Build a dashboard to monitor application performance and alert support teams in real time.
The goal is to create a web application that provides a comprehensive view of application health, including server uptime, response times, error rates, and resource utilization. Alerts can be configured to notify the support team if any parameter exceeds a predefined threshold, ensuring prompt response to potential issues. Historical data logging can also help in diagnosing recurring issues and making data-driven decisions.
Develop a system that automates tracking, categorizing, and resolving common issues reported by users.
This project involves creating a ticketing system that uses automation to categorize issues, assign priority levels, and potentially resolve frequent issues based on predefined solutions or decision trees. Integrating machine learning algorithms can enhance its capabilities by analyzing historical data to suggest solutions for new issues. Additionally, the system should have reporting and analytics to help support teams identify trends in issues and optimize response strategies.