Operations | Monitoring | ITSM | DevOps | Cloud

The latest News and Information on Monitoring for Websites, Applications, APIs, Infrastructure, and other technologies.

Monitor Proxmox Virtual Environments with ScienceLogic

See how the ScienceLogic Proxmox Virtual Environment PowerPack brings centralized visibility and operational context for Proxmox infrastructure into Skylar One. In this demo, VP of Skylar AI Douglas James walks through how the PowerPack automatically discovers Proxmox clusters, nodes, QEMU virtual machines, LXC containers, and storage resources, while building topology relationships that help teams understand how their virtual infrastructure is connected.

AI Only Your Data Can Build

Your competitive edge isn't the model; it's the data that only you have. Sonal Pardeshi, Head of AI Product at Splunk, explains why teams building on general-purpose models keep arriving at the same generic outcomes, and what changes when agents are grounded in your own machine data and your own governance. AI Toolkit and Agent Launchpad let teams build and run agents against your grounded data.

Best Synthetic Monitoring Tools [36 Analyzed, 7 Shortlisted]

Summarize with ChatGPT Summarize with Claude The best synthetic monitoring tools are Hyperping for Playwright browser checks with on-call and status pages, Checkly for Playwright-native monitoring as code, Datadog for connecting failed journeys to logs and traces, Grafana Cloud for teams using k6, Better Stack for checks inside a broader incident workflow, Site24x7 for no-code recording and broad location coverage, and Uptime.com for enterprise website monitoring.

Best Redis Monitoring Tools in 2026 [32 Analyzed]

Summarize with ChatGPT Summarize with Claude The best Redis monitoring setup usually combines more than one tool. Use Prometheus with redis_exporter and Grafana for open-source metrics and alerts, Redis Insight when you need to inspect keys and slow commands, Datadog when Redis failures need to connect to application traces and logs, and Hyperping for the outside-in availability and incident-response layer. I analyzed 32 products and shortlisted seven.

Golden Paths for AI agents: What changes when platform users aren't human?

Agents are already calling your self-service APIs, querying your catalog, and independently provisioning resources around the clock. According to Gartner’s 2026 Hype Cycle for Agentic AI report, agents have had the most aggressive adoption curve of any emerging technology. Gartner even considers agents to be a formal user persona, referring to the agent experience (AX) throughout the report.

Laravel vs. Ruby on Rails

Laravel and Ruby on Rails are both full-stack, batteries-included MVC frameworks with an ORM, a templating engine, a CLI, and a shared philosophy: going from an empty folder to a working app shouldn't take fifty decisions first. Laravel wins when your team already lives in PHP, or when you want the largest possible pool of developers, packages (code other people have already written for common tasks), and hosting options to choose from.

Telegraf Controller 1.1: Make Fleet-Wide Config Changes with a Single Edit

Summary Telegraf Controller 1.1 lets teams make fleet-wide configuration changes with a single edit using Global Constants, Configuration Groups, and Configuration Aliases. Configuration Versioning makes every change traceable, comparable, and reversible. High availability, available in Telegraf Enterprise, automatically fails over between Controller instances so agents can continue pulling configurations and reporting health if an instance goes down. Table of Contents.

Only hard work: AI's unexpected burnout risk

On this episode of Masters of Data, we dig into what happens when AI actually delivers on its promise to eliminate busywork, and explore why removing the toil doesn't feel like the win everyone expected. We make the case that repetitive tasks build the intuition, pattern recognition, and muscle memory people need to do the harder work well. Security and engineering leaders rethinking how much triage and busywork to hand off to AI will find plenty to chew on here, especially anyone staring down a task list where every single item feels like the hardest one.

The AI Acceleration Gap Is Becoming Every CIO's Biggest Leadership Challenge

Today, I’m very happy to share a new report, Bridging the AI Acceleration Gap, from Harvard Business Review Analytic Services and sponsored by Nexthink. It examines how employee-led AI adoption is reshaping the role of IT—and what technology leaders need to do next.

The Grafana AI SDK for Go: a shared foundation for building AI applications

Starting an experiment with an LLM has never been easier. Keeping a growing collection of those experiments consistent is another matter. Earlier this year, as more teams began exploring AI features here at Grafana Labs, we repeatedly encountered the same pattern: a new experiment would start, move quickly, and build its own client for whichever model provider it needed. The next experiment would do the same, with a slightly different abstraction for streaming, tools, errors, or provider configuration.