Automation Configuration Items for Measuring Execution Efficacy
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Solution Overview
Problem
Existing automation technologies lack a systematic approach to quantify their efficacy, leading to inefficiencies in resource utilization and time savings across computing systems, particularly in remote network management platforms hosting multiple enterprises.
Innovation Solution
A configuration management database is used to store and update metrics on automation execution time and resource usage, enabling calculation of automation benefits and recommending similar automations for other enterprises based on these metrics, with graphical dashboards providing summarized information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automation technologies are deployed to save time and resources, then productivity improves, but the overhead of definition, development, integration, testing, and maintenance increases
Solution Approach 1:
The patent implements a feedback mechanism where automation efficacies are measured, stored in a configuration management database, and used to generate recommendations. This feedback loop allows the system to learn from past automation performances and make informed decisions about future automation deployments, thereby optimizing the balance between productivity gains and implementation overhead.
Solution Approach 2:
The system enables self-service automation by allowing enterprises to autonomously evaluate automation recommendations based on stored efficacy data. The configuration management database and recommendation engine facilitate autonomous decision-making, reducing the need for manual evaluation and selection of automations.
2Loss of time
If multiple automations are implemented across enterprises, then overall time savings increase, but the difficulty of measuring and comparing efficacy increases
Solution Approach 1:
The patent replaces manual measurement and evaluation methods with an automated system. The configuration management database automatically stores and tracks automation metrics, while the recommendation engine automatically analyzes this data to generate efficacy comparisons and recommendations, eliminating the need for manual measurement and analysis.
Solution Approach 2:
The configuration management database serves multiple functions: storing automation definitions, tracking execution metrics, calculating efficacies, and generating recommendations. This multi-functional approach consolidates what would otherwise be separate measurement and evaluation processes into a single unified system.
3Measurement precision
If automation metrics are stored and analyzed in detail, then automation efficacy can be accurately assessed, but the complexity of the data management system increases
Solution Approach 1:
The patent segments the data management system into distinct functional components within the configuration management database: storage for automation definitions, storage for execution metrics, calculation mechanisms for efficacy, and generation mechanisms for recommendations. This segmentation allows each component to handle specific tasks efficiently, reducing overall system complexity while maintaining measurement precision.
Data Source
AI summary
An embodiment may involve persistent storage containing one or more tables, wherein the tables include entries that specify automations, wherein the automations are software applications. One or more processors are configured to: receive a specification for a new automation, wherein the specification includes a frequency at which the new automation is to be executed, and expected time or resources saved per execution; generate an automation request within the tables, wherein the automation request includes the frequency and the expected time or resources saved; generate a reference from the automation request to an automation configuration item (CI) in the tables, wherein the automation CI represents a software application used to perform the new automation; cause the software application to execute at least part of the new automation and in accordance with the frequency; and measure actual time or resources saved per execution of the new automation.