Operations | Monitoring | ITSM | DevOps | Cloud

Rich Communication Services (RCS) is an advanced messaging protocol designed to replace traditional SMS. Supported by most modern Android smartphones and, starting with iOS 18, also iPhones, RCS offers a significantly richer messaging experience. It brings features like: RCS elevates the way organizations communicate with users by aligning with the capabilities expected from today’s messaging platforms.

Every IT decision-maker faces a common challenge: balancing operational efficiency with cost control. While software solutions help streamline operations and drive efficiency, they can introduce redundancies into your system. These redundancies strengthen availability through backup systems but often complicate data management, leading to inconsistencies and potential outages. This is where hardware solutions like fabric interconnects prove invaluable.

The enterprise artifact management market - which has belonged for a while to JFrog and Sonatype - is now truly up for grabs. Cloudsmith was built on the core principle that cloud-native architecture matters. So does simplicity in design and workflow. Partnerships matter, too. We’ve built a comprehensive platform that controls and secures every artifact as it’s built, scanned, signed, stored, and shipped across the software supply chain.

Most IT leaders already understand that AI is the future of operations, but too many are still treating it like it’s so far off. The irony? Waiting is exactly what’s costing them the most. While businesses obsess over budget cuts, resource constraints, and service quality, one truth remains: delays in adopting AI for IT operations are compounding operational inefficiencies, inflating labor costs, and stalling digital progress. AI isn’t just about innovation; it’s about scale.

As digital operations grow increasingly more complex, resilience is no longer optional, it’s essential. The next major outage isn’t a question of if, but when. And when it hits, the gap between true enterprise platforms and brittle point tools will become impossible to ignore.

Looking for the best on-call scheduling software for your team? Or maybe you’re exploring alternatives to your current tool? Signing up for different on-call tools and testing them all takes weeks. That’s a lot of time you probably don’t have, especially when you need reliable on-call coverage now. That’s why I did the heavy lifting for you. I signed up for and tested the 5 popular on-call scheduling tools in the market: Spike, PagerDuty, Incident.io, Splunk Oncall, and OpsGenie.

- Alvin Toffler History offers us a powerful lens for the present. The Second Industrial Revolution didn't just make factories faster; the advent of electricity and the assembly line fundamentally reinvented how societies were organized. Manual labor was augmented, displacing millions from agriculture while simultaneously creating entirely new classes of work in manufacturing and engineering. Productivity soared, not because people worked harder, but because the very definition of work was transformed.

On a recent episode of The Product Manager podcast, Cortex CEO Anish Dhar joined host Hannah Clark to challenge a growing narrative: that software engineering is obsolete in the age of AI. His take? Engineering isn’t disappearing, it’s maturing. At Cortex, we work with some of the most forward-thinking engineering organizations at companies like Canva and Fanatics.

Managing today's complex enterprise infrastructure presents significant challenges — from siloed data and steep learning curves to time-consuming troubleshooting. As the pace of business accelerates and infrastructure demands grow, these obstacles are increasingly difficult to overcome. That’s why we built Infra Assistant, a new AI capability in Puppet Enterprise Advanced, powered by Perforce Intelligence.

AI is changing how we build software — but debugging code still comes down to having context. One minute the model’s performance is cruising. The next, you’re hit with a KeyError from a tool you forgot existed, triggered by a model that silently timed out, and a retrieval call that returns... nothing, or 11 “Let me try this a different way" messages before failure. You’re stitching together LLM calls, agents, vector stores, and custom logic. Then hoping it holds up in prod.