Operations | Monitoring | ITSM | DevOps | Cloud

Data locality: AI models often rely on large datasets. Locating compute close to the data reduces transfer times and improves training performance. Latency sensitivity: Real-time AI applications, like recommendation systems or edge analytics, depend on low-latency environments. This can be more easily tuned in private or hybrid setups. Hardware specialization: Some AI workloads benefit from custom hardware like GPUs or TPUs. Private cloud allows more control over this, while public cloud offers broader access but less customization.

‎‎Subscribe. Fuel your curiosity. In this episode, we break down what we’ve learned from teams running AI at scale, and why on-premises infrastructure is making a strong comeback. We’re seeing a shift: performance, cost control, data sovereignty, and platform flexibility are driving conversations about on-prem strategies for AI. No one-size-fits-all answers, but if you’re building or scaling AI, this might help you think a few steps ahead.

In the July edition of the Kubernetes Monitoring Helm chart office hours, we discuss the version 3.2 release as well as the plan for upcoming features. Finally, we end with a packed Q&A full of great questions.

Get alerted on frontend issues the moment they happen — no setup headaches required. In this short demo, Elliot Kirk from Grafana Labs introduces out-of-the-box alerting for frontend observability. Whether you're tracking error counts or web vitals, this new feature makes it easy to stay ahead of performance issues. With just a few clicks, you can: Enable prebuilt alerts for your apps Visualize and edit alerts directly in the UI Customize thresholds and durations Set up notifications and stay in the loop Launch alerting with every new app setup.

Redgate Flyway extends DevOps practices to your databases to speed up software delivery while keeping business-critical data safe. From version control to continuous delivery, Redgate Flyway helps individuals, teams, and enterprises build on application delivery processes to automate database development and deployments.

In this episode of Now That’s IT, Aaron Betts shares his remarkable journey—from launching his first MSP in 2005 and losing it all during the financial crisis, to taking a corporate detour, burning out, and ultimately returning to lead Intelesys as President. Aaron opens up about the hard-earned lessons of entrepreneurship, the shift from break/fix to managed services, and how a life-altering health scare reshaped his leadership style. He shares how he's rebuilding company culture, redefining success, and guiding his MSP toward a $10M vision—all while empowering his team to think bigger.