Bite-Sized Big Tech
Podcast: Play in new window | Download (Duration: 41:56 — 29.0MB)
The main topic for this news episode is a revisiting of the Multi-Cloud subject we touched last time. Next we take a look at an article about the state of the Docker project and we end on an article about an excellent post-morten by Monzo about some trouble they had over the summer.
Continue reading “Episode 158 – Roaring News”Podcast: Play in new window | Download (Duration: 43:29 — 30.1MB)
Today we are joined by Mark Phillips, product marketing manager and more interestingly, heavily involved with Ansible at Red Hat. Now, rather than making this episode specifically about Ansible, Mark shares his extensive expertise on the subjects of orchestration, config management and automation.
Podcast: Play in new window | Download (Duration: 35:34 — 24.7MB)
In this Roaring News episode we start debunking a “85% of companies use multi cloud” statement, look at the future of Data Engineering and are completely astounded at the amount of tracking that happens on the world wide web. We close off with a deeper look at the Cloud Native Computing Foundation open sourcing the Kubernetes audit and go another round on “Smart Data” versus “Big Data”.
Podcast: Play in new window | Download (Duration: 37:25 — 25.9MB)
For a podcast on Big Data, we were amazed that we never covered the subject of NoSQL. So we’re correcting this today. Not by listing and comparing all the NoSQL solutions out there, but rather by going over the differences between the two paradigms. This way we hope to offer enough insight so you can feel comfortable deciding if you should or should not deploy NoSQL in your environment. Continue reading “Episode 155 – NoSQL: You keep using that word…”
Podcast: Play in new window | Download (Duration: 35:01 — 24.3MB)
In this News installment, coming to you courtesy of Dave and Endgaget, we talk about how the Osaka track is paving the way for data free flow across borders and take a look at the alleged problem with the UK’s facial recognition system. Ending on a “high note”, we discuss how Facebook and Googles (and a lot of other’s) MLPerf benchmark is going to change the way we look at our machine learning setups. Or not…
