Operations | Monitoring | ITSM | DevOps | Cloud

Add skills to agents: Use Assistant playbooks for faster answers, investigations

Grafana Assistant is the most general-purpose tool we’ve delivered since dashboards. People use our Grafana Cloud LLM to understand unfamiliar areas of their stacks, generate dashboards and beautiful visualizations out of thin air, build queries, and support investigations.

Grafana dashboards as code: How to manage your dashboards with Git

Note: This blog post originally published in May 2025 and was updated in February 2026 to reflect that Git Sync is now available in public preview in Grafana Cloud. As your Grafana instance scales, so does the challenge of maintaining dashboards. Managing dozens—or hundreds—of dashboards through the UI alone can quickly become overwhelming. Tracking changes gets murky, dashboards multiply, and consistency suffers.

We Built an MCP Server

When I joined Kubex last year, the company was already well aware of the growing power of Large Language Models. As a company focused on intelligent resource optimization for Kubernetes, GPUs, and cloud infrastructure, generative AI didn’t feel like a threat so much as a natural extension of where the industry was heading. Kubex had already invested heavily in machine learning, but it was becoming clear that foundation models could unlock an entirely new class of capabilities for our customers.

Introducing Harness Artifact Registry | Unified. Secure. Built for the Future Artifact Management

Managing build artifacts today is harder than it should be. Fragmented tools, security blind spots, and disconnected developer workflows make it difficult to keep builds safe, consistent, and production-ready. In this walkthrough, Shibam Dhar, DevRel Engineer at Harness, shows how Harness Artifact Registry unifies artifact management across the entire software delivery lifecycle — from creation to deployment — while improving security and developer experience.

(Tech Talk) Shipping with Context Knowledge Graphs as the Backbone of AI-First Software Delivery

Knowledge graphs are essential to solving the context bottleneck in AI-First software delivery, which occurs because workflows, policies, and dependencies are siloed and invisible to AI agents. In this Tech Talk, Prateek Mittal ((Product Director of AI Core and Data Platform at Harness)) discusses the key concepts: Knowledge Graphs vs. Observability: Observability tells you "what is happening," while knowledge graphs tell you "what does that mean" by modeling structured relationships. They work together to link live signals to affected services or SLAs.

Skylar Advisor: Proactive Guidance for Modern Operations

Meet Skylar Advisor, bringing trusted and verifiable guidance to IT operations by connecting real time observability with your data and knowledge. Built AI native, it helps teams cut through alert floods, understand what matters most and why, and take the next best steps with confidence. Every recommendation is evidence backed and traceable to the exact data and sources used, so guidance is clear, explainable, and defensible when the stakes are high.

From Chaos To Clarity: How Forcepoint Scaled FinOps Across The Organization

When Anthony Leung talks about FinOps, he’s speaking from operating at real scale — not theory. As VP of Engineering Platforms and Security Research at Forcepoint, he led a transformation that cut cloud spend in half while improving availability, and built a culture where engineers own their economics.