Operations | Monitoring | ITSM | DevOps | Cloud

The real reason your AI initiatives are failing

AI has made it faster and easier to change a codebase than ever before. But in a system as complex and interdependent as modern software delivery, writing code has never been the biggest challenge. For most teams, the real constraint is getting that code safely into production. So while AI assistants and autonomous coding agents have dramatically accelerated the pace of change, for many organizations those changes are piling up against bottlenecks that were already slowing them down.

Modern E2E Testing with Playwright and AI

Pair Playwright with LLMs to plan, generate, refactor, and monitor end-to-end tests, without shipping hallucinations. This webinar showcases practical workflow: ground models with fresh docs, driving the browser via Playwright MCP, auto-fixing failing tests, refactoring to POMs, add API checks, and reusing the same suite for synthetic monitoring in Checkly. Chapters.

Why AIOps Needs Agentic AI

The AIOps and observability market has always been fragmented—and it’s not by accident. Different domain-specific tools, multiple data types, and reliance on supervised learning created complexity and silos. Now, a new approach is emerging. By placing LLMs at the center of decision-making, Agentic AI has the potential to unify this fragmented space and truly transform AIOps. This clip explains the root of fragmentation—and why the agentic approach offers a way forward. For a deeper dive, visit our website to see how the Fabrix.ai platform is architected to solve the real-time data challenge in AIOps.

Azure Integration Services and AI

Join Mick and Sebastian as they dive deep into the world of enterprise integration, exploring the evolution from BizTalk Server to Azure Integration Services and the growing impact of AI on integration projects. Discover how integration is crucial for breaking down data silos to power AI models, the importance of data privacy and compliance especially in the EU and the challenges developers face in keeping up with rapid technological change.

Scaling AI the right way in the enterprise

AI isn’t the future—it’s already here, shaping inboxes, dashboards, and project roadmaps. Yet, despite the hype, most enterprises struggle to scale AI in ways that deliver real impact. In this episode of the ManageEngine Insights Podcast, host Jeremy Spence sits down with Michael Barnes, a trusted advisor to APAC C-level leaders, to uncover why so many AI initiatives stall after the pilot stage.

Automate or Elevate? 5 Steps to Build an AI-Powered Incident Playbook

Modern development tools, CI/CD infrastructure, and AI have accelerated the pace at which companies release software. This speed supports innovation, but it also increases complexity and the chance of something breaking in ways that aren’t immediately obvious. Teams now deal with more operational data, complex failure patterns, and systems where a small configuration change can ripple across dozens of microservices.

How to Read the City Without Leaving Your Screen

Understanding how a city operates has never required full immersion on foot or hours of people-watching from a bench outside a train station. These days, real-time data and digital platforms do most of the legwork. Anyone can read the flow of a city by observing its online signals, which move as rapidly as traffic during rush hour. Location-based apps, social feeds, open data portals, and maps with live overlays create an ongoing narrative of urban behavior. Individuals can use this information to understand how people move, where they gather, and what draws their attention at particular times.

LLM app Observability: Opentelemetry as a standard

LLM observability is broken There are too many new libraries floating around, but they don't follow accurately the OpenTelemetry conventions. OTel isn’t perfect for LLMs yet—but extending a proven standard beats inventing another one. Why not use the same standard (OTel) which works so well for rest of the apps, and just work on top of it? This is what I was ranting with Pranav Raj S, co-founder at Chatwoot and we thought there must be other folks facing similar issues.

From Productivity to Performance: SQL Prompt's Next Chapter with AI

For nearly 20 years, SQL Prompt has been a trusted companion for database professionals, helping them write cleaner code, reduce errors, and save time. From its earliest days, the focus has been on productivity while removing the repetitive, mundane tasks that slow people down. It’s been about building the reliability and performance that developers and DBAs depend on every day and that story doesn’t stop here.

Datadog in the Era of AI

AI is changing everything. At Datadog, our approach is two-fold: empower you with complete observability across your entire stack, including AI as you incorporate it, and harness emergent technologies to make Datadog even more powerful. Join VP of Product Michael Whetten to see how Datadog is accomplishing these two approaches. He'll share the latest feature updates and new products designed to help you thrive in an AI-powered world. Plus, get a look at our long-term vision for the future of AI and its impact on your work.