Application Uptime Calculation via Incident Report Correlation
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Solution Overview
Problem
Existing database management systems face challenges in optimizing performance and resource utilization, particularly in handling complex queries and large volumes of data, especially when deployed on cloud-based platforms.
Innovation Solution
An application uptime system that monitors the execution of applications, collects end user and development system incident reports, determines end user metrics, generates user interface views, and presents them to provide enhanced visibility into application availability and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous monitoring of application execution is implemented, then application reliability and uptime metrics are improved, but system resource consumption and operational complexity increase
Solution Approach 1:
The monitoring system operates periodically rather than continuously, activating monitoring only when external triggers indicate potential incidents. This periodic approach maintains reliability by detecting incidents when they occur while reducing resource consumption by stopping monitoring during normal operation periods.
Solution Approach 2:
The system performs preliminary actions by collecting incident reports and determining uptime metrics proactively, generating user interface views that present application availability status before users need to query for this information, thereby improving reliability visibility without continuous monitoring overhead.
2Measurement precision
If incident report collection and analysis is performed, then application uptime metrics and end user experience insights are improved, but data processing time and system resource usage increase
Solution Approach 1:
The system extracts only the necessary incident report data elements needed for uptime calculation, separating essential metrics from unnecessary detailed information. This extraction approach maintains measurement precision by focusing on critical data points while reducing data processing time by eliminating redundant analysis.
3Use of energy by moving object
If monitoring is activated only upon external triggers, then resource consumption is reduced, but detection speed for unexpected incidents may be worsened
Solution Approach 1:
The system uses feedback from external triggers to activate monitoring, where incident reports and system events provide feedback signals that trigger monitoring activation. This feedback mechanism ensures rapid detection of actual incidents while maintaining low resource consumption during normal operation, as monitoring activates automatically when feedback indicates an incident occurrence.
Data Source
AI summary
In some implementations, there is provided a method that includes monitoring, by an application uptime system, whether execution of an application is successful without causing an incident; in response to the execution of the application being unsuccessful and causing the incident, the method further comprising: collecting one or more end user incident reports including an incident identifier, a start time of the incident, and a stop time of the incident, collecting one or more development system incident reports linked to the one or more end user incident reports, determining at least one end user metric for the application, generating one or more user interface views based on the at least one end user metric for the application, and causing to be presented the one or more user interface views. Related systems, methods, and articles of manufacture are also disclosed.