Update event-driven-scaling.md

Author: ggailey777

articles/azure-functions/event-driven-scaling.md

@@ -49,7 +49,7 @@ Scaling can vary based on several factors, and apps scale differently based on t
 * **New instance rate:** For HTTP triggers, new instances are allocated, at most, once per second. For non-HTTP triggers, new instances are allocated, at most, once every 30 seconds. Scaling is faster when running in a [Premium plan](functions-premium-plan.md).
 * **Target-based scaling:** Target-based scaling provides a fast and intuitive scaling model for customers and is currently supported for Service Bus queues and topics, Storage queues, Event Hubs, Apache Kafka, and Azure Cosmos DB extensions. Make sure to review [target-based scaling](./functions-target-based-scaling.md) to understand their scaling behavior.
 * **Per-function scaling:** With some notable exceptions, functions running in the Flex Consumption plan scale on independent instances. The exceptions include HTTP triggers and Blob storage (Event Grid) triggers. Each of these trigger types scale together as a group on the same instances. Likewise, all Durable Functions triggers also share instances and scale together. For more information, see [per-function scaling](#per-function-scaling).
-* **Maximum monitored triggers:** Currently, the scale controller can only monitor up to 100 triggers to making scaling decisions. When your app has more than 100 event-based triggers, scale decisions are made based on only the first 100 triggers that run. For more information, see [Best practices and patterns for scalable apps](#best-practices-and-patterns-for-scalable-apps).  
+* **Maximum monitored triggers:** Currently, the scale controller can only monitor up to 100 triggers to making scaling decisions. When your app has more than 100 event-based triggers, scale decisions are made based on only the first 100 triggers that execute. For more information, see [Best practices and patterns for scalable apps](#best-practices-and-patterns-for-scalable-apps).  
 
 ## Limit scale-out