Continuous Intelligence¶
This site provides documentation for this project. Use the navigation to explore module-specific materials.
How-To Guide¶
Many instructions are common to all our projects.
See ⭐ Workflow: Apply Example to get these projects running on your machine.
Project Documentation Pages (docs/)¶
- Home - this documentation landing page
- Project Instructions - instructions specific to this module
- Your Files - how to copy the example and create your version
- Glossary - project terms and concepts
Additional Resources¶
Custom Project¶
Dataset¶
The dataset includes system performance metrics with columns for requests, errors, and total latency in milliseconds. Each row represents a snapshot of system activity and performance.
Signals¶
I used the original signals and added one new one:
- error_rate – percentage of failed requests
- success_rate – percentage of successful requests
- avg_latency_ms – average response time per request
- throughput – number of requests handled
Experiments¶
I modified the original project by adding a new signal called success_rate to better understand system reliability. I also added a graph to visualize how latency and error rate change across observations.
Results¶
The results showed that the system has a consistently low error rate and a high success rate. The graph also showed that as the number of requests increases, the average latency slightly increases.
Interpretation¶
This means the system is reliable but may slow down under higher demand. From a business perspective, this insight helps identify when performance improvements may be needed to maintain a smooth user experience during peak usage.