#cloud-native

#cloud-native

AI inference is the process by which a trained large language model (LLM) applies what it has learned to new data to make predictions, decisions, or classifications. In practical terms, the process goes like this. After a model is trained, say the new GPT 5.1, we use it during the inference phase, where it analyzes data (like a new image) and produces an output (identifying what's in the image) without being explicitly programmed for each fresh image. These inference workloads bridge the gap between LLMs and AI chatbots and agents.

The Spring Framework is possibly the most iconic software development framework of all time. It once suffered from a reputation of bloat, but it has long since shed that perception. In this article, we'll take fresh look at Spring, including an overview of Spring Boot and how Spring handles standard application needs like persistence and security. You'll also learn about newer features that modernize Spring, including its approach to developer experience, reactive programming, and cloud and serverless development.

"Bringing DevOps Principles to Controls and Audits", not the most exciting title in the world, but I'm actually going to be talking about a revolution. What I'm talking about is an open-source project that me and my colleagues at Container Solutions are working on. My goal is that by the end of it, you'll be interested enough to check it out, perhaps give feedback, maybe even get involved.

"Solo.io is a cloud connectivity company. Its main cloud products are Gloo Gateway, a cloud-native API gateway built on Envoy, and Gloo Mesh, which aims to simplify Istio service mesh management for Kubernetes. And, of course, there are the inevitable AI-related products. When we spoke to Levine, Solo.io had just announced an MCP gateway for kgateway (described by the company as "the ecosystem's most mature and widely deployed cloud-native API gateway"). Most recently, the company announced that it had donated agentgateway to the Linux Foundation."

The real value in multi-cloud operations lies in providing consistent operations across AWS, Azure, and Google Cloud Platform. "If I want to run something in Google and I want to run something in Amazon, if I have to learn new ways of doing things... it becomes more complex for the enterprise," he explained. Nutanix enables organizations to maintain the same operational model across all cloud environments, reducing training requirements and operational complexity.

The transition from local development to production is crucial in creating a seamless developer experience, which is a focus for tools and frameworks today.

The new version of Veeam Kasten for Kubernetes focuses on enterprise-ready virtualization, enhanced security, easy scalability, and customer choice, unifying data protection for VMs.