Cloud Architecture Profile Selection via Workload Simulation
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Solution Overview
Problem
Current cloud migration strategies often result in sub-optimal infrastructure architecture in the cloud, failing to efficiently handle current and future workloads, leading to potential overload, latency, errors, and resource failures due to inadequate resource utilization and scaling.
Innovation Solution
The use of workload modeling and simulation techniques to select cloud architecture profiles based on actual application workloads and resource utilization correlations, allowing for efficient handling of current and future workloads, and enabling vertical and horizontal scaling to prevent overload and optimize resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If cloud architecture profiles are selected without workload modeling and simulation, then migration to cloud platforms can be performed quickly, but the infrastructure architecture becomes sub-optimal and fails to efficiently handle current and future workloads
Solution Approach 1:
The patent applies preliminary action by performing workload modeling and simulation before cloud migration to generate optimized cloud architecture profiles. The system models application workloads and resource utilization correlations in advance, simulates different cloud architecture configurations, and selects optimal profiles before actual migration occurs. This ensures the cloud infrastructure is pre-configured to efficiently handle both current and future workloads, avoiding sub-optimal architecture selection.
2Ease of manufacture
If cloud architecture profiles are selected without workload modeling, then implementation is simpler and faster, but the system becomes prone to overload, latency, errors, and resource failures
Solution Approach 1:
The patent applies self-service by enabling the system to automatically model workloads, simulate cloud architecture profiles, and select optimal configurations without manual intervention. The workload modeling component automatically correlates application workloads with resource utilization data, the simulation component autonomously evaluates different cloud architecture scenarios, and the system self-determines the optimal cloud architecture profile. This automated approach maintains simplicity while ensuring reliable, overload-resistant architecture selection.
3Device complexity
If traditional cloud migration approaches are used, then migration can be performed with minimal analysis, but resource utilization is inadequate and scaling is insufficient to meet future demands
Solution Approach 1:
The patent applies preliminary action by performing comprehensive workload modeling and cloud architecture simulation before migration. The system analyzes application workloads and resource utilization correlations in advance, simulates multiple cloud architecture profiles with different scaling configurations, and selects optimal profiles that accommodate both current and future workload demands. This preliminary analysis ensures adequate resource utilization and scaling capability without requiring complex post-migration adjustments.
Data Source
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AI summary
This document describes modeling and simulation techniques to select a cloud architecture profile based on correlations between application workloads and resource utilization. In some aspects, a method includes obtaining infrastructure data specifying utilization of computing resources of an existing computing system. Application workload data specifying tasks performed by one or more applications running on the existing computing system is obtained. One or more models are generated based on the infrastructure data and the application workload data. The model(s) define an impact on utilization of each computing resource in response to changes in workloads of the application(s). A workload is simulated, using the model(s), on a candidate cloud architecture profile that specifies a set of computing resources. A simulated utilization of each computing resource of the candidate cloud architecture profile is determined based on the simulation. An updated cloud architecture profile is generated based on the simulated utilization.