Operations | Monitoring | ITSM | DevOps | Cloud

Digital Adoption + AI: The Secret Route to Zero Tickets

Generative AI has the potential to transform workplace productivity – but do organizations know how to deliver on that promise? New research shows that employees who use generative AI tools engage with them up to ten times per day, spending over three hours per week interacting with AI at work. And yet within the same organizations, large groups of employees have never meaningfully engaged with these tools at all.

MCP and A2A: What They Are and Why They Matter for Autonomous IT

MCP and A2A are the two protocols that make agentic AI governable at enterprise scale. One controls how agents use tools, and the other controls how agents work together. AI in the enterprise is no longer confined to chat windows. It’s operating inside incident queues and automation pipelines. Increasingly, teams are using AI agents to take action: detecting incidents, executing remediations, updating tickets, coordinating across systems.

From signals to savings: Optimizing cloud costs with Grafana Assistant and MCP servers

In today's cloud-native environments, managing resource waste and optimizing costs can feel like a constant battle. Operators, along with their fearless FinOps teams, spend countless hours hunting down unused resources, deciphering complex telemetry data, and manually implementing code or configuration changes to try to reduce cloud costs. But what if you could automate the entire process, from identifying waste to implementing the fix, all based on actual production telemetry?

5 Ways You Can Improve Your Shipping Operations

No business can be truly successful if they have not optimised its shipping operations. In fact, without optimisation, this facet of your organisation can cost you valuable resources such as time and money. With that in mind, check out our suggestions on how you can improve the shopping operations in your organisation, below.

How Long Does Deep Research Take? We Timed 5 Tasks With & Without AI

How long does deep research take? That's a million dollar kind question if you've ever lost a weekend to digging through sources for a report. You already know the pain of hours of searching, reading, and synthesizing, only to wonder if you missed something crucial. We gathered experiment data comparing traditional research methods against modern AI tools across five common professional tasks. The exact time savings we measured might surprise you, and they reveal how AI is quietly redefining what it means to be a deep researcher.

Why Generic AI Fails in Ops: What Trustworthy Actually Requires

Enterprise operations reached a point where complexity outpaced human interpretation and outgrew the capabilities of generic AI. As environments became more distributed and interdependent, every incident, anomaly, and degradation produced ripple effects across systems that require context, lineage, and reasoning. Yet most AI models were not built for this reality. They were trained for general knowledge tasks, not the deeply connected operational truths that define enterprise performance.

How to Reduce MTTR with AI-Powered Runtime Diagnosis

Reducing Mean Time to Resolution (MTTR) in production systems requires understanding failure behavior in real time. While AI code agents significantly accelerated software development and deployment, incident resolution has remained constrained by incomplete pre-captured telemetry. AI SRE tools improve signal correlation, but MTTR reduction requires runtime-verified diagnosis that confirms execution behavior directly in production systems.