Cloud Service Analyzer for Network Bottleneck Detection
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Solution Overview
Problem
Cloud-based services face challenges in troubleshooting and performance analysis due to network latency issues and the difficulty in isolating bottlenecks, which affect user experience and compliance with Service Level Agreements (SLAs).
Innovation Solution
A method and system that utilize an analyzer service executed on servers, communicatively coupled to user devices, to perform tests such as traceroutes and web page loads both through and outside the cloud-based system, processing results to identify bottlenecks and issues, and trigger remedial actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If cloud-based services are adopted to reduce costs and improve accessibility, then platform agnosticism and availability are improved, but network latency issues and troubleshooting difficulty worsen
Solution Approach 1:
The patent implements preliminary diagnostic actions by executing traceroute and web page load tests before users experience performance issues. The analyzer application proactively collects network performance data and transmits it to the analyzer service, enabling early detection of latency and bottleneck issues before they impact user experience.
Solution Approach 2:
The patent introduces an intermediary analyzer service that mediates between user devices and the cloud-based service. This service receives diagnostic data from multiple user devices, processes the information centrally, and generates comprehensive performance reports, simplifying the troubleshooting process for both users and service providers.
2Measurement precision
If comprehensive performance tests are conducted to identify bottlenecks, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent implements partial action by selecting specific diagnostic tests (traceroute and web page load tests) that target the most common performance issues. Rather than conducting exhaustive system analysis, the system focuses on measuring network latency and identifying bottlenecks through these key tests, achieving sufficient diagnostic precision with minimal time investment.
Solution Approach 2:
The patent employs periodic action by scheduling performance tests to run at regular intervals or triggered by specific events. The analyzer application can execute diagnostic tests periodically or when performance degradation is detected, balancing continuous monitoring needs with resource consumption and time loss.
3Reliability
If multiple tests are performed both through and outside the cloud-based system, then reliability of performance analysis is improved, but device complexity increases
Solution Approach 1:
The patent implements universality by designing the analyzer application to perform multiple diagnostic functions through a single unified interface. The application can execute both traceroute tests and web page load tests, handle data transmission to the analyzer service, and provide performance analysis, consolidating multiple functions into one application to manage complexity.
Solution Approach 2:
The patent combines multiple diagnostic tests and analysis functions into a unified analyzer service architecture. By merging the collection, processing, and analysis of test data from multiple sources into a single centralized service, the system achieves reliable performance analysis while avoiding the complexity of distributed analysis across multiple separate systems.
Data Source
AI summary
Systems and methods for troubleshooting and performance analysis of a cloud-based service include receiving metrics over time from a plurality of analyzers, wherein the metrics include service-related metrics and network-related metrics related to a cloud-based service, wherein each analyzer of the plurality of analyzers is executed at one of a user device accessing the cloud-based service and in the cloud-based service, and wherein at least one analyzer is executed in the cloud-based service; analyzing the metrics to determine a status of the cloud-based service over the time; and identifying issues related to the cloud-based service utilizing the analyzed metrics over the time, wherein the issues include any of an issue on a particular user device, an issue in a network between a particular user device and the cloud service, and an issue within the cloud service.