Custom Project¶
Dataset¶
I used web service metrics which contained number of errors, requests and total latency time. (Source: https://denisecase.github.io/pro-analytics-02/reference/datasets/cintel/#9-web-service-metrics-example-file)
Signals¶
The main signals of interest were error rate, average latency time, and latency percentiles.
Experiments¶
I began by adding a histogram of latency time, latency is one of the "Four Golden Signals" and the tail end represents particularly lengthy requests or errors. I then added a econd graph showing the correlation of requests and error rate to average latency time..
Results¶
Only 3 of the data rows had a latency above the 90th percentile. Of these three the error rate was on the higher side, averaging around 4.5%, the total number of requests was also high.
Interpretation¶
Without detailed latency information (latency per request versus per error, for example) it's difficult to determine if errors are slow or if more requests result in greater latency.
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