2020 >
Monitoring IoT Devices At Scale
Tyler Hoffman- Watch Now - Duration: 39:03
I'd like to talk about how companies should think about and build out their IoT monitoring solutions using metrics. The differences between logs, metrics, and traces have been talked about at length in the software engineering space, but not for firmware. Using metrics to monitor a fleet of devices allows for assessing the health of thousands to millions of devices, even across groups of devices or firmware versions, all while keeping complexity, bandwidth, and power consumption to a minimum.
Takeaways:- Know how to think about and build a metrics library for gathering compressed and aggregated metrics on devices
- Understand the differences between logs, metrics, and traces, and why using metrics is the best way to monitor fleets of devices post-deployment.
- Know the next steps on how to ingest the data in a server under their control to do monitoring analysis.
- Learn some formulas for calculating fleet health, such as expected battery life, crash free hours, and average connectivity per hour.
Very interesting content, thanks for presenting. Logging, state capture and trend analysis are obviously not new techniques however it's great to see how you're adapting them for the IOT world and using the captured data for defect identification and continuous quality analysis.
Thank you for the informative presentation!
Awesome presentation, very informative, thank you very much.
This is an outstanding presentation! I've used many of these techniques, both device side and server side, because I'm a total data hound. Data is power! It's saved my butt many times, reactively and proactively. Feeding data into tools like Stackdriver, Kibana, Grafana, and Splunk gives great queriability and graphability. Being able to visualize things gives quick alert and visibility to issues. It's also a great analytical debug method.