This content type is full of IndieWeb post types, which are all content types which allow me to take greater ownership of my own data. These are likely unrelated to my blog posts. You can find a better breakdown by actual post kind below:
The word “microservices” started getting used after a series of events–companies were moving to cloud virtual machines. Those VMs got broken up into containers, and the containers can fit to the size of the service. Services that are more narrowly defined take up smaller containers, and can be packed more densely into the virtual machines–hence
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Podcast (mp3): Download (Duration: 1:38 — 1.2MB)
This isn’t a proper episode. It’s just Joe giving a very quick update on the OggCamp live show. It will be a joint effort with the Ubuntu Podcast …
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It’s the Late Night Ubuntu Podcast! Recorded live at OggCamp 17, Jesse and Joe are joined by Martin and Mark from the Ubuntu Podcast for a (very …
Anjana is fascinated by languages, both human and machine, and the connections between the two. She recently completed a MS in computational linguistics at Saarland University in Germany, where she studied speech technology, machine learning, and computer-assisted language learning. Her spontaneous talk "Learning Functional Programming with JavaScript" has been viewed over a half-million times on YouTube. She talks to Scott about her thoughts on languages and her strategies for learning.
Patrick Chanezon (Docker) chats with John and Damon about trends that are changing how Developers work. Show notes at http://devopscafe.org – Listen to DevOps Cafe Ep. 73 - Guest: Patrick Chanezon by DevOps Cafe Podcast instantly on your tablet, phone or browser - no downloads needed.
After raising $18 million, social networking startup Yubl made a series of costly mistakes. Yubl hired an army of expensive contractors to build out its iOS and Android apps. Drama at the executive level hurt morale for the full-time employees. Most problematic, the company was bleeding cash due to a massive over-investment in cloud services.
Serverless computing reduces the cost of using the cloud. Serverless also makes it easy to scale applications. The downside: building serverless apps requires some mindset shift. Serverless functions are deployed to transient units of computation that are spun up on demand. This is in contrast to the typical model of application delivery–the deployment of an
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Mozilla launches yet more projects, Krita had a brush with the tax man, Flash is on the way out, Debian is almost totally reproducible, Mycroft …