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Practical Zephyr - Devicetree semantics (Part 4)

Having covered the Devicetree basics in the previous article, we now add semantics to our Devicetree using so-called bindings: For each supported type, we’ll create a corresponding binding and look at the generated output to understand how it can be used with Zephyr’s Devicetree API. Notice that we’ll only look at Zephyr’s basic Devicetree API and won’t analyze specific subsystems such as gpio in detail.

IT, End Users, and AI Navigating the New Love Hate Triangle of Support

AI is unquestionably the trendy new heartthrob in town, but as more business leaders get swept up in googly-AI-ed fantasies, is it putting real-life employee relationships at risk? Join us for a Valentine's Day webinar where we'll tackle the hottest questions in IT.

Aiven workshop: Learn Apache Kafka with Python

What's in the Workshop Recipe? Apache Kafka is the industry de-facto standard for data streaming. An open-source, scalable, highly available and reliable solution to move data across companies' departments, technologies or micro-services. In this workshop you'll learn the basics components of Apache Kafka and how to get started with data streaming using Python. We'll dive deep, with the help of some prebuilt Jupyter notebooks, on how to produce, consume and have concurrent applications reading from the same source, empowering multiple use-cases with the same streaming data.

The Evolution of Business: Why Mobile Apps are the Future

In the digital age, the business landscape has been profoundly transformed by the advent of mobile technology. With smartphones becoming ubiquitous, mobile apps have emerged as essential tools for enterprises looking to thrive in a competitive market. They serve not only as direct marketing channels but also as platforms for customer engagement and personalized services, heralding a new era in which agility and accessibility are key to business advancement.

Building a Privacy-First AI for Incident Management

At Rootly, we're integrating AI into incident management with a keen eye on privacy. It's not just about tapping into AI's potential; it's about ensuring we respect and protect our customers’ privacy and sensitive data. Here's a quick overview of how we're blending innovation with strong privacy commitments.

The Real Cost of Synthetic User Testing with AWS

Every time I share a project using SaaS tools, someone inevitably responds that they could do the same thing on their own home server ‘for free.’ I mention this not because it is annoying, since I would never go on social media at all if annoying responses were allowed to change my behavior, but because I think it points to a basic misconception that still affects DevOps practitioners today: the refusal to accurately estimate the real costs of self-managed solutions.

Codefresh in the Wild: building Starbase-80

This article is part of our series “Codefresh in the Wild” which shows how we picked public open-source projects and deployed them to Kubernetes with our own pipelines. This week’s pick is starbase-80, a Kubernetes “homepage” application. We will use various tools such as GitHub, Docker, AWS, Codefresh, Argo CD, Terraform. This article chronicles how we integrated all those tools together in order to build an end-to-end deployment workflow.

Safer Client-Side Instrumentation with Honeycomb's Ingest-Only API Keys

We're delighted to introduce our new Ingest API Keys, a significant step toward enabling all Honeycomb customers to manage their observability complexity simply, efficiently, and securely. Ingest Keys are currently available for Environment & Services customers, with Classic support and programmatic key management capabilities under development and coming soon!

Codefresh in the Wild: Building draw.io

This article is part of our series “Codefresh in the Wild” which shows how we picked public open-source projects and deployed them to Kubernetes with our own pipelines. This week’s pick is draw.io an online application for drawing different types of diagrams. We will use several tools such as GitHub, Docker, Helm Codefresh, Argo Rollouts, Argo CD. This guide chronicles how we integrated all those tools together in order to build an end-to-end Kubernetes deployment workflow.