Compute Instance Resource Usage Management via Dynamic Limits
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Solution Overview
Problem
Customers face challenges in determining optimal compute instance performance requirements, leading to overprovisioning or underprovisioning of resources, resulting in unnecessary costs or performance bottlenecks due to unpredictable workload demands.
Innovation Solution
Implementing a usage management service that monitors actual resource usage of compute instances and adjusts performance limits based on customer-specified or workload-specific targets, allowing for dynamic allocation of resources to match changing demands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If customers provision compute instances with high performance to ensure adequate resource availability, then performance reliability is improved, but resource cost increases
Solution Approach 1:
The patent implements dynamic adjustment of compute instance performance limits based on monitored workload demands. The system continuously observes actual resource usage patterns and automatically modifies performance limits to match current needs, transitioning from static overprovisioning to dynamic adaptation. This resolves the contradiction by maintaining reliability when needed while reducing costs during lower demand periods.
Solution Approach 2:
The system establishes a feedback loop where compute instance performance limits are continuously monitored, evaluated against workload demands, and adjusted accordingly. The usage management service receives performance data, analyzes whether current limits are appropriate, and implements adjustments to optimize the balance between reliability and cost efficiency.
2Quantity of substance
If customers provision compute instances with low performance to reduce costs, then resource cost decreases, but performance reliability deteriorates
Solution Approach 1:
The system dynamically scales performance limits upward when workload demands increase, ensuring reliability is maintained during high-demand periods. Instead of static low-performance provisioning, the system adapts in real-time to prevent performance bottlenecks while minimizing costs during lower utilization periods.
Solution Approach 2:
The feedback mechanism detects when workload demands exceed current performance limits and triggers automatic adjustments to restore adequate performance levels. This ensures that cost-saving low-performance provisioning does not compromise reliability when actual workload requires higher capacity.
3Ease of operation
If fixed performance limits are applied to compute instances, then resource allocation simplicity is improved, but adaptability to changing workload demands deteriorates
Solution Approach 1:
The system implements self-service automation where the usage management service autonomously monitors workload patterns and adjusts performance limits without requiring manual intervention. This maintains the simplicity of fixed limits from the user perspective while enabling dynamic adaptability through automated decision-making and adjustment.
Solution Approach 2:
The automated feedback loop continuously evaluates workload demands against current performance limits and implements adjustments without user involvement. This preserves operational simplicity while achieving adaptability through system-driven monitoring and automatic reconfiguration of resource allocation.
Data Source
AI summary
Techniques for managing compute resource usage by virtualized compute instances within a provider network are described. A computer system connected to a provider network hosts one or more compute instances. An agent associated with the computer system obtains per-compute instance resource usage information of computer system resources such as processors, memory, and network interfaces. The agent sends the usage information to a usage management service of the provider network. The usage management service generates usage limits based on the usage information from the agent and on usage targets and sends the usage limits to the computer system. The computer system limits the resource usage of the compute instance based on the usage limits.