diff --git a/README.md b/README.md
index 92b2845..4248166 100644
--- a/README.md
+++ b/README.md
@@ -191,6 +191,16 @@ An updated and curated list of readings to illustrate best practices and pattern
 	* [LogDevice: Distributed Data Store for Logs at Facebook](https://code.facebook.com/posts/357056558062811/logdevice-a-distributed-data-store-for-logs/)
 	* [LogFeeder: Log Collection System at Yelp](https://engineeringblog.yelp.com/2018/03/introducing-logfeeder.html)
 	* [Collection and Analysis of Daemon Logs at Badoo](https://badoo.com/techblog/blog/2016/06/06/collection-and-analysis-of-daemon-logs-at-badoo/)
+* [Distributed Monitoring and Alerting](https://www.oreilly.com/ideas/monitoring-distributed-systems)
+    * [Alibaba Monitoring System](https://www.usenix.org/conference/srecon18asia/presentation/xinchi)
+	* [Smart Monitoring System for Anomaly Detection on Business Trends at Alibaba](https://www.usenix.org/conference/srecon17asia/program/presentation/wang)
+    * [Real User Monitoring at Dailymotion](https://medium.com/dailymotion/real-user-monitoring-1948375f8be5)
+    * [Alerting Ecosystem at Uber](https://eng.uber.com/observability-at-scale/)
+    * [Job-based Forecasting Workflow for Observability Anomaly Detection at Uber](https://eng.uber.com/observability-anomaly-detection/)
+    * [Securitybot: Distributed Alerting Bot at Dropbox](https://blogs.dropbox.com/tech/2017/02/meet-securitybot-open-sourcing-automated-security-at-scale/)
+    * [Observability (2 parts) at Twitter](https://blog.twitter.com/engineering/en_us/a/2016/observability-at-twitter-technical-overview-part-ii.html)
+    * [Distributed Security Alerting at Slack](https://slack.engineering/distributed-security-alerting-c89414c992d6)
+    * [Real-Time News Alerting at Bloomberg](https://www.infoq.com/presentations/news-alerting-bloomberg)    
 * [Distributed Security](https://msdn.microsoft.com/en-us/library/cc767123.aspx)
 	* [Approach to Security at Scale at Dropbox](https://blogs.dropbox.com/tech/2018/02/security-at-scale-the-dropbox-approach/)
 	* [Aardvark and Repokid: AWS Least Privilege for Distributed, High-Velocity Development at Netflix](https://medium.com/netflix-techblog/introducing-aardvark-and-repokid-53b081bf3a7e)	
@@ -203,21 +213,12 @@ An updated and curated list of readings to illustrate best practices and pattern
 	* [Syscall Auditing at Scale at Slack](https://slack.engineering/syscall-auditing-at-scale-e6a3ca8ac1b8)
 	* [Athenz: Fine-Grained, Role-Based Access Control at Yahoo](https://yahooeng.tumblr.com/post/160481899076/open-sourcing-athenz-fine-grained-role-based)
 	* [WebAuthn Support for Secure Sign In at Dropbox](https://blogs.dropbox.com/tech/2018/05/introducing-webauthn-support-for-secure-dropbox-sign-in/)
-	* [Alibaba Monitoring System](https://www.usenix.org/conference/srecon18asia/presentation/xinchi)
-	* [Smart Monitoring System for Anomaly Detection on Business Trends at Alibaba](https://www.usenix.org/conference/srecon17asia/program/presentation/wang)
 	* [Security Development Lifecycle (SDL) at Slack](https://slack.engineering/moving-fast-and-securing-things-540e6c5ae58a)
 	* [Unprivileged Container Builds at Kinvolk](https://kinvolk.io/blog/2018/04/towards-unprivileged-container-builds/)
 	* [Diffy: Differencing Engine for Digital Forensics in the Cloud at Netflix](https://medium.com/netflix-techblog/netflix-sirt-releases-diffy-a-differencing-engine-for-digital-forensics-in-the-cloud-37b71abd2698)
 	* [Detecting Credential Compromise in AWS at Netflix](https://medium.com/netflix-techblog/netflix-cloud-security-detecting-credential-compromise-in-aws-9493d6fd373a)
 	* [Scalable User Privacy at Spotify](https://labs.spotify.com/2018/09/18/scalable-user-privacy/)
-	* [AVA: Audit Web Applications at Indeed](https://engineering.indeedblog.com/blog/2018/09/application-scanning/)
-	* [Distributed Alerting](https://www.usenix.org/node/197452)
-		* [Alerting Ecosystem at Uber](https://eng.uber.com/observability-at-scale/)
-		* [Job-based Forecasting Workflow for Observability Anomaly Detection at Uber](https://eng.uber.com/observability-anomaly-detection/)
-		* [Securitybot: Distributed Alerting Bot at Dropbox](https://blogs.dropbox.com/tech/2017/02/meet-securitybot-open-sourcing-automated-security-at-scale/)
-		* [Observability (2 parts) at Twitter](https://blog.twitter.com/engineering/en_us/a/2016/observability-at-twitter-technical-overview-part-ii.html)
-		* [Distributed Security Alerting at Slack](https://slack.engineering/distributed-security-alerting-c89414c992d6)
-		* [Real-Time News Alerting at Bloomberg](https://www.infoq.com/presentations/news-alerting-bloomberg)
+	* [AVA: Audit Web Applications at Indeed](https://engineering.indeedblog.com/blog/2018/09/application-scanning/)	
 * [Distributed Messaging, Queuing, and Event Streaming](https://arxiv.org/pdf/1704.00411.pdf)
 	* [Scaling Push Messaging for Millions of Devices at Netflix](https://www.infoq.com/presentations/neflix-push-messaging-scale)
 	* [Samza: Stream Processing System for Latency Insighs at LinkedIn](https://engineering.linkedin.com/blog/2018/04/samza-aeon--latency-insights-for-asynchronous-one-way-flows)
@@ -243,7 +244,7 @@ An updated and curated list of readings to illustrate best practices and pattern
 		* [Kafka in Platform Events Architecture at Salesforce](https://engineering.salesforce.com/how-apache-kafka-inspired-our-platform-events-architecture-2f351fe4cf63)	
 		* [Kafka in Socket Architecture (with a Comprehensive Comparison Table) at Trello](https://tech.trello.com/why-we-chose-kafka/)	
 		* [Analytics Pipeline (Kafka, Dataflow, BigQuery) at Teads.tv](http://highscalability.com/blog/2018/4/9/give-meaning-to-100-billion-events-a-day-the-analytics-pipel.html)
-	* [Data Deduplication Techniques](https://en.wikipedia.org/wiki/Data_deduplication)
+	* [Stream Data Deduplication](https://en.wikipedia.org/wiki/Data_deduplication)
 		* [Exactly-once Semantics are Possible: 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)
 		* [Delivering Billions of Messages Exactly Once: Deduping at Segment](https://segment.com/blog/exactly-once-delivery/)