Looking at the report that Gartner did in 2022 regarding top technology trends, AI engineering represents an important pillar in the near future. It is composed of three core technologies: DataOps, MLOps and DevOps.The discipline’s main purpose is to develop AI models that can quickly and continuously provide business value. For instance, models that enable cross-functional collaboration, automation, data analysis, and machine learning.
On 8 November 2022, at Open Source Experience Paris, Canonical announced that Charmed Kubeflow, Canonical’s enterprise-ready Kubeflow distribution, now integrates with MindSpore, a deep learning framework open-sourced by Huawei. Charmed Kubeflow is an end-to-end MLOps platform with optimised complex model training capabilities designed for use with Kubernetes.
Both servers and software development use Linux. Today, Linux distributions are used by the vast majority of electronics and embedded systems. Worldwide, Linux servers make up about 90% of all internet servers. Additionally, the Linux kernel is used by around 80% of all smartphones. Today, every system in the world is linked via a network. Information exchange across systems requires network connectivity. Computer networking refers to communication over the internet as well as within a network.
Welcome to the concluding blog of this mini-series on tapping into the fourth industrial revolution. In Part I, we introduced and assessed the current status in the IT and OT domains. In Part II, we discussed the automation pyramid of modern factories and the need to adopt a more holistic approach toward closing the divide.
If you’re embarking on a new project and evaluating public clouds, the cost involved will be one of your main considerations. You might decide to use Google Cloud Platform (GCP) as your primary cloud platform. If so, you’ll want to estimate costs based on listed prices. But it might surprise you to find a higher bill than you originally expected.
This is the third blog from a series focusing on how public clouds meet telecommunication operators’ business demands. In the previous two blogs, we talked about how Amazon Web Services (AWS) and Google Cloud Platform have enabled telcos to run critical workloads on public clouds. In this last part of our series, you’ll hear about Microsoft Azure cloud and why it’s a trusted platform for the telecommunication industry to host their workloads.
Monitoring KSM (Kernel Same-page Merging) performance at deduping memory shared across VMs.
In the first part of this blog series, we discussed the run-time (in)security challenge, which can leave your code and data vulnerable to attacks by both the privileged system software of the public cloud infrastructure, as well as its administrators. We also introduced the concept of trusted execution environments and confidential computing, (CC), as a paradigm to address this challenge.
Users live in the sunlit world of what they believe to be reality. But, there is, unseen by most, an underworld. A place that is just as real, but not as brightly lit. The Kernel Parameter side (apologies to George Romero). Kernel parameters aren’t really that scary in actuality, but they can be a dark and cobweb-filled corner of the Linux world. Kernel parameters are the means by which we can pass parameters to the Linux (or Unix-like) kernel to control how that it behaves.
Welcome to Part II of this three-part mini-series on bridging the gap between operational technology (OT) and information technology (IT) in Industry 4.0. In Part I, we set the stage for the remainder of the series and gave an overview of IT and OT, the two technological layers of modern industrial factories. In this blog, we expand on that knowledge by confronting the two domains and discussing the automation pyramid concept.
