Cloud Workload Consolidation for Maintenance Migration Reduction
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Solution Overview
Problem
Cloud maintenance operations often require significant workload migrations, which are time-consuming and resource-intensive, leading to performance penalties for both infrastructure and workloads due to the need to transfer large amounts of data during updates.
Innovation Solution
A method that involves analyzing maintenance binaries to identify classes of hardware that will be disrupted, consolidating workloads onto fewer components, idling these components before maintenance, updating idle components first, and then migrating workloads across them, thereby reducing the number of migrations and speeding up the update process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If workload migrations are performed during cloud maintenance operations, then hardware and software components can be updated, but significant time and resources are consumed and performance penalties occur
Solution Approach 1:
The patent applies preliminary action by pre-updating a subset of hardware components before workloads are migrated to them. Specifically, the system identifies target hardware components, updates them in advance while they are idle or under minimal load, and then migrates workloads to these pre-updated components. This eliminates the need to perform updates during the migration process itself, thereby reducing total maintenance time and performance penalties.
Solution Approach 2:
The patent segments the hardware component population into multiple subsets, where each subset is updated separately and sequentially. Rather than migrating all workloads and updating all components simultaneously (which would cause massive performance degradation), the system divides components into groups, updates them in stages, and migrates workloads incrementally. This segmentation reduces the peak resource consumption and time required for maintenance operations.
2Reliability
If workload migrations are performed during cloud maintenance operations, then hardware components can be updated, but network throughput and target workload throughput are reduced
Solution Approach 1:
The system performs software updates on target hardware components before workloads are migrated to them. By completing the update process in advance while the component is idle or under minimal load, the system avoids the performance degradation that would occur if updates were performed concurrently with workload execution. This preliminary action ensures that network throughput and workload performance are not degraded during the maintenance operation.
3Reliability
If workload migrations are performed during cloud maintenance operations, then hardware components can be updated, but significant resources and planning are required
Solution Approach 1:
The system employs automated mechanisms for workload migration and hardware update coordination. Rather than requiring extensive manual planning and intervention, the system automatically identifies suitable target hardware components, schedules updates, executes migrations, and manages resource allocation. This self-service automation reduces the complexity of migration planning and execution while ensuring reliable maintenance operations.
Data Source
AI summary
A method, system and computer program product for minimizing workload migrations during cloud maintenance operations. Upon receiving an indication that a scheduled maintenance operation is to be performed, a cloud controller uploads the maintenance binaries associated with the scheduled maintenance operation and analyzes the maintenance binaries so as to evaluate the requirements of the maintenance packages and dependencies associated with the scheduled maintenance operation. A matrix is then generated by the cloud controller to identify the classes of hardware that will be disrupted by the scheduled maintenance operation based on the analysis. The workloads running on the classes of hardware identified in the matrix will then be consolidated prior to the scheduled maintenance operation. By consolidating the workloads onto a fewer number of hardware components, a fewer number of workload migrations will need to be performed during the cloud maintenance operation.