Operations | Monitoring | ITSM | DevOps | Cloud

In a multi-cloud environment, each cloud platform brings its unique tech stack to record events, manage services, set up configurations, manage user access and permissions, etc. While this allows you to leverage the best-of-breed services from different cloud vendors, the complexity of this setup makes it challenging to detect and respond to anomalies across clouds in real-time.

We’re excited to announce the official release of the UptimeRobot Terraform provider, a feature that many of you have been requesting. Starting today, you can manage your UptimeRobot resources, including monitors, alerting integrations, maintenance windows, and public status pages, directly in your Terraform configuration. Let’s take a closer look.

If your container shows Status: unhealthy, Docker's health check is failing. The container is still running, but something inside, usually your app, isn’t responding as expected. This doesn’t always mean a crash. It just means Docker can’t verify the app is working. Here’s how to debug the issue and restore the container to a healthy state.

Ask banking leaders if their systems are healthy, and most respond confidently: “Yes, everything’s up.” But track a transaction closely, and reality shifts. A high-value payment retries repeatedly before settling. A KYC process silently times out, losing a verified customer. Compliance checks complete using stale data. No visible outages. Yet silent failures accumulate, becoming costly and increasingly damaging. This is downtime that dashboards never flag.

Supporting every hospital chart, scan, and bedside alert is a web of digital systems—EHRs, lab interfaces, clinical apps, networks, and connected devices—all working in sync or struggling to. When something slips, say, an Epic interface queue backs up and lab results don’t reach the attending physician on time, the consequences aren’t theoretical. That delay might mean a sepsis alert gets missed. A treatment window closes. A patient’s outcome changes.

Most monitoring tools weren't built for the AI-first world. By nature, traditional monitoring platforms force you out of your natural coding environment and trap you in clunky web interfaces, brittle configuration panels, and rigid APIs. And sadly, when monitoring providers do offer "AI features," it's usually a chatbot bolted onto their existing UI, being nothing more than a pale imitation of the AI tools you’re reading about every day on Hacker News. All this creates friction.