Operations | Monitoring | ITSM | DevOps | Cloud

The new Advanced Pipeline Editor went live for all paid plans, we launched a public Blueprints library of ready-made pipeline patterns, we reworked plan pricing and raised the Free tier to 100 GB/day, and the source and processor catalog grew with an AWS Neuron source, an AWS CloudWatch metrics source, and a full set of XML processors. None of these are flashy on their own.

Application autoscaling has existed for years. Database autoscaling has lagged behind. Today, that changes on Upsun. Managed PostgreSQL and MariaDB read replicas now autoscale, joining worker autoscaling in production since March 2026. Apps, workers, and managed databases all autoscalead replicas saturate first, connection pools max, someone getse on one platform - natively, without a third-party database engine or a Kubernetes layer to operate. Three operational headaches just disappeared.

A DevOps platform unifies the entire software delivery lifecycle. Unlike standalone tools that automate individual tasks, a DevOps platform connects CI/CD, security, governance, artifact management, infrastructure, and engineering workflows into a single software delivery system. Tool sprawl creates operational complexity as engineering organizations scale.

Every on-call engineer has lost an evening to some version of this. Something breaks; the fix is usually somewhere in the logs, and the logs are scattered everywhere: a dozen servers, a few containers, a couple of cloud services, none of them in one place. So, you SSH into one box, grep, get nothing, move to the next, and an hour later there are fifteen terminal tabs open and still no clear sequence of events. Log aggregation tools kill that scramble.

Ford's competitors had the same electric motors he did. Most just swapped out the steam engine and kept the old factory layout, a costly mistake. Ford used the new tech to rebuild the plant around the flow of the car. Knowing how much power each machine drew, he knew his cost to produce a car, and made personal automobiles affordable for all.

Many teams invest heavily in code quality, architecture and testing – yet still struggle with outages, slow response times, and unclear ownership. The reason is simple: software quality is about more than technology alone.

When you add a domain to a DNS monitor, the first question is simple: which records should it watch? Until now there were two answers, and both had a catch. Autodiscovery probes hundreds of common names — www, mail, _dmarc, the usual suspects — and it catches most of what real zones contain. But if you named a record something unusual, no wordlist in the world is going to guess it.

One of the most important realizations emerging across enterprise AI governance discussions is that most risky AI behavior is not malicious. Employees are typically trying to work faster. They are trying to summarize documents, accelerate research, draft communications, analyze spreadsheets, or automate repetitive tasks. In many cases, employees may not fully understand how AI providers handle uploaded information, what data policies apply, or where organizational compliance boundaries actually exist.