Multi-Cloud Storage Tier Translation for Enterprise Cost Visibility
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Solution Overview
Problem
In multi-cloud storage environments, enterprises face challenges in managing and monitoring storage tiers across different cloud providers due to varying definitions and costs, leading to manual and error-prone processes for aligning vendor tiering with their own organizational definitions.
Innovation Solution
A translation layer maps vendor storage tiers to enterprise-defined tiers, populating datasets with metadata to present data in the enterprise's own terminology, providing visibility into costs and performance metrics, and automating the alignment process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If enterprises use multiple cloud providers with different storage tier definitions, then storage flexibility and vendor independence are improved, but management complexity and monitoring difficulty increase
Solution Approach 1:
The patent introduces a translation layer as an intermediary component that sits between the enterprise's storage management system and multiple cloud providers. This translation layer converts vendor-specific storage tier definitions into enterprise-defined tier definitions, allowing the enterprise to manage diverse cloud storage resources through a unified interface without being constrained by any single vendor's tier structure, thereby maintaining storage flexibility while reducing management complexity
2Measurement precision
If enterprises manually align vendor tiering with organizational definitions, then accuracy in tier mapping is improved, but time consumption and error rates increase
Solution Approach 1:
The patent implements preliminary action by pre-configuring translation rules and mappings between vendor storage tiers and enterprise-defined tiers. The system proactively establishes these mappings in advance, so when storage operations need to be performed, the tier translation is already prepared and can be executed automatically without manual intervention, thereby maintaining high accuracy while significantly reducing time consumption
Solution Approach 2:
The translation layer operates autonomously to perform tier mapping translations without requiring manual alignment efforts. The system self-manages the conversion between vendor-specific tier definitions and enterprise-defined tiers through automated rule-based translation, eliminating human errors and freeing up time while maintaining consistent and accurate tier mappings
Data Source
AI summary
The technology described herein is directed towards mapping the storage tiers of various multi-cloud vendors to an enterprise's storage tiers and the enterprise's associated storage tier datasets, based on enterprise storage tiering definition data. Once mapped, the storage tier datasets are populated based on the vendor's per-tier metadata that are associated with the enterprise's data stored on that vendor's storage tiers. Similar mapping is performed for each other vendor's storage tiers. Once the storage tier datasets are populated based on the corresponding metadata, the metadata's variable parameters (e.g., performance metrics) for the enterprise's stored data can be presented according to the enterprise's own defined tiers and labels for the parameters. The metadata information in the datasets can be viewed per vendor and per enterprise-defined tier dataset, such as for object storage monitoring, cost comparison among different vendors' tiers, and closest vendor-to-enterprise parity comparisons of like variables.