Fabric RTI 101: Cost and Performance Optimization

In Microsoft Fabric, cost and performance optimization comes from being selective about what you process in real time and how you manage it afterward.

Streaming everything is rarely necessary — and can quickly become expensive. Instead, focus on hot, time-critical data that genuinely requires immediate insight or action. Examples include operational metrics, device telemetry, or fraud-detection signals. Less urgent data can flow through scheduled or downstream processes.

You can also reduce load by pre-aggregating or filtering events upstream. For example, summarizing counts or averages before sending data into an Eventstream or KQL database can dramatically lower both volume and compute cost without sacrificing analytic value.

When absolute precision isn’t required, sampling is another useful technique. Rather than processing every event, you can analyze representative subsets — ideal for dashboards, exploratory analysis, or trend monitoring.

While older architectures talk about hot, warm, and cold storage tiers, in Fabric the same idea is handled logically rather than physically.

The hot layer refers to actively streamed data in components like Eventstreams and KQL Databases, where low latency is critical.

The warm layer might include data persisted in Lakehouses or Warehouses for near-real-time reporting.

The cold layer refers to long-term historical data, typically retained in OneLake or exported to external archival storage for cost efficiency.

Managing these layers conceptually allows you to balance immediacy, performance, and cost without manually adjusting storage tiers.

The most effective optimization strategy is right-sizing — scaling compute to match workload patterns and applying sensible retention limits. The goal isn’t to make everything fast, but to make everything fast enough at the right price point.

Learn more about Fabric RTI

If you really want to learn about RTI right now, we have an online on-demand course that you can enrol in, right now. You’ll find it at Mastering Microsoft Fabric Real-Time Intelligence

2026-08-23