As a backend developer, I want to optimize the database queries and server performance so that the system can handle large amounts of sensor data efficiently.
Description
This use case focuses on optimizing the backend for better performance, particularly with large datasets of sensor data. This involves improving the efficiency of database queries, reducing response times, and optimizing the server to handle high traffic. The goal is to ensure the system can scale and handle real-time and historical data requests without performance degradation.
Acceptance Criteria
[ ] Database queries for retrieving real-time and historical data are optimized for performance.
[ ] The system is able to handle large datasets efficiently without significant delays or timeouts.
[ ] The system is load-tested to ensure it can handle increased traffic and large volumes of data.
Testing
Normal Flow of Events
The backend team reviews and optimizes the database queries used for real-time and historical data retrieval.
Load testing is performed to simulate high traffic and ensure the system performs efficiently under stress.
API response times are monitored and optimized to meet performance goals.
Alternate/Exceptional Flows:
S-1:Database query performance issues
The queries take too long to retrieve data.
The backend team adds indexing, query optimizations, or caching to improve performance.
Backend Performance Optimization
User Story
As a backend developer, I want to optimize the database queries and server performance so that the system can handle large amounts of sensor data efficiently.
Description
This use case focuses on optimizing the backend for better performance, particularly with large datasets of sensor data. This involves improving the efficiency of database queries, reducing response times, and optimizing the server to handle high traffic. The goal is to ensure the system can scale and handle real-time and historical data requests without performance degradation.
Acceptance Criteria
Testing
Normal Flow of Events
The backend team reviews and optimizes the database queries used for real-time and historical data retrieval. Load testing is performed to simulate high traffic and ensure the system performs efficiently under stress. API response times are monitored and optimized to meet performance goals.
Alternate/Exceptional Flows:
S-1:Database query performance issues
The queries take too long to retrieve data. The backend team adds indexing, query optimizations, or caching to improve performance.