Auto-scaling Group Standby Instance Management
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Solution Overview
Problem
Existing network computing and storage systems face challenges in accommodating sudden traffic spikes or immediate resource needs, as virtual resources often fail to meet increased demands, leading to inefficiencies in resource allocation and management.
Innovation Solution
Implementing auto-scaling groups that allow customers to manage virtual computer instances by placing them into standby or detaching them, enabling dynamic resource adjustment and management through API calls, which allows for flexible resource allocation and maintenance without impacting active instances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If virtual resources are dynamically scaled to accommodate traffic spikes, then system adaptability and service quality are improved, but resource allocation efficiency and management complexity deteriorate due to unanticipated demands
Solution Approach 1:
The patent applies preliminary action by creating standby instances before traffic spikes occur. The auto-scaling group maintains a pool of pre-provisioned instances that can be rapidly activated when demand increases, eliminating the need to provision resources from scratch during critical moments. This resolves the contradiction by preparing resources in advance (improving adaptability) while keeping the standby instances in a controlled, pre-configured state (managing complexity).
Solution Approach 2:
The patent implements dynamics through the auto-scaling group's ability to dynamically adjust the number of active instances based on real-time demand. The system can scale out by activating standby instances or launching new instances, and scale in by terminating instances when demand decreases. This dynamic adjustment mechanism improves adaptability to traffic patterns while the automated control logic manages the complexity of resource orchestration.
2Loss of time
If instances are maintained in standby for rapid activation, then response time to traffic spikes is improved, but resource allocation efficiency deteriorates due to idle standby capacity
Solution Approach 1:
The patent applies partial action by maintaining only a controlled number of standby instances rather than pre-provisioning excessive capacity. The auto-scaling group manages the balance between having enough standby instances to respond quickly to demand while avoiding the waste of maintaining too many idle instances. This resolves the contradiction by having partial standby capacity (improving response time) while limiting the total number of standby instances to optimize resource efficiency.
3Reliability
If instances are rapidly activated during traffic spikes, then service quality is improved, but system stability deteriorates due to sudden resource changes
Solution Approach 1:
The patent applies beforehand cushioning by maintaining standby instances as a buffer between demand fluctuations and system responses. These standby instances absorb sudden traffic spikes, cushioning the impact on the active instance pool and preventing abrupt system state changes. This resolves the contradiction by using standby instances as a cushion (improving service quality during spikes) while the gradual activation process maintains system stability.
Solution Approach 2:
The patent implements feedback through the auto-scaling group's continuous monitoring of system metrics and demand patterns. The system uses this feedback to make informed decisions about when and how many instances to activate, preventing erratic scaling behavior. This feedback mechanism ensures that service quality is maintained through appropriate scaling while system stability is preserved through controlled, data-driven resource adjustments.
Data Source
AI summary
A computing resource service provider may provide computing instances organized into logical groups, such as auto-scaling groups. Computing instances assigned to an auto-scaling group may be place into standby. Standby instances may still be managed by the auto-scaling group but may not contribute to the capacity of the auto-scaling group for auto-scaling purposes.