Automated Cluster Consolidation via Simulated Merge Analysis
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Solution Overview
Problem
The difficulty in identifying which clusters to consolidate and the complexity of the consolidation process in distributed computer systems prevent customers from merging small clusters, despite increased supported cluster sizes, due to the need for deep knowledge of workload demand patterns and resource settings.
Innovation Solution
A system and method for automatically consolidating clusters by generating a digital representation of a simulated merged cluster, applying resource management operations, and executing an automatic consolidation operation to create a merged cluster, utilizing a management server with a cluster consolidation manager that predicts and executes consolidation processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual cluster consolidation is performed, then resource management efficiency can be optimized, but the process complexity and difficulty of identifying consolidation targets increase significantly
Solution Approach 1:
The system enables automated self-service cluster consolidation by having the management server automatically identify consolidation candidates, simulate merge outcomes, and execute consolidation operations without requiring deep expert knowledge from users. The system serves itself by making intelligent decisions about which clusters to consolidate and how to perform the consolidation.
Solution Approach 2:
The system performs preliminary actions by simulating cluster consolidations before actual execution. The management server generates simulated merged clusters and evaluates resource management outcomes in advance, allowing users to visualize and approve consolidation plans before they are implemented, thereby reducing the complexity of the actual consolidation process.
2Measurement precision
If deep knowledge of workload demand patterns and resource settings is required, then consolidation accuracy improves, but ease of operation deteriorates
Solution Approach 1:
The management server acts as an intermediary between users and the complex consolidation process. It automatically analyzes workload demand patterns and resource settings using its内置 algorithms, presenting simplified consolidation options to users without requiring them to possess deep technical knowledge. The intermediary translates complex technical parameters into user-friendly consolidation recommendations.
Solution Approach 2:
The system creates digital representations (copies) of clusters and their workload patterns to analyze consolidation outcomes without affecting actual operations. By working with simulated copies of cluster data, the system can accurately evaluate consolidation scenarios and present results to users without requiring them to understand the underlying complex workload dynamics.
3Reliability
If sophisticated sequence of operations is required for consolidation, then consolidation reliability improves, but execution time increases
Solution Approach 1:
The management server performs preliminary validation and planning of the consolidation sequence before execution. It simulates the entire consolidation process in advance, identifying potential issues and optimizing the operation sequence. This preliminary action ensures reliable consolidation while reducing actual execution time by avoiding retries and corrections during the actual consolidation process.
Data Source
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AI summary
A system and method for automatically consolidating clusters of host computers in a distributed computer system uses a digital representation of a simulated merged cluster of host computers to produce resource management analysis results on the simulated merged cluster of host computers. The simulated merged cluster of host computers is a simulation of a consolidation of first and second clusters of host computers. In addition, the system and method involves executing an automatic consolidation operation on the first and second clusters of host computers to generate a merged cluster of host computers that includes the host computers from both the first and second clusters.