Entitlement Engine Aggregates Cloud Subscription Offsets
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Solution Overview
Problem
Current cloud-based systems lack a centralized mechanism to track and reconcile resource consumption across multiple independent host clouds, making it difficult to enforce subscription limits, detect over- or under-consumption, and accurately apply billing adjustments.
Innovation Solution
Implementing a cloud management system with a centralized entitlement engine that aggregates and reconciles marginal subscription offsets by tracking short-term resource consumption across multiple host clouds, generating billing records that account for under- and over-consumption events, and adjusting subscription costs accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If individual host clouds operate independently without centralized coordination, then each cloud can manage its own resources autonomously, but resource consumption tracking and subscription limit enforcement become inaccurate across multiple clouds
Solution Approach 1:
A centralized entitlement engine is introduced as an intermediary component that receives consumption data from multiple independent host clouds, aggregates the data, and enforces subscription limits. This mediator enables accurate cross-cloud resource tracking without requiring the host clouds themselves to become complex coordinated systems.
2Reliability
If centralized subscription limit enforcement is implemented across multiple host clouds, then accurate billing and over-consumption detection are achieved, but system complexity and data aggregation requirements increase
Solution Approach 1:
The centralized entitlement engine implements feedback mechanisms by continuously monitoring resource consumption data from multiple host clouds, comparing it against subscription limits, and generating enforcement actions. This feedback loop ensures reliable subscription limit enforcement while keeping the engine's operational complexity manageable through automated decision-making.
3Speed
If real-time resource consumption monitoring is implemented across multiple host clouds, then timely detection of over-consumption is achieved, but data collection and processing overhead increase
Solution Approach 1:
The system monitors resource consumption at appropriate intervals rather than continuously, collecting just enough data to detect over-consumption events timely. This partial monitoring approach achieves fast over-consumption detection while minimizing the energy overhead of data collection and processing.
4Productivity
If marginal subscription offsets are aggregated across multiple host clouds, then under-consumption credits are captured and applied, but reconciliation complexity increases
Solution Approach 1:
The centralized entitlement engine merges offset reconciliation operations with the primary resource consumption monitoring function. By combining these operations into a single unified process, the system captures and applies under-consumption credits across multiple host clouds while minimizing additional complexity through integrated processing.
Data Source
AI summary
Embodiments relate to systems and methods for aggregating marginal subscription offsets in a set of multiple host clouds. A set of aggregate usage history data can record consumption of processor, memory, operating system, or other resources subscribed to by a user across multiple host clouds. An entitlement engine can analyze the aggregate usage history data to identify a short-term subscription margin for one or more subscribed resources, such as processor throughput, operating system instances, or other resources reflecting the under or over-consumption of a cloud resource against subscription limits on an hourly or other basis across multiple clouds. The entitlement engine can track the short-term subscription margin for one or multiple resources each hour of a day, and/or over other intervals, and determine the positive or negative subscription offset cost for each interval. The offsets can be combined to generate a net or aggregate subscription offset cost, or to provide other subscription adjustments.