Operations | Monitoring | ITSM | DevOps | Cloud

A SaaS team once spotted their first breach not in a SIEM dashboard, but in their AWS bill. Their compute costs spiked by 400% overnight. Turns out, an attacker had spun up dozens of high-powered instances for crypto mining. Logs eventually confirmed the intrusion, but the cost anomaly was the first signal that something was wrong. This incident isn’t unusual. Cloud costs often reflect consumption, but they can also reflect compromise.

It’s 3 AM. API latency just spiked from 200ms to 2s. Alerts are firing, and users are frustrated. You SSH into the first server: top, free -h, iostat — nothing unusual. On to the next host. And the next. That’s how most of us learned to debug. The tools worked, and we got good at using them. But as infrastructure became distributed and dynamic, this approach started to break down. Modern monitoring needs more than SSH and top. It needs unified telemetry.

<span data-mce-type="bookmark" style="display: inline-block; width: 0px; overflow: hidden; line-height: 0;" class="mce_SELRES_start"></span> Andrew Hillier sits down with Dan Ciruli, who leads the cloud native product management team at Nutanix.

NTILE in SQL transforms raw lists into structured distributions before they reach a dashboard. By pushing distribution logic upstream, it divides ordered rows at the query level, so the insights in Power BI, Tableau, or Excel are accurate, not just polished visuals. This guide explores its syntax, practical examples, and comparisons with other ranking functions. It also highlights how database IDEs bring NTILE insights directly into analysis and reporting workflows. Table of contents.

As a developer, you often face the challenge of retrieving information from multiple sources with different structures. What if you could create a single interface that automatically routes queries to the right data source? Imagine your application needing to answer both “What’s the population of California?” and “What are popular attractions in Hawaii?”.