Most Azure monitoring setups suffer from a "visibility paradox": we ingest massive amounts of data, yet we struggle to find the one log that actually matters during an incident. The default "log everything" approach doesn't just inflate your bill; it creates a sea of noise that hides critical insights. If you aren't actively managing your ingestion-time data, you’re likely paying for a lot of data that will never be queried.

In this session, we’ll move from passive logging to active data management. I’ll share the exact KQL transformations I use to strip out noise before it hits disk, and how to strategically use Basic vs. Analytics logs to save on long-term storage. We’ll finish by looking at how to build meaningful Azure Workbooks that visualize this refined data, ensuring your dashboards show you actionable insights rather than just expensive clutter.

It’s time to architect a monitoring system that justifies its own invoice.