Operations | Monitoring | ITSM | DevOps | Cloud

Building AI applications often means juggling multiple models, scattered datasets, and version chaos across local systems. But what if you could bring it all together — securely and efficiently — in one place? In this walkthrough, Shibam Dhar, DevRel Engineer at Harness, demonstrates how Harness Artifact Registry makes it easy to manage and govern your AI/ML assets — from models and datasets to prompts and agents — with built-in support like Hugging Face and generic registry types.

Slow computer? Watch RITA diagnose and fix it in real time. Zero Ticket IT.

Spec-driven development with AI coding agents could change how you build software. In this GitKon 2025 talk, Erik Hanchett, Senior Developer Advocate at AWS, breaks down why AI coding assistants perform dramatically better when they start with structured specifications instead of raw prompts. If you've been vibe coding your way through complex features and wondering why your AI keeps going off the rails, this is the video for you.

Millions of metrics. Zero clarity. That’s the reality many IT teams are facing today. As environments grow more complex, telemetry explodes. Millions of records generated every hour. Dozens of specialized tools for network, storage, Kubernetes, cloud, AI workloads. Each tool is good at its domain. But none of them answers the real question: Where should I focus right now? Fragmented visibility creates predictable failure modes.