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+---
+title: "Yet Another Page on Readings in Distributed Systems"
+description: "My own list of links, articles, papers, etc. I enjoyed reading
+about distributed systems"
+tags:
+  - "Distributed Systems"
+  - "Readings"
+date: "2015-05-08"
+categories:
+  - "Distributed Systems"
+slug: "readings-in-distributed-systems"
+---
+
+> "Distributed systems are hard."
+-Everyone.
+
+This page is dedicated to general discussion of distributed systems, references
+to general overviews and the like. Distributed systems are difficult and even
+the well established ones aren't [bulletproof][1]. How can we make this better?
+As SysAdmins? As Developers? First we can attempt to understand some of the
+issues related to designing and implementing distributed systems. Then we can
+throw all that out and figure out what *really* happens to distributed systems.
+
+## Recommended Reading ##
+
+### General ###
+
+*   [Fallacies of Distributed Computing][2]
+
+*   [CAP Theorem][3]
+
+    -   [LYSEFGG: Distribunomicon: My other cap is a theorem][4]
+
+    -   For a more entertaining introduction to CAP, Hebert's ''Learn You Some
+        Erlang for Great Good'' has a really good subsection on the topic that
+        includes the zombie apocalypse and some introduction to how a blend
+        between AP and CP systems can be achieved.
+
+    -   [CAP Theorem Proof][5]
+
+    -   [You can't sacrifice partition tolerance][6]
+
+*   [Consistency Model][7]
+
+    -   [List of Consistency Models][8]
+
+    -   [Linearizability][9]
+
+    -   [Linearizability versus Serializability][10]
+
+    -   [Eventual Consistency][11]
+
+*   [Paxos][12]
+
+    -   [Understanding Paxos (Part 1)][13]
+
+*   [Vector Clock][14]
+
+*   [Split-Brain][15]
+
+*   [Network Partitions][16]
+
+*   [Distributed Systems and the End of the API][17]
+
+*   [The Log][18]: What every software engineer should know about real time
+    data's unifying abstraction
+
+The [Jepsen][19] "Call me maybe" articles are really good, well written essays
+on topics and technologies related to distributed systems.
+
+Introductory post to the "Call me maybe" series:
+
+*   [Call me maybe][20]
+
+Here are some personal recommendations:
+
+*   [The Network is Reliable][1]
+
+*   [Strong Consistency Models][21]
+
+*   [Asynchronous Replication with Failover][22]
+
+Really anything from Ferd Herbert is good. Particularly, the first and last
+chapters of [Erlang In Anger][30] which includes longer essays from his blog
+posts.
+
+*   [Queues Don't Fix Overload][31]
+
+*   [It's About the Guarantees][32]
+
+*   [Lessons Learned while Working on Large-Scale Server Software][33]
+
+### General Networking ###
+
+*   [TCP incast][29]
+
+### Hadoop ecosystem ###
+
+This link is more specific to HDFS and is a rather limited experiment but
+nonetheless a good read to further understand partition issues that can arise
+in Hadoop systems:
+
+*   [Partition Tolerance in HDFS][23]
+
+More links from the [Jepsen essays][19]:
+
+*   [Call me maybe: Zookeeper][24]
+
+*   [Call me maybe: Kafka][25]
+
+*   [Call me maybe: Cassandra][26]
+
+### Databases ###
+
+-   [Wikipedia ACID][27]
+
+-   [Call me maybe: Postgres][28]
+
+[1]: http://aphyr.com/posts/288-the-network-is-reliable
+
+[2]: http://en.wikipedia.org/wiki/Fallacies_of_Distributed_Computing
+
+[3]: http://en.wikipedia.org/wiki/CAP_theorem
+
+[4]: http://learnyousomeerlang.com/distribunomicon#my-other-cap-is-a-theorem
+
+[5]: http://lpd.epfl.ch/sgilbert/pubs/BrewersConjecture-SigAct.pdf
+
+[6]: http://codahale.com/you-cant-sacrifice-partition-tolerance/
+
+[7]: http://en.wikipedia.org/wiki/Consistency_model
+
+[8]: http://en.wikipedia.org/wiki/Category:Consistency_models
+
+[9]: http://en.wikipedia.org/wiki/Linearizability
+
+[10]: http://www.bailis.org/blog/linearizability-versus-serializability/
+
+[11]: http://en.wikipedia.org/wiki/Eventual_consistency
+
+[12]: http://en.wikipedia.org/wiki/Paxos_(computer_science)
+
+[13]: http://distributedthoughts.wordpress.com/2013/09/22/understanding-paxos-part-1/
+
+[14]: http://en.wikipedia.org/wiki/Vector_clock
+
+[15]: http://en.wikipedia.org/wiki/Split-brain_(computing)
+
+[16]: http://en.wikipedia.org/wiki/Network_partitioning
+
+[17]: https://speakerdeck.com/cemerick/distributed-systems-and-the-end-of-the-api
+
+[18]: http://engineering.linkedin.com/distributed-systems/log-what-every-software-engineer-should-know-about-real-time-datas-unifying
+
+[19]: http://aphyr.com/tags/jepsen
+
+[20]: http://aphyr.com/posts/281-call-me-maybe
+
+[21]: http://aphyr.com/posts/313-strong-consistency-models
+
+[22]: http://aphyr.com/posts/287-asynchronous-replication-with-failover
+
+[23]: https://www.growse.com/2014/07/18/partition-tolerance-and-hadoop-part-1-hdfs/
+
+[24]: http://aphyr.com/posts/291-call-me-maybe-zookeeper
+
+[25]: http://aphyr.com/posts/293-call-me-maybe-kafka
+
+[26]: http://aphyr.com/posts/294-call-me-maybe-cassandra
+
+[27]: http://en.wikipedia.org/wiki/ACID
+
+[28]: http://aphyr.com/posts/282-call-me-maybe-postgres
+
+[29]: http://www.snookles.com/slf-blog/2012/01/05/tcp-incast-what-is-it/
+
+[30]: http://www.erlang-in-anger.com/
+
+[31]: http://ferd.ca/queues-don-t-fix-overload.html
+
+[32]: http://ferd.ca/it-s-about-the-guarantees.html
+
+[33]: http://ferd.ca/lessons-learned-while-working-on-large-scale-server-software.html