Operations | Monitoring | ITSM | DevOps | Cloud

It’s time to stop proclaiming that “cloud native is the future”. Kubernetes has just celebrated its 10 year anniversary, and 76% of respondents to the latest CNCF Annual Survey reported that they have adopted cloud native technologies, like containers, for much or all of their production development and deployment. Cloud native isn’t the future – it’s here and now. Data-intensive workloads are no exception.

Technology procurement directly influences business success. The equipment you procure will determine how your teams deliver projects and contribute to your success. So what does being “well-equipped” look like in the world of Linux laptops? In this blog, we’ll lay down the best practices for procurement professionals who have been tasked with procuring Linux laptops.

One of the most critical gaps in traditional Large Language Models (LLMs) is that they rely on static knowledge already contained within them. Basically, they might be very good at understanding and responding to prompts, but they often fall short in providing current or highly specific information.

What is patching automation? With increasing numbers of vulnerabilities, there is a growing risk of cyber incidents, attacks and breaches. It’s more important than ever to ensure that your systems are protected 24/7. Patching is a vital step in any vulnerability management process.

In a 2020 paper, Patrick Lewis and his research team introduced the term RAG, or retrieval-augmented generation. This technique enhances generative AI models by utilizing external knowledge sources such as documents and extensive databases. RAG addresses a gap in traditional Large Language Models (LLMs). While traditional models rely on static knowledge already contained within them, RAG incorporates current information that serves as a reliable source of truth for LLMs.