Workload Routing Proximity Zones
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Solution Overview
Problem
Existing workload routing solutions in IT infrastructure primarily focus on compatibility and capacity checks, neglecting the relative placements of workloads within the infrastructure, specifically overlooking proximity requirements such as affinity and anti-affinity constraints that are crucial for maintaining performance and resiliency.
Innovation Solution
A method for routing workloads in IT infrastructure that considers proximity requirements by determining proximity groups and zones, applying proximity-based rules to ensure workloads are appropriately placed to maximize routing efficiency while adhering to compatibility and capacity constraints, using proximity zones to define boundaries for keeping workloads together or apart based on performance and resiliency needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing workload routing solutions focus only on compatibility and capacity checks, then the routing process is simple and fast, but the relative placements of workloads are overlooked, leading to suboptimal performance and resiliency
Solution Approach 1:
The routing process is segmented into multiple evaluation stages: compatibility checking, capacity assessment, and proximity evaluation. Each stage filters and ranks infrastructure options, with the proximity analysis providing the final optimization layer that considers affinity and anti-affinity requirements among workloads.
Solution Approach 2:
The system performs preliminary proximity analysis by pre-calculating affinity and anti-affinity relationships between workloads before final routing decisions. This advance preparation allows the routing algorithm to make informed decisions about relative workload placements without significantly increasing overall processing time.
2Reliability
If proximity requirements are considered in workload routing, then performance and resiliency are enhanced, but the complexity of the routing process increases
Solution Approach 1:
The system applies different levels of analysis to different aspects of workload routing: basic compatibility and capacity checks are performed uniformly across all workloads, while proximity requirements are evaluated locally based on specific affinity and anti-affinity relationships. This selective approach focuses computational resources where they are most needed.
Solution Approach 2:
The system implements proximity analysis as an optional enhancement rather than a mandatory requirement for all routing decisions. Basic routing functionality remains simple and fast, while proximity-based optimization is applied selectively to workloads that have specific affinity or anti-affinity requirements, avoiding unnecessary complexity for cases where it is not needed.
3Manufacturing precision
If proximity zones are defined to enforce affinity and anti-affinity rules, then workload placement accuracy is improved, but the infrastructure modeling complexity increases
Solution Approach 1:
The proximity zone concept serves multiple functions simultaneously: it defines physical or logical boundaries in the infrastructure, groups workloads with affinity requirements, identifies separation zones for anti-affinity requirements, and provides a framework for evaluating multiple routing constraints. This multi-functionality reduces the need for separate modeling mechanisms for each type of constraint.
Data Source
AI summary
A system and method are provided for routing workloads in an information technology infrastructure using models of same. The method includes determining at least one proximity group of workloads; determining at least one proximity zone in the infrastructure for routing each proximity group; and determining a workload routing solution subject to one or more constraints defined by one or more proximity based rules.