Operations | Monitoring | ITSM | DevOps | Cloud

The Rise of Intelligence Services: Turning Data into the Next Frontier of IT Value

Once upon a time, “managed services” meant uptime. If the servers stayed green, the provider was a hero. But in 2026, that model is officially outdated. Service quality is table stakes. What matters now is service intelligence—the ability to learn, automate, and improve from every action the IT organization takes. Think about it: your service desk logs hundreds of tickets a day. Each one contains clues about process gaps, recurring incidents, and improvement opportunities.

Resolve's Agents of IT podcast - Ep. 9 - Sean and Ari's Hot Takes 5 #aiautomation #itautomation

In this episode of Agents of IT, Sean Heuer, Resolve CCO, and Ari Stowe, Resolve COO, look back on 2025 and share their unfiltered hot takes on what really defined the year in IT. Yes, AI dominated every keynote and conference slide. But they dig deeper into what actually changed inside organizations. As more departments leaned on technology in new ways, IT teams faced a sharp increase in complexity, tooling sprawl, and operational pressure. The conversation explores how this shift reshaped IT’s role, stretched existing models, and set the stage for what comes next.

Shorten your 'inner loop' as a new hire and get past imposter syndrome with Grafana Assistant

Let's talk about being new. Four months ago, I joined Grafana Labs as a senior solutions engineer. It wasn’t just a new company, it was a new industry. I came from the visual workspace provider Miro, where I was comfortable doing discovery and talking about visual collaboration and innovation. But stepping into observability? I was in the deep end. And let me tell you, the imposter syndrome was real. Everyone around me was fluent in this language of metrics, logs, and traces.

AI-Assisted Communication Across Teams

Effective communication is essential for IT operations. In Alloy Navigator, everything happens in one place, directly within tickets and workflows, keeping everyone informed and helping teams get things done faster. AI writing assistance makes messages clear, professional, and actionable. All communication in one place Faster ticket resolution Clear, professional messages with AI assistance Reduced misunderstandings and errors Teams stay aligned and informed.

How to Send Critical Freshservice Tickets to On-Call Staff Instantly (OnPage Integration)

This video demonstrates how the OnPage + Freshservice integration helps IT and support teams respond faster to urgent incidents and critical tickets—without changing their existing Freshservice workflows. Freshservice is often the system of record for incidents and service requests, but dashboards and email alerts aren’t always reliable when something requires immediate, human acknowledgment, especially after hours. That’s where OnPage comes in.

Harness Dynamic Pipelines: Complete Adaptability, Rock Solid Governance

Harness Dynamic Pipelines offers an option to create pipelines, or pipeline stages, at runtime For a long time, CI/CD has been “configuration as code.” You define a pipeline, commit the YAML, sync it to your CI/CD platform, and run it. That pattern works really well for workflows that are mostly stable. But what happens when the workflow can’t be stable? In all of those cases, forcing teams to pre-save a pipeline definition, either in the UI or in a repo, turns into a bottleneck.

The Rise of AI Agents and the Reinvention of Kubernetes: Ratan Tipirneni's 2026 Outlook

Prediction: The next evolution of Kubernetes is not about scale alone, but about intelligence, autonomy, and governance. As part of the article ‘AI and Enterprise Technology Predictions from Industry Experts for 2026′, published by Solutions Review, Ratan Tipirneni, CEO of Tigera, shares his perspective on how AI and cloud-native technologies are shaping the future of Kubernetes.

Zero code tracing: Kubernetes observability with Logz.io and eBPF

Distributed tracing is a core tool for operating modern microservices platforms. For SREs and DevOps teams, it is often the fastest way to understand latency issues, service dependencies, and unexpected failure modes. But achieving comprehensive tracing coverage is resource-intensive and time-consuming. It usually requires application changes, language-specific instrumentation, agent lifecycle management, and ongoing coordination with development teams.