Operations | Monitoring | ITSM | DevOps | Cloud

Observability and Security for the AI Era

Datadog has always been driven by a broader vision of helping teams understand and operate complex systems. In this session, you’ll hear from Yrieix Garnier, VP of Product, and Hugo Kaczmarek, Senior Director of Product, as they share the latest updates across the Datadog product suite and discuss how that vision continues to shape the platform’s evolution and support the next generation of AI-driven applications.

AI Cost Management: How To Track, Allocate And Optimize AI Spend

AI cost management is the practice of tracking, allocating, and optimizing the cloud infrastructure costs tied to building, running, and scaling AI workloads. It differs from traditional cloud cost optimization because AI infrastructure behaves differently at every layer of the stack. The biggest problem isn’t overspending. It’s that most organizations can’t see where their AI spending is going.

How to Translate YouTube Videos: Tools and Best Practices

Most creators don't think about translation until they open their analytics one day and see traffic coming in from Brazil, Germany, or Japan. And they just sit there staring at it like, wait, people actually want to watch this? In a different language? That's usually the moment it all clicks. The good news is that tools built to translate YouTube video content have gotten genuinely good. Not impressive for a computer good. Actually, it's good. Dubbed audio that sounds natural, lip sync that holds up, and a workflow that doesn't require a team or a big budget to pull off.

Investors Balance Growth Potential and Structural Risks in Apple Ecosystem

The smartphones, smart devices, and ecosystem services market remains under pressure due to technological limitations and ongoing structural changes at companies such as Apple. Despite a 4% decline in smartphone sales in China during the first two months of 2026, the company managed to increase iPhone sales by 23%, driven by seasonal discounts and subsidies on the base iPhone 17 model.
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AlmaIQ brings unparalleled level of efficiency and effectiveness for IT teams using Collective IQ

AlmaIQ, the intelligent self-service agent for employees just received an incredible boost that expands its role to uniquely help IT teams. Interacting with users through Microsoft Teams, AlmaIQ answers questions about devices and internal processes in natural language. Whereas that intelligence simplified employees lives on the job, it now enables IT teams to interact with Collective IQ at the level of departments, groups, and collections of devices to spot patterns and trends. The overall result: vastly more productive operations and satisfied employees.

#054 - From Shiny Objects to FinOps: Taming Cloud Costs in the AI Era with Josh Schlanger (CloudX...

In this episode of the Kubernetes for Humans podcast, we are joined by infrastructure and FinOps expert Josh Schlanger. Drawing on over 15 years of experience across Martech, e-commerce, and health tech, Josh shares why solving core business problems should always take priority over chasing new, "shiny object" technologies.

Jensen Huang's warning: lead the AI transition - or finance it

The wrong people got the most attention from Jensen Huang’s comments last week. Huang told the All-In Podcast that he’d be “deeply alarmed” if a $500,000 engineer consumed less than $250,000 in AI tokens annually. Within 48 hours, the discourse collapsed into a compensation debate.

AI Deployment in Production: Orchestrate LLMs, RAG, Agents | Harness Blog

For the past few years, the narrative around Artificial Intelligence has been dominated by what I like to call the "magic box" illusion. We assumed that deploying AI simply meant passing a user’s question through an API key to a Large Language Model (LLM) and waiting for a brilliant answer.

LiteLLM Compromise: Securing AI Pipelines from PyPI Supply Chain Attacks | Harness Blog

On March 24, 2026, the AI open-source ecosystem was impacted by a critical supply chain attack involving the widely used Python package LiteLLM. Attackers compromised the LiteLLM PyPI distribution pipeline and published malicious versions (notably in the 1.82.7-1.82.8 range), embedding a multi-stage payload designed to steal credentials and execute remote code.