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The easiest path is to read Designing Data Intensive Applications by Martin Kleppman. Builds from the ground up and by the end (or after a second read) you will
by mapme 5y ago
The easiest path is to read Designing Data Intensive Applications by Martin Kleppman. Builds from the ground up and by the end (or after a second read) you will have a deep understanding. Book hits on all of of the tech you mentioned except Kube. For that read one of the original google papers on cluster management systems eg. Omega
- jitl 5y agoI want to hire Martin Kleppman!!!! URGH!!!
- ocdbg 5y agoMartin Kleppman also has uploaded distributed systems course lectures on his channel https://www.youtube.com/playlist?list=PLeKd45zvjcDFUEv_ohr_HdUFe97RItdiB https://www.youtube.com/playlist?list=PLeKd45zvjcDFUEv_ohr_H...
- bwh2 5y agoDesigning Data Intensive Applications was surprisingly detailed in terms of data storage. I also enjoyed Release It! by Michael Nygard to learn about making distributed systems more resilient.
- ingvul 5y agoWhile I recommend reading DDIA, I think buzzcut_diet may end up disappointed. Reasons: - it takes a while to read DDIA. Probably around 6 months of focused reading. Perhaps more - one can learn a really good chunk of theoretical stuff... but probably not applicable to day to day work - zero practical experience will be gained regarding Kubernetes, Spark, Kafka, EMR, Redis So, I would recommend a more practical approach: - start already reading the documentation of K8s, Kafka, Spark, etc. Choose one and go for it. I would recommend Kafka since its documentation is well written - while reading documentation of the tooling above, one will inevitable stumble upon theoretical stuff that will not be explained in detail: that's exactly when you pick up DDIA (or similar books) and try to find the topic in the index and read it.