Apply suggestions from code review

Author: Jak-MS

articles/event-hubs/event-processor-balance-partition-load.md

@@ -25,7 +25,7 @@ Each sensor pushes data to an event hub. The event hub is configured with 16 par
 
 When you design a consumer in a distributed environment, the scenario must handle the following requirements:
 
-1. **Scale:** Create multiple consumers, with each consumer taking ownership of reading from a few Event Hub partitions.
+1. **Scale:** Create multiple consumers, with each consumer taking ownership of reading from a few Event Hubs partitions.
 2. **Load balance:** Increase or reduce the consumers dynamically. For example, when a new sensor type (for example, a carbon monoxide detector) is added to each home, the number of events increases. In that case, the operator (a human) increases the number of consumer instances. Then, the pool of consumers can rebalance the number of partitions they own, to share the load with the newly added consumers.
 3. **Seamless resume on failures:** If a consumer (**consumer A**) fails (for example, the virtual machine hosting the consumer suddenly crashes), then other consumers can pick up the partitions owned by **consumer A** and continue. Also, the continuation point, called a *checkpoint* or *offset*, should be at the exact point at which **consumer A** failed, or slightly before that.
 4. **Consume events:** While the previous three points deal with the management of the consumer, there must be code to consume events and do something useful with it. For example, aggregate it and upload it to blob storage.