Operations | Monitoring | ITSM | DevOps | Cloud

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 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.

A missed page at 2 a.m. can turn a minor service degradation into an hours-long outage, an SLA breach, and a costly customer-trust problem. For IT operations, SRE, and DevOps teams, the tool that decides who gets alerted, how, and when someone stops the escalation is a critical piece of infrastructure.

New research from BigPanda reveals what enterprises spend on outsourced IT operations support, what they get in return, and why leaders are ready to rethink the model. Enterprises spend an average of $5.4 million a year on outsourced IT operations support. That’s a substantial investment. It should produce reliable frontline operations: incidents detected, understood, routed, and resolved with the speed and accuracy the business expects. The research shows a different picture.

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.

Earlier this year, we introduced Ivanti Innovators Hub to bring together support, knowledge and community into a more unified experience. That launch established a strong foundation for a more effortless and predictable experience. Now, we're building on it with new enhancements designed to make the Hub more personalized, connected and relevant, with integrated learning opportunities, stronger community engagement and more tailored experiences.

ITSM best practices are standardized ways to design, operate, measure, and improve IT services. For enterprise teams, the most important practices are clear service ownership, consistent incident and problem management, risk-based change controls, trustworthy configuration data, standardized request fulfillment, outcome-based metrics, governed automation, and continual improvement.

This guide shows platform engineers how to evolve beyond basic service catalogs into golden paths that drive real developer adoption. Learn proven patterns for building Internal Developer Platforms that deliver measurable productivity gains through streamlined workflows, self-service capabilities, and developer-friendly abstractions. Your internal developer platform golden paths launched three months ago. Adoption sits at 11 percent. The service catalog has 247 entries, half of them outdated.

Automated incident response means the platform captures the timeline, key events, and decisions as an incident unfolds, instead of a human reconstructing them afterward. Runbooks fire the instant an incident opens: channel created, bridge spun up, Jira and ServiceNow tickets filed, all within seconds. The AI Scribe Agent joins the video bridge on its own and listens to chat, pulling key events out of both the talking and the typing.

Table of Contents Kubernetes resource optimization appears to be a single problem, but the platforms that address it disagree on almost every design decision, starting with how they analyze workload demands. Some set CPU and memory requests from live signals, while others learn a workload’s historical pattern and provision ahead of it.