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Refactor the section of Distributed Messaging/Queuing

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binhnguyennus 2018-05-11 10:26:03 +08:00
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@ -164,28 +164,28 @@ An updated and curated list of selected readings to illustrate best practices in
* [OAuth Audit Toolbox at Indeed](http://engineering.indeedblog.com/blog/2018/04/oaudit-toolbox/)
* [Active Directory Password Blacklisting at Yelp](https://engineeringblog.yelp.com/2018/04/ad-password-blacklisting.html)
* [Secure Infrastructure to Store Bitcoin in the Cloud at Coinbase](https://engineering.coinbase.com/how-coinbase-builds-secure-infrastructure-to-store-bitcoin-in-the-cloud-30a6504e40ba)
* [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)
* [Distributed Messaging, Queuing, and Event Streaming](https://arxiv.org/pdf/1704.00411.pdf)
* [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)
* [Delaying Asynchronous Message Processing with RabbitMQ at Indeed](http://engineering.indeedblog.com/blog/2017/06/delaying-messages/)
* [Real-time Data Pipeline with Kafka at Yelp](https://engineeringblog.yelp.com/2016/07/billions-of-messages-a-day-yelps-real-time-data-pipeline.html)
* [Building Reliable Reprocessing and Dead Letter Queues with Kafka at Uber](https://eng.uber.com/reliable-reprocessing/)
* [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)
* [Kafka in Socket Architecture (with a Comprehensive Comparison Table) at Trello](https://tech.trello.com/why-we-chose-kafka/)
* [Delaying Asynchronous Message Processing with RabbitMQ at Indeed](http://engineering.indeedblog.com/blog/2017/06/delaying-messages/)
* [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)
* [Cherami: Message Queue System for Transporting Async Tasks at Uber](https://eng.uber.com/cherami/)
* [Messaging Service at Riot Games](https://engineering.riotgames.com/news/riot-messaging-service)
* [Event Stream Analytics with Druid (Search Engine meet Column DB) at Walmart](https://medium.com/walmartlabs/event-stream-analytics-at-walmart-with-druid-dcf1a37ceda7)
* [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)
* [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/)
* [Event Stream Analytics with Druid (Search Engine meet Column DB) at Walmart](https://medium.com/walmartlabs/event-stream-analytics-at-walmart-with-druid-dcf1a37ceda7)
* [Kafka the Message Broker](https://martin.kleppmann.com/papers/kafka-debull15.pdf)
* [When to use RabbitMQ or Kafka](https://content.pivotal.io/blog/understanding-when-to-use-rabbitmq-or-apache-kafka)
* [Kafka at Scale at LinkedIn](https://engineering.linkedin.com/kafka/running-kafka-scale)
* [Real-time Data Pipeline with Kafka at Yelp](https://engineeringblog.yelp.com/2016/07/billions-of-messages-a-day-yelps-real-time-data-pipeline.html)
* [Building Reliable Reprocessing and Dead Letter Queues with Kafka at Uber](https://eng.uber.com/reliable-reprocessing/)
* [Audit Kafka End-to-End at Uber](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)
* [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)
* [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/)
* [Deduplication For Efficient Storage (From 50 PB To 32 PB) At Mail.Ru](https://medium.com/@andrewsumin/efficient-storage-how-we-went-down-from-50-pb-to-32-pb-99f9c61bf6b4)