Metric Data Aggregator for Cloud Service Performance Monitoring
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Solution Overview
Problem
Current information handling systems lack an efficient method to aggregate and present metric data from multiple cloud-based services, hindering holistic performance analysis and leading to potential false system status assessments.
Innovation Solution
A metric data aggregator system comprising a processor and data store that collects and aggregates service level and cloud level metric data from proxy servers and load balancers, providing aggregated data to remote users for precise analysis and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If metric data is collected from multiple cloud-based services without aggregation, then data collection is simple, but holistic performance analysis cannot be achieved and false system status assessments occur
Solution Approach 1:
The patent introduces a metric data aggregator as an intermediary component that collects metric data from multiple cloud-based services (proxy servers, load balancers) and consolidates it into unified aggregated metric data. This mediator resolves the contradiction by enabling holistic performance analysis without requiring direct complex interactions between multiple service components, thus improving measurement precision while managing system complexity through a dedicated aggregation layer
2Productivity
If aggregated metric data is stored and made accessible, then real-time analysis and visualization are enabled, but data access complexity increases
Solution Approach 1:
The patent implements a data store with automated query processing capabilities that enable remote users to independently access aggregated metric data through standardized query interfaces. The system provides self-service data retrieval mechanisms where users can query and visualize metric data without requiring complex manual processes, thus improving operational efficiency while maintaining ease of operation through automated, user-friendly access methods
Data Source
AI summary
A metric data aggregator includes a processor and a data store. The processor is configured to obtain service level metric data from a plurality of proxy servers; obtain cloud level metric data from a plurality of proxy servers and at least one load balancer; aggregate the service level metric data and the cloud level metric data; and provide the aggregated service level and cloud level metric data to a remote user. The data store configured to store aggregated cloud level and service level metric data; and retrieve the aggregated service level and cloud level metric data in response to queries.