Workload Simulator for Production Cluster Resource Allocation
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Solution Overview
Problem
Existing systems for managing production clusters face challenges in efficiently allocating computing resources across nodes, leading to decreased overall performance due to the inability to account for the impact of tuning one job on other jobs executing within the cluster.
Innovation Solution
A system comprising a workload simulator and a cluster tuner that uses a scaled-down test cluster to simulate the workload of a production cluster, allowing for the determination of optimal resource allocation across nodes, thereby improving cluster performance and resource efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional tools are used to tune a single job by allocating memory and processing resources, then the performance of that single job is improved, but the overall cluster performance decreases due to inability to account for impacts on other jobs
Solution Approach 1:
The patent creates a simulated workload that replicates the production workload characteristics on a test cluster. This copying approach allows tuning of resource allocation configurations without affecting the actual production cluster, enabling evaluation of how changes impact overall cluster performance before deployment. The simulated workload includes multiple jobs with similar resource consumption patterns to the production environment, allowing comprehensive assessment of tuning decisions.
Solution Approach 2:
The system performs preliminary testing and evaluation of resource allocation configurations on the test cluster before applying them to the production cluster. By simulating the workload and testing configurations in advance, the system identifies optimal resource allocation settings that improve overall cluster performance without risking production stability. This preliminary action prevents detrimental configurations from being deployed to production.
2Productivity
If more nodes are added to the production cluster to handle increased workload, then the processing capacity is improved, but the complexity and cost of operating the cluster increases
Solution Approach 1:
The patent optimizes the allocation parameters of existing computing resources through simulated workload testing. By adjusting resource allocation configurations (such as memory and processing resource distribution) and evaluating their impact on overall cluster performance, the system maximizes the utilization efficiency of existing nodes. This approach improves processing capacity without requiring additional nodes, thereby avoiding increased cluster complexity and operational costs.
3Speed
If resource allocation is optimized for one job type, then the execution speed of that job type is improved, but other job types may experience resource contention and performance degradation
Solution Approach 1:
The simulated workload encompasses multiple job types with diverse resource consumption patterns, allowing the system to evaluate resource allocation configurations holistically. The configuration that optimizes performance across all job types in the simulation is selected for deployment, ensuring balanced performance and stability across the production cluster without severe resource contention for any single job type.
Data Source
AI summary
A system includes a production cluster with a first plurality of nodes. The production cluster executes a workload. Jobs associated with the workload are allocated, according to a first configuration, across the first plurality of nodes. A workload simulator is coupled to the production cluster and a test cluster. The workload simulator extracts production cluster data, which includes production capability information, workload data, and production cluster usage information, as well as test capability information. The workload simulator determines a first job type to include in a simulated workload to be executed on the test cluster and a number of jobs of the first job type to include in the simulated workload. The system also includes a test cluster which includes a second plurality of nodes. The second plurality of nodes includes fewer nodes than does the first plurality of nodes. The test cluster executes the simulated workload.