Operations | Monitoring | ITSM | DevOps | Cloud

Predict GPU hardware failures 48–72 hours in advance. A guide to the five rate-based signals — ECC error trends, XID events, thermal ramp, row remap exhaustion, PCIe downtraining — and how to combine them into a composite health score.

Trust in a cloud provider used to come down to two metrics: uptime and cost. If services stayed online and pricing looked competitive, that was often enough. That is no longer the case. Modern development teams expect far more from their infrastructure. Speed, usability, transparency, and flexibility now shape how developers evaluate cloud platforms. A provider may meet uptime guarantees and still frustrate teams with slow provisioning, unclear billing, or rigid tooling.

Every week there is another model drop, another agent framework, and another workflow tweak you are supposed to evaluate. Meanwhile, the largest companies, the ones operating at the highest scale and leaning hardest on AI, are also the ones making headlines for reliability strain: capacity limits, outages, and services that buckle under load.

We are excited to announce a significant update to our ODBC Drivers product line. This release delivers broader compatibility across modern data platforms, improved integration with third-party tools, and extended support for advanced data types and authentication methods.

Last month I was making a change to sx, our CLI. I updated a core flow, adding external catalogs as a source for sx add. Small change. Then came the testing. I knew I was messing with a core flow and wanted to be sure I hadn't broken anything. I spent about forty-five minutes setting up an isolated environment. Spinning up Docker. Fighting with tmux. Getting a clean install state I could run through the TUI a few times. Forty-five minutes of my afternoon that produced zero code. I complained in Slack.

Platform Engineering leaders are caught between two competing imperatives. You’re under pressure to flatten cloud spend but your team is still provisioning defensively because nobody wants to be the person who causes a production incident. You try to optimize, but six months later, when someone pulls a report, nothing has changed.