February 14th, 2018 | 26 mins 58 secs
ai, application development, cloud, cloud computing, developers, edge computing, internet of things, iot, kubernetes, open source, programming, software, software development, tech, technology
For this episode of The New Stack Makers, Host TC Currie is joined by Steve Herrod, VC at General Catalyst where he focuses on infrastructure. He recently published an article on LinkedIn called Cloud vs. Edge – This is Not a Cage Match.
“It comes down to the use cases,” Herrod said about the difference between Cloud and Edge computing, "You don’t want your car’s IoT chip to have to go to the cloud before it decides to make the turn, but it’s faster to go to the cloud to crunch a bunch of sensor data from thousands of IoT devices."
February 12th, 2018 | 42 mins 39 secs
application development, bons.ai, cloud, developers, devops, iot, kubernetes, open source, podcast, programming, software, software development, tech, technology
Here’s something that probably doesn’t cross most developers’ minds: In a distributed system whose components don’t share state with one another, how does one produce an application whose stated goal, if you will, is to create and maintain a state — specifically, something learned?
January 17th, 2018 | 20 mins 59 secs
application development, cloud, cloudnativecon, cncf, developers, devops, iot, kubecon, kubernetes, open source, podcast, programming, software, software development, tech, technology
On today's episode of The New Stack Makers, we were joined by Cloud Native Computing Foundation COO Chris Aniszczyk alongside Weaveworks CEO Alexis Richardson to address all things CNCF, including its roadmap heading into 2018 and beyond.
January 11th, 2018 | 45 mins 15 secs
big data, computer science, data, data analysis, data management, data streaming, iot, mapr, netflix, programming
Autonomous cars alone create over 3-4 terabytes of data per vehicle hour. There are new businesses like Netflix creating huge volumes of data. No industry has seen this volume of data ever before. How are we going to leverage this data? What are the challenges as we slip into a data driven world? How is machine learning going to help?