Operations | Monitoring | ITSM | DevOps | Cloud

Summary Downsampling turns high-frequency time series data into lower-resolution summaries. In InfluxDB 3, you can calculate those summaries by querying with SQL or materialize them on a schedule with the Python Processing Engine. Table of Contents This tutorial demonstrates both approaches using the InfluxDB 3 Processing Engine’s built-in bird tracking simulator plugin. You will generate telemetry, aggregate it into 10-second windows, and validate the result with SQL.

Power Usage Effectiveness has long been used as a metric to calculate data center efficiency. For roughly the last two decades, this popular metric has been used to manage data centers throughout the world. In Singapore, arguably one of the leading data center hubs in Southeast Asia with 1.4 gigawatts capacity, future PUE limits are likely to force operators of both new and existing data centers to modify their facilities and how they are managed.

With AI agents and AI-generated code becoming the norm in modern enterprise software, backend systems are evolving faster than ever. And it’s leaving most operations teams with an impossible choice: burn out senior talent on repetitive firefighting, or hand production over to untrained AI agents. With disruptions costing enterprises an average of $300,000 per hour, manual firefighting isn’t an option.

Say you get a support escalation about a page in the app that won’t load. But when you pull up your synthetic checks, they're all green: 100% uptime, probes are passing. Something's not adding up, but which one do you trust? If you’ve run Grafana Cloud Synthetic Monitoring, you’ve been on both sides of this. Sometimes it's the ticket: real users hit a wall on the path but your checks pass cleanly. Other times, it’s the inverse.

On the product team here at Grafana Labs, we consider AI agents our users, too. That’s why we set out to test how well agents can debug incidents across the full stack, and how much better they perform with Grafana Cloud’s Knowledge Graph vs. using raw telemetry alone. Our early results are promising. In one real incident we replayed 16 times each way, an agent with Knowledge Graph context found the correct root cause 15 times, compared with just once using raw telemetry alone.

At Nexthink’s DEX Day in Raleigh, NC, IT leaders shared how they’re tackling vulnerability response, compliance, and the growing expectations on end-user computing (EUC) teams.

Managing monitors has meant one of two things: the dashboard, or writing your own API calls. There is now a third. The official UptimeRobot CLI is live on npm, and it drives every monitor, incident, and status page in your account from the shell you already have open. It is free, open source under Apache 2.0, and works on every plan including the free one.