Monitoring Tool Configuration in Distributed Computing Systems
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Solution Overview
Problem
Current distributed computing systems require manual reconfiguration of monitoring tools to accommodate changes in virtual objects and services, which is time-consuming, error-prone, and increases costs due to increased network traffic and resource demands.
Innovation Solution
Automated methods to identify new virtual objects and changes in functionalities, adjusting monitoring configurations and resource allocation rules to dynamically manage infrastructure resources and auxiliary services, optimizing the distribution of virtual objects across server computers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual reconfiguration of monitoring tools is performed to accommodate new virtual objects or functionality changes, then monitoring accuracy is improved, but time consumption and error rate increase
Solution Approach 1:
The system performs preliminary actions by automatically detecting changes in virtual objects and their functionalities before manual intervention is needed. The monitoring tool proactively identifies when new virtual objects are deployed or when existing ones change functionality, and automatically adjusts monitoring configurations in advance, eliminating the need for time-consuming manual reconfiguration while maintaining monitoring accuracy.
Solution Approach 2:
The monitoring tool is designed to be self-service capable by automatically detecting changes in the distributed computing system environment and self-adjusting its configuration without human intervention. The system monitors itself and adapts to changes autonomously, reducing both time consumption and potential human errors associated with manual reconfiguration.
2Measurement precision
If manual reconfiguration of monitoring tools is performed to accommodate new virtual objects or functionality changes, then monitoring accuracy is improved, but error rate increases
Solution Approach 1:
The monitoring tool automatically detects changes in virtual objects and their functionalities and adjusts its own configuration without human intervention. This self-service capability eliminates human errors that occur during manual reconfiguration while maintaining the necessary monitoring accuracy through automated rule-based adjustments.
Solution Approach 2:
The system implements a feedback mechanism where the monitoring tool continuously monitors the distributed computing system for changes in virtual objects and their functionalities. When changes are detected, the system automatically feeds this information back into the configuration adjustment process, ensuring monitoring accuracy is maintained while avoiding human errors through automated decision-making.
3Productivity
If monitoring tool resources are increased to accommodate increased network traffic from new virtual objects, then monitoring capability is improved, but resource costs increase
Solution Approach 1:
The monitoring tool employs dynamic resource allocation that automatically adjusts resource consumption based on the actual workload and network traffic conditions. When new virtual objects are deployed and increase network traffic, the system dynamically scales monitoring resources to match the demand, avoiding both resource shortages and unnecessary resource consumption, thereby maintaining monitoring capability while optimizing resource costs.
Solution Approach 2:
The system changes operational parameters by automatically adjusting monitoring resource allocation based on detected changes in virtual objects and network traffic patterns. This parameter adjustment ensures that monitoring capability is maintained at appropriate levels without over-provisioning resources, thus improving productivity while controlling resource costs.
Data Source
AI summary
Methods and systems adjust resources and monitoring configuration of a monitoring tool and auxiliary servers of a distributed computing system. Any new virtual object installed in the distributed computing system or change in functionality of an existing virtual object of the distributed computing system is identified. Expected configuration rules and resource allocation rules are determined for the virtual object. The expected configured rules are used to adjust a monitoring configuration of the monitoring tool. The resource allocation rules are used to adjust the infrastructure resources available to the monitoring tool. When the virtual object creates a change in demand for auxiliary services, corresponding auxiliary servers are installed, removed, or changed in the distributed computing system. Resource allocated rules and expected configuration rules are determined for the auxiliary servers and used to adjust the infrastructure resources and monitoring configuration of the monitoring tool. Methods optimize distributions of virtual objects.