Operations | Monitoring | ITSM | DevOps | Cloud

How Live Monitoring Supports Smarter Decision-Making and Safety

Here's the reality: most businesses don't fail because of small ideas; they fail because warning signs were missed until it was too late. The gap between reacting to problems and preventing them can make or break operations. That's where live monitoring comes in. By combining real-time surveillance with smart analytics, businesses can spot risks before they escalate, protect people and assets, and make informed decisions on the fly. It's not just about watching, it's about anticipating.

The next era of IT management with ManageEngine: What agentic AI will unlock

Agentic AI is generating a lot of buzz, but what does it actually do for IT teams? Join us as we showcase how the industry is evolving in the new era. What once took hours or days will soon take minutes—unlocking a new level of productivity and efficiency for IT operations. The foundation of this evolution? AI-driven contextual analytics. Agenda.

11 Must-Have AI Sales Tools for B2B Operations Management

In B2B sales, every interaction, follow-up, and decision matters. Teams are managing more leads, more data, and more tasks than ever before, and keeping everything running smoothly can feel overwhelming. AI helps revenue teams work smarter by taking over routine follow-ups, surfacing actionable insights, and giving managers the information they need to make quick, informed decisions. Below are 11 AI platforms that every B2B operations manager should be familiar with, organized by their primary focus and the benefits they bring to operations.

Architecture for the agentic era: How AI will reshape data, security, and observability

As AI agents move from copilots to autonomous systems, they’re generating and consuming data at unprecedented scale. The result is a new kind of infrastructure pressure — one that’s quietly reshaping how organizations think about data, cost, and control. Across IT, Security, and Observability, leaders are realizing a hard truth: too much data is too costly.

AI Isn't Here to Replace Your Dashboard... Yet

Non-deterministic UIs are the future and will replace your dashboards, but they’re not here yet. So until then, we’re stuck with conversational interfaces. In an effort to try and describe what I consider the future of UIs to look like, I wrote about how you (and I) have been designing dashboards wrong. The core insight was that we've been designing for static representations of data that sit on a TV in the office, when the actual use case is someone at a desk using them to debug an issue.

Five key takeaways from EDUCAUSE 2025: Adopting AI while navigating change

Having just returned from the 2025 EDUCAUSE Annual Conference in Nashville, I want to share some insights on the future of campus IT from the higher education technology leaders in attendance. Every year, this conference provides an opportunity for technology providers and higher ed professionals to connect and explore the latest innovations in higher education technology. Two themes emerged as critical priorities.

Search Telemetry Without Limits in a Multi Cloud and AI World

Cribl Search gives you one lens across all your telemetry data no matter where it lives. Instead of forcing teams to move data into one system or jump between tools, you get a familiar pipe based query experience with dashboarding and alerting built in. Storage and query processing stay separate so you decide where your data lives while your users get fast, simple access in one place.

Episode 1 - Preparing the workforce for AI | The Intelligent Enterprise

In our first podcast episode of The Intelligent Enterprise, Ricardo Costa, Senior Vice President and Chief Technology Officer at Purolator, gives us his views on how to prepare the workforce for AI. In his role as a technology "translator" connecting business strategies with tech implementations, Ricardo highlighted the importance of translating complex tech concepts into simple, understandable stories and addressing leadership challenges in preparing the workforce for AI, including upskilling and ethical considerations.

AI Observability: How to Keep LLMs, RAG, and Agents Reliable in Production

AI observability closes the gap between “something’s wrong” and “here’s what to fix.” If you run AI in production, you might have felt the whiplash. Yesterday, your LLM answered in 300 milliseconds (ms). Today p99 crawls, costs spike, and nobody’s sure if the culprit is model behavior, data freshness, or GPUs stuck at the ceiling. Dashboards light up, but they don’t tell you which issue puts customers at risk. That’s the gap AI observability closes.