Operations | Monitoring | ITSM | DevOps | Cloud

Why Multi-Agent AI Workflows Need a Control Plane

AI is transforming how infrastructure and platform teams design, deploy, and operate systems. As organizations move from experimentation to production, a clear pattern is emerging. AI can decide what should change, but it cannot safely control how those changes are executed. This creates a gap in modern architectures. That gap is filled by a control plane. That control plane already exists in Puppet Enterprise Advanced.

How one PM scaled customer discovery with AI

Customer interviews are one of the most powerful ways to build better products — but they’re also time-consuming. In this video, Avinoam “Avi” Zelenko, Principal Product Manager at Atlassian, shares how he transformed the way he runs customer interviews using AI automation and Rovo agents. What used to take hours of coordination, note-taking, and manual summaries now happens automatically. By stitching together the Teamwork Collection and Slack, Avi built a workflow that captures conversations, summarizes insights, and shares them across teams in real time.

Why AI observability is a critical ITOps priority

AI Observability is a Critical Priority for ITOps Teams See how LogicMonitor helps ITOps teams monitor AI workloads, reduce blind spots, and move toward Autonomous IT. Schedule a meeting AI has shifted from experimental pilots to everyday business operations. Customers are interacting with AI-powered applications. Engineering teams are building with LLMs, GPUs, APIs, and automation at a much faster pace. That adds to the visibility strain on already overburdened ITOps teams.

Scout MCP Server: Example Prompts, Use Cases, and What's New

The Scout MCP server connects your AI assistant directly to your Scout Monitoring data. Instead of switching between your editor, Scout, and a chat window, your assistant can pull traces, errors, N+1 insights, and endpoint metrics on its own and use that context to suggest or make fixes right in your codebase. This covers how to connect it, what to ask it, how other teams are using it, and what we shipped recently.

From Telemetry to Shared Understanding: Why Operations Teams Need Better Visual Incident Notes

Modern operations teams are rarely short on data. A production incident can generate thousands of log lines, multiple dashboards, traces across several services, deployment events, alerts, chat messages, and customer reports. The harder problem is turning that data into shared understanding quickly enough for people to act.

Best AI Video Generators in 2026

The AI video space has matured into a handful of serious contenders, each with distinct strengths. If you're trying to pick one - or understand how they stack up - this guide ranks and compares the seven best AI video generators of 2026, with clear guidance on which fits which use case. No single tool wins everything, so the right choice depends on what you're making. Throughout, we'll reference Grok Imagine as a strong all-rounder you can test free, alongside the other major options.

Why Cloud Spending Keeps Rising Across the Financial Sector

Financial institutions have spent years modernizing their technology infrastructure, but cloud adoption continues to accelerate. From global banks to fintech startups, organizations across the financial sector are increasing their cloud budgets as they look for greater flexibility, efficiency, and access to advanced technologies.

Analysing Claude Code telemetry with SquaredUp - diving deeper

In our previous article we looked at the basics of: In this article, we are going to take a deeper dive into some of the complexities of configuration as well as some of the nuances of analysing Claude telemetry. Before we dive into the code, let us just remind ourselves that our telemetry pipeline looks like this: That is, we are emitting Claude Code telemetry to an OpenTelemetry Collector. The telemetry is then exported to an Application Insights endpoint and stored in Log Analytics tables.

Deep AI Investigation for ITOps: What It Is and Why It Matters

Investigation is the most time-consuming and cognitively demanding phase of incident response, and it’s the phase least served by existing tooling. Modern ITOps teams have spent years investing in better detection and alerting. The tools are faster, the dashboards are richer, and anomaly detection keeps improving.