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Artificial Intelligence (AI) is revolutionizing businesses across industries. From personalized customer experiences to predictive analytics and process automation, there are hardly any sectors untouched by AI's impact. Its applications in data management aren't left behind. In fact, AI has the potential to transform traditional data management practices.

In our previous article, we outlined what a Linux coredump is and how they work under the hood. One common constraint we see in embedded Linux, however, is a limited amount of storage space. Whether we’re trying to limit writes to disk, or need to reserve most of the disk space available to a device for other data, sometimes we just don’t have enough space to store coredumps.

If you've been in earshot of tech leadership lately, you've probably heard the words 'EU,' 'AI,' and 'compliance' in conversation. The EU AI Act is officially upon us, and with it comes a whole new set of incident response and reporting requirements that might feel like a yet another bureaucratic set of requirements to worry about. But there's a different way to look at this legislation.

Artificial intelligence is reshaping how enterprises manage and secure their networks, but not all AI is created equal, and not all Large Language Models (LLMs) are ready for the job. While tools like ChatGPT and Google Gemini are transforming communication and productivity, applying general-purpose LLMs to something as specialized and high-stakes as network operations is an entirely different challenge. Networks are dynamic, complex, and context-heavy.

Over the past ten years, Azure has become one of the most prominent cloud computing platforms available, rivaled only by AWS. Part of Microsoft’s suite of Azure services, Azure web apps provide a packaged environment for hosting web applications built in many languages. Because this environment is fully managed by Azure, developers have limited options for control.