Instance Availability Estimate via Boot Time Statistics
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Solution Overview
Problem
Customers face frustration due to the lack of specific information regarding the availability of computing resources, such as virtual machine instances, as they are only informed that instances will be ready 'soon' without a clear estimate of the time to availability.
Innovation Solution
A mechanism is implemented within a network-based distributed execution environment to provide an instance availability estimate by collecting data on actual boot times, generating statistics, and offering a 95% confidence estimate of the time to availability, which can be displayed to customers during the waiting period.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the system provides only a generic indication that the instance will be ready 'soon,' then the system complexity is reduced, but the information completeness deteriorates causing customer frustration
Solution Approach 1:
The system performs preliminary actions by collecting boot time data for various instance configurations in advance and storing it in a database. When a customer requests an instance, the system retrieves pre-collected statistics from the database to provide an availability estimate, rather than calculating it in real-time. This preliminary data collection and storage resolves the contradiction by providing comprehensive information without adding complex real-time calculation mechanisms.
2Measurement precision
If the system collects and processes boot time data to generate availability estimates, then the information accuracy is improved, but the processing time and computational resources increase
Solution Approach 1:
The system collects boot time data during instance provisioning and stores it in a database for future reference. When generating availability estimates, the system retrieves pre-collected data from the database rather than performing new measurements. This preliminary data collection approach improves measurement precision while avoiding time loss during the estimation process.
Solution Approach 2:
The system creates a statistical model (copy) of actual boot time behavior based on historical data. Instead of measuring each instance boot time individually in real-time, the system uses the statistical copy (average, standard deviation) to provide instant availability estimates. This copying approach maintains high accuracy while eliminating the time cost of real-time measurement.
3Ease of operation
If the system provides detailed availability estimates with confidence levels, then the customer satisfaction is improved, but the system requires more data collection and statistical processing infrastructure
Solution Approach 1:
The system preliminarily collects boot time data and calculates statistical metrics (average, standard deviation) during the instance provisioning process. This pre-calculated statistical information is stored and readily available when customers request availability estimates. The preliminary calculation of statistical metrics simplifies the customer-facing interface while maintaining the necessary data infrastructure.
Solution Approach 2:
The system implements a feedback mechanism where actual boot times are collected and used to update statistical models. This feedback loop continuously improves the accuracy of availability estimates without requiring complex real-time processing. The system uses simple statistical updates (comparing new data to existing averages and standard deviations) rather than complex algorithms, improving customer experience while limiting infrastructure complexity.
Data Source
AI summary
Data defining the actual time to availability for various configurations of instances of computing resources is collected. The collected data can be utilized to provide an estimate of the expected time to availability for a specific configuration of an instance of a computing resource in response to receiving a request to create a new instance of the computing resource.