Task Automation Service for Repetitive Compute Workflows
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Solution Overview
Problem
Computing systems in service provider environments face inefficiencies in executing repetitive tasks, as users often perform similar sequences of actions, leading to wasted time and resources due to the lack of automated optimization of compute tasks.
Innovation Solution
A task automation service that monitors and analyzes compute tasks, identifies efficient patterns through machine learning, and provides automation options to automatically execute optimized task sequences, reducing the need for manual repetition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users manually perform repetitive compute tasks in service provider environments, then task execution flexibility is maintained, but time consumption and resource waste increase significantly
Solution Approach 1:
The system automatically performs compute tasks by monitoring user actions and executing learned task patterns without requiring continuous manual intervention. The automation service learns from user behavior and autonomously executes repetitive tasks, allowing the system to serve itself rather than requiring constant human operation.
Solution Approach 2:
The system creates copies of efficient task patterns by monitoring and recording user compute tasks. These task patterns are stored and can be replicated and executed automatically, allowing the most efficient user approaches to be copied and reused across multiple task executions without requiring users to recreate them each time.
2Productivity
If manual compute task execution is used, then user control over task details is maintained, but resource utilization efficiency deteriorates due to repetitive actions
Solution Approach 1:
The automation service continuously monitors user compute tasks and provides feedback by identifying patterns and suggesting optimizations. The system learns from user actions and feeds this information back to improve automation accuracy, allowing users to maintain control while the system progressively becomes more efficient at resource utilization.
Solution Approach 2:
The automation service is designed to handle multiple types of compute tasks across different applications and services within the service provider environment. A single automation system can manage various task types including cloud resource provisioning, data processing, and application deployment, making it universally applicable while improving resource efficiency.
3Loss of time
If compute task automation is implemented, then time and resource efficiency improve, but system complexity increases due to monitoring and pattern recognition requirements
Solution Approach 1:
The automation service acts as an intermediary layer between users and the service provider environment. It monitors user actions, learns task patterns, and executes automated tasks without requiring direct complex interactions between users and the underlying infrastructure. This intermediary handles the complexity of pattern recognition and task execution internally while presenting a simple interface to users.
Data Source
AI summary
A technology is provided for optimizing compute tasks for performing functions in computer environment. Compute tasks and sub-compute tasks that perform a function within computer environment may be monitored. One or more task patterns may be detected based at least in part on the one or more compute tasks. At least one task patterns is identified as an efficient or alternative compute task pattern to perform the function. An automation option is provided to execute the efficient or alternative compute task pattern to perform the function. Each compute task associated with the efficient or alternative compute task pattern may be automatically executed to perform the function upon acceptance of the automation option.