Virtual Compute Sub-Pool Segregation for Latency and Security
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Solution Overview
Problem
Current virtual compute systems face challenges in providing secure, customizable, and efficient compute capacity, particularly in handling latency-sensitive requests and complying with regulatory requirements, due to shared hardware usage and rigid execution schemes that do not adequately address user-specific needs such as cost, latency, and error rates.
Innovation Solution
The implementation of a virtual compute system that maintains multiple sub-pools of pre-initialized virtual machine instances segregated at the hardware level, allowing for customized code execution environments based on user needs, with the ability to pre-warm instances with specific software configurations to reduce latency and enhance security by using single-tenanted hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple sub-pools of virtual machine instances are maintained segregated at the hardware level, then data security and regulatory compliance are improved, but device complexity and resource allocation overhead increase
Solution Approach 1:
The system divides the virtual machine instance pool into multiple sub-pools segregated at the hardware level, where each sub-pool is dedicated to specific users or workloads. This physical segmentation ensures that data from different users cannot be accessed by others, providing robust security and compliance with regulations that require data isolation.
Solution Approach 2:
The capacity acquisition and maintenance manager acts as an intermediary that automatically manages the complexity of hardware segregation. It handles the acquisition, allocation, and maintenance of compute capacity across multiple hardware-segregated sub-pools, shielding users from the underlying complexity while ensuring security requirements are met.
2Loss of time
If virtual machine instances are pre-initialized and pre-warmed with software components, then code execution latency is reduced, but compute resource availability and cost increase
Solution Approach 1:
Virtual machine instances are pre-initialized with necessary software components and kept in a pre-warmed state within the sub-pools. This preliminary preparation ensures that when code execution is requested, the instances are already ready to run, significantly reducing startup latency and enabling faster code execution.
Solution Approach 2:
The system dynamically manages the pre-warmed instances in sub-pools, adjusting the number and state of virtual machine instances based on demand. When execution requests are received, pre-warmed instances are quickly activated; when demand is low, instances can be de-provisioned or returned to a lower-power state, optimizing resource consumption.
3Reliability
If compute capacity is dedicated and reserved for specific users, then execution reliability and security are improved, but system adaptability and resource utilization efficiency decrease
Solution Approach 1:
The system segments compute capacity into dedicated sub-pools for specific users while maintaining the ability to manage and allocate resources dynamically within each segment. This segmentation provides execution reliability and security guarantees while allowing flexible resource management within the constraints of each user's dedicated pool.
Data Source
AI summary
A system for providing low-latency computational capacity from a virtual compute fleet is provided. The system may be configured to maintain a plurality of virtual machine instances on one or more physical computing devices, wherein the plurality of virtual machine instances comprises a first pool comprising a first sub-pool of virtual machine instances and a second sub-pool of virtual machine instances, and a second pool comprising virtual machine instances used for executing one or more program codes thereon. The first sub-pool and/or the second sub-pool may be associated with one or more users of the system. The system may be further configured to process code execution requests and execute program codes on the virtual machine instances of the first or second sub-pool.