Improved README readability

Author: riferrei

README.md

@@ -1,6 +1,6 @@
 # Prioritizing Event Processing with Apache Kafka
 
-Implement event processing prioritization in [Apache Kafka](https://kafka.apache.org) is often a hard task because Kafka doesn't support broker-level reordering of messages like some messaging technologies do. This is not necessarily a limitation, since Kafka is a [distributed commit log](https://engineering.linkedin.com/distributed-systems/log-what-every-software-engineer-should-know-about-real-time-datas-unifying). With this data structure, events are immutable, and so their ordering is within partitions. But this doesn't change the fact the developers may need to implement event processing prioritization with Kafka, anyway.
+Implement event processing prioritization in [Apache Kafka](https://kafka.apache.org) is often a hard task because Kafka doesn't support broker-level reordering of messages like some messaging technologies do. This is not necessarily a limitation, since Kafka is a [distributed commit log](https://engineering.linkedin.com/distributed-systems/log-what-every-software-engineer-should-know-about-real-time-datas-unifying). With this data structure, messages are immutable, and so their ordering is within partitions. But this doesn't change the fact the developers may need to implement event processing prioritization with Kafka, anyway.
 
 This project addresses event processing prioritization via the bucket pattern. It groups partitions into simpler abstractions called buckets. Bigger buckets mean a higher priority, and smaller buckets mean less priority. The number of partitions associated with each bucket defines their size. The bucket pattern also addresses code simplicity by providing a way to do all of this without forcing developers to handle low-level code related to event partitioning and consumer assignment.