IoT, IIoT and Managing Edge Data

Brian Gilmore (@BrianMGilmore, Director IoT/Emerging Technology @InfluxDB) talks about Edge and Industrial Edge Computing, as well as application and data challenges at the edge.

SHOW: 634

CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotw

CHECK OUT OUR NEW PODCAST - "CLOUDCAST BASICS"

SHOW SPONSORS:

• CloudZero - Cloud Cost Intelligence for Engineering Teams
• Streamline on-call, collaboration, incident management, and automation with a free 30-day trial of Lightstep Incident Response, built on ServiceNow. Listeners of The Cloudcast will also receive a free Lightstep Incident Response T-shirt after firing an alert or incident.
• Pay for the services you use, not the number of people on your team with Lightstep Incident Response. Try free for 30 days. Fire an alert or incident today and receive a free Lightstep Incident Response t-shirt.
• Datadog Application Monitoring: Modern Application Performance Monitoring
• Get started monitoring service dependencies to eliminate latency and errors and enhance your users app experience with a free 14 day Datadog trial. Listeners of The Cloudcast will also receive a free Datadog T-shirt.

SHOW NOTES:

• InfluxData (homepage) - InfluxDB - Time Series Platform
• Understanding Time Series Database Platforms (Cloudcast Eps:394)

Topic 1 - Welcome to the show. Before we get into the fascinating world of Edge and IoT, tell us a little bit about your background, and then where you focus these days with InfluxData.

Topic 2 - It’s been a little while since we covered IoT and IIoT. In the past it was somewhat of a fragmented market segment (lots of definitions, lots of different use-cases). How do you summarize the IoT and IIoT markets in 2022? 

Topic 3 - We’ve always said that the sensor part of IoT isn’t very interesting, but what a company does with the data is very interesting (and complicated). How do companies think about edge data these days – what aspects of the data are valuable? 

Topic 4 - Time Series databases seem like the perfect fit for IoT and IIoT use-cases because they are designed to be both real-time and give historical context (from a time perspective). Is this the case, and why do companies ever consider other types of databases at the edge?

Topic 5 - What are the current best practices about managing data at the edge, in terms of long-term retention and what they eventually do with the data (analysis, analytics, etc.) to better optimize those edge applications? 

Topic 6 - What are some of the emerging trends you’re starting to see happen at the edge, that maybe weren’t on the industry radar a few years ago? 

FEEDBACK?

• Email: show at the cloudcast dot net
• Twitter: @thecloudcastnet