized capacity planning methods are used, then ease of operation is maintained, but adaptability to changing cloud environments and pricing models deteriorates
Solution Approach 1:
The system dynamically adapts to changing cloud environments by continuously monitoring and recording updates to pricing models, regulatory policies, and data placement configurations in the distributed ledger. The capacity planning and compliance engine processes these dynamic changes in real-time, adjusting recommendations without requiring complete reconfiguration of the management approach.
Solution Approach 2:
The distributed ledger provides continuous feedback about the state of data placement, pricing changes, and compliance status across the multi-cloud environment. The capacity planning and compliance engine uses this feedback to generate optimized recommendations, creating a closed-loop system that adapts to changing conditions while maintaining operational simplicity through automated decision support.
3Adaptability or versatility
If comprehensive tracking of pricing models and regulatory policies across all clouds is implemented, then adaptability and compliance monitoring are improved, but loss of information and data management complexity increase
Solution Approach 1:
The distributed ledger serves as a trusted intermediary that consolidates and standardizes information about pricing models, regulatory policies, and data placement across multiple clouds. By providing a unified, environment-wide view through the ledger, the system reduces data management complexity while maintaining comprehensive tracking and compliance monitoring capabilities.
Data Source
AI summary
In a multi-cloud computing environment comprising a plurality of cloud platforms across which an enterprise stores primary data and copies of the primary data, a method maintains a distributed ledger system with a plurality of nodes, wherein a given one of the plurality of cloud platforms is operatively coupled to a given one of the plurality of nodes of the distributed ledger system. Further, the method manages capacity planning and data placement for the primary data and the copies of the primary data in association with the distributed ledger system by storing transaction data in the distributed ledger system that represents at least one of one or more pricing models associated with each cloud platform and one or more regulatory policies associated with each cloud platform to enable an environment-wide view of at least one of the pricing models and the regulatory policies of the plurality of cloud platforms.