Fungible Compute Attribute GUI for Regional Availability
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Solution Overview
Problem
Cloud computing providers face challenges in launching compute instances when user-specified attributes cannot be met, even if functional equivalents are available, due to regional or vendor-specific processor type mismatches.
Innovation Solution
A graphical user interface that allows users to select either user-defined or system-defined values for compute instance attributes, enabling the system to launch the instance with the appropriate values, whether user-selected or system-selected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the user specifies exact values for compute instance attributes (processor type, region, vendor), then the compute instance configuration meets user requirements, but the instance cannot be launched if those exact values are unavailable even if functional equivalents exist
Solution Approach 1:
The system dynamically adjusts the configuration process by allowing users to select between two modes: specifying exact attribute values or providing constraints only. The interface adapts based on user input, transitioning from a rigid value-specification mode to a flexible constraint-based mode when exact values are unavailable, ensuring the compute instance can be launched with equivalent alternatives.
Solution Approach 2:
The system changes the parameter specification approach from fixed exact values to flexible constraints. Instead of requiring specific processor types, regions, and vendors, the system accepts high-level constraints (e.g., processor architecture type, performance tier, budget range) and automatically maps these to available compute instances, resolving the contradiction between meeting requirements and adapting to availability.
2Productivity
If the system automatically selects attribute values when users provide constraints, then the compute instance can be launched with available resources, but the user loses control over specific configuration choices
Solution Approach 1:
The system inverts the traditional configuration workflow by allowing users to first define their constraints and preferences, then automatically generating appropriate attribute values. Instead of users selecting from pre-defined specific values, the system uses the user's constraints to automatically determine suitable values, thereby maintaining user control while enabling automated provisioning.
Solution Approach 2:
The system performs self-service by automatically selecting specific attribute values based on user-provided constraints and real-time availability information. The system autonomously resolves the mapping between high-level constraints and specific configuration values, reducing manual effort while preserving user intent through the constraint-based approach.
Data Source
AI summary
Techniques for configuring and creating a compute instance are disclosed. A system displays, within a Graphical User Interface (GUI), first and second interface elements representing first and second configurable attributes of a compute instance. Each interface element comprises a first selectable component and a second selectable component. The system receives a first user input selecting the first selectable component corresponding to a system-selected configuration for the first configurable attribute and selects a value for the first configurable attribute. The system receives a second user input selecting the second selectable component corresponding to a user-selected configuration for the second configurable attribute and displays a third interface element configured to receive user input specifying a value for the second configurable attribute. The system receives user input specifying the second value for the second configurable attribute and launches the compute instance.