Operations | Monitoring | ITSM | DevOps | Cloud

We recently sat down with founder and principal consultant at recultiv8, Coenraad Pretorius, who drew on his years of data engineering experience in the manufacturing and energy sectors to share key industrial IoT insights.

As enterprises scale, teams often find it harder to identify user-reported issues. Software-defined wide area networks (SD-WANs) can make it easier to add branch offices, but they can also make it more challenging to distinguish connectivity degradation from changes in application behavior. FortiManager provides a centralized control plane for Fortinet Secure SD-WAN and reduces operational complexity.

In a recent technical evaluation by Journal du Net (JDN), Upsun (formerly Platform.sh) was recognized for its ability to "pull ahead" (tire son épingle du jeu) in a fiercely competitive market dominated by cloud giants and specialized pure players. While hyperscalers offer raw power, Upsun’s strategic fusion of enterprise reliability and AI-ready agility has redefined expectations for modern PaaS.

The decision to migrate a production application is rarely about the destination. It is about the friction of the journey. For most engineering leaders, the word "migration" is a synonym for "refactor." The industry has conditioned us to assume that moving to a modern cloud platform requires throwing away years of stable configuration, learning a new proprietary DSL, and rewriting core application logic to fit a specific container or serverless model.

In this blog post, we’ll explain what alert management software does, where it’s used, and which features you should look for when choosing the right solution.

Incident alerting is a critical part of modern operations, yet it’s often misunderstood or reduced to “sending notifications.” In reality, it is about ensuring that the right people are informed at the right time – and that incidents move from detection to action without confusion or delay. This page explains why fast, reliable alerting matters, where it fits between monitoring and incident response, and what best practices look like.

We've all heard from an engineering leader about the exact moment they realized their architecture had gotten too complex. It usually happens when they look at a service map and realize it looks like a box of tangled Christmas lights. This cognitive overload is exactly what Steve Evans, the former SVP of engineering at Chegg, reflected on in a recent post on LinkedIn. He argued that microservices were a trillion dollar mistake because we often over-build for future problems that never actually arrive.

Last week, Heroku announced it is transitioning to a "sustaining engineering model." In plain English: no new features, no new enterprise contracts for new customers, and Salesforce is redirecting its investment elsewhere. The platform will be maintained for security and stability, but that's it. If you've been in this industry long enough, you know what "sustaining mode" means.

I've been in this industry since before the word "PaaS" existed. I founded Cloud 66 in 2012 — the same year Heroku was peaking, dotCloud was pivoting to become Docker, and the idea of "just git push and forget about servers" felt like the future. It was the future. Partly. The deployment experience was revolutionary. The business model wasn't. Last week, Heroku announced its transition to "sustaining mode" — no new features, no new enterprise contracts.

According to our new report, FinOps in the AI Era: A Critical Recalibration, 40% of companies now spend $10M or more annually on AI. Most can’t tell you if it’s working. That’s not a budgeting problem. It’s a systems problem. And Donella Meadows wrote the playbook for understanding it.