diff --git a/README.md b/README.md
index d0e21de..f8bb883 100644
--- a/README.md
+++ b/README.md
@@ -136,7 +136,7 @@ An updated and curated list of selected readings to illustrate High Scalability,
 	* [Logging and Aggregation at Quora](https://engineering.quora.com/Logging-and-Aggregation-at-Quora)
 	* [BookKeeper: Distributed Log Storage at Yahoo](https://yahooeng.tumblr.com/post/109908973316/bookkeeper-yahoos-distributed-log-storage-is)
 	* [LogDevice: Distributed Data Store for Logs at Facebook](https://code.facebook.com/posts/357056558062811/logdevice-a-distributed-data-store-for-logs/)
-* [Distributed Messaging](https://arxiv.org/pdf/1704.00411.pdf)
+* [Distributed Messaging and Event Streaming](https://arxiv.org/pdf/1704.00411.pdf)
 	* [When to use RabbitMQ or Kafka](https://content.pivotal.io/blog/understanding-when-to-use-rabbitmq-or-apache-kafka)
 	* [Should You Put Several Event Types in the Same Kafka Topic? - Martin Kleppmann](https://www.confluent.io/blog/put-several-event-types-kafka-topic/)
 	* [Kafka at Scale at Linkedin](https://engineering.linkedin.com/kafka/running-kafka-scale)
@@ -146,6 +146,10 @@ An updated and curated list of selected readings to illustrate High Scalability,
 	* [Audit Kafka End-to-End at Uber (count each message exactly once, audit a message across tiers)](https://eng.uber.com/chaperone/)
 	* [Kafka for PaaS at Rakuten](https://techblog.rakuten.co.jp/2016/01/28/rakuten-paas-kafka/)
 	* [Publishing with Kafka at The New York Times](https://open.nytimes.com/publishing-with-apache-kafka-at-the-new-york-times-7f0e3b7d2077)
+	* [Kafka Streams on Heroku](https://blog.heroku.com/kafka-streams-on-heroku)
+	* [Kafka in Platform Events Architecture at Salesforce](https://engineering.salesforce.com/how-apache-kafka-inspired-our-platform-events-architecture-2f351fe4cf63)		
+	* [Bullet: Forward-Looking Query Engine for Streaming Data at Yahoo](https://yahooeng.tumblr.com/post/161855616651/open-sourcing-bullet-yahoos-forward-looking)
+	* [Benchmarking Streaming Computation Engines at Yahoo](https://yahooeng.tumblr.com/post/135321837876/benchmarking-streaming-computation-engines-at)
 	* [Deduplication Techniques](https://en.wikipedia.org/wiki/Data_deduplication)
 		* [Exactly-once Semantics are Possible: Here’s How Kafka Does it](https://www.confluent.io/blog/exactly-once-semantics-are-possible-heres-how-apache-kafka-does-it/)
 		* [Real-time Deduping at Scale with Kafka-based Pipleline at Tapjoy](http://eng.tapjoy.com/blog-list/real-time-deduping-at-scale)
@@ -325,11 +329,6 @@ An updated and curated list of selected readings to illustrate High Scalability,
 	* [Domain Events](https://martinfowler.com/eaaDev/DomainEvent.html)
 		* [Domain Events: Simple and Reliable Solution](http://enterprisecraftsmanship.com/2017/10/03/domain-events-simple-and-reliable-solution/)
 		* [Domain-Driven Design in Organizing Monolith Before Breaking it into Services at Weebly](https://medium.com/weebly-engineering/how-to-organize-your-monolith-before-breaking-it-into-services-69cbdb9248b0)
-	* [Event Stream Processing](https://www.sas.com/en_us/insights/articles/big-data/3-things-about-event-stream-processing.html)
-		* [Kafka Streams on Heroku](https://blog.heroku.com/kafka-streams-on-heroku)
-		* [Kafka in Platform Events Architecture at Salesforce](https://engineering.salesforce.com/how-apache-kafka-inspired-our-platform-events-architecture-2f351fe4cf63)		
-		* [Bullet: Forward-Looking Query Engine for Streaming Data at Yahoo](https://yahooeng.tumblr.com/post/161855616651/open-sourcing-bullet-yahoos-forward-looking)
-		* [Benchmarking Streaming Computation Engines at Yahoo](https://yahooeng.tumblr.com/post/135321837876/benchmarking-streaming-computation-engines-at)
 	* [Event Sourcing](https://martinfowler.com/eaaDev/EventSourcing.html)
 		* [Event Sourced Architectures for High Availability](https://www.infoq.com/presentations/Event-Sourced-Architectures-for-High-Availability)
 		* [Event Sourcing and Stream Processing at Scale](https://martin.kleppmann.com/2016/01/29/event-sourcing-stream-processing-at-ddd-europe.html)