Wiredgorilla

The Raspberry Pi Foundation has a new product — the Raspberry Pi 400. The flagship Raspberry Pi 4 was released in June 2019. Since, they added an 8GB model, brought out the Compute Module 4, we certified all Raspberry Pis since Raspberry Pi 2 and we worked together to make the full Ubuntu Desktop ‘just work’ on a Raspberry Pi 4. Now, Ubuntu Server and Ubuntu Desktop also work, out of the box, with the all-new Raspberry Pi 400.  You can get it on its own, the Raspberry Pi 400 keyboard computer itself. Or as a kit including a beginners guide, a Raspberry Pi official power supply and an official mouse (pictured at the end of the article). We are also delighted to say that for a month you can also get an Ubuntu Desktop Groovy Gorilla sticker when you purchase a Raspberry Pi 4 from Pimoroni. The folks at Pimoroni run their Raspberry Pi business on Ubuntu and very kindly agreed to ship some Groovy Gorilla merch with relevant orders. The latest and greatest The changes from the ...

Kubeflow, the ML toolkit on K8s, now fits on your desktop and edge devices! ? Data science workflows on Kubernetes Kubeflow provides the cloud-native interface between Kubernetes and data science tools: libraries, frameworks, pipelines, and notebooks. > Read more about what is Kubeflow Cloud-native MLOps toolkit gets heavy To make Kubeflow the standard cloud-native tool for MLOps within the AI landscape, the open-source community has accomplished the aggregation and integration of many projects on top of Kubernetes. Unfortunately, this notable accomplishment also has a downside. Deploying Kubeflow on your laptop or edge device has become impractical. The very minimum memory necessary to deploy the full Kubeflow bundle is 12Gb of RAM. On top of that, it is Linux-based. This means that on Windows and macOS you need to allocate 12+ Gb of memory to a Linux VM. Last time I tried, my 16Gb of RAM MacBook Pro did not like the idea. Kubeflow lite to experiment on ...

In October, we shared a blog post detailing significant snap startup time improvements due to the use of a new compression algorithm. In that article, we focused on the cold and hot application startups, but we did not delve much into the first-run setup scenario. While running our tests, we observed a rather interesting phenomenon, primarily on the Fedora 32 Workstation system. On a particular laptop, we noticed that the initial snap launch took about 60 seconds, whereas cold launches would take about 10 seconds. We decided to analyze this problem, and once we did, we realized there’s an amazing investigative story to be shared, including some really cool findings and general advice for developers on how to optimize their snaps. First-run startup time It is important to note that the difference (6x) was what drew our eye – rather the actual numbers, as these are highly dependent on the platform capabilities and software in question. For that matter, 6-second and 1-second launch ti...