Amazon’s early principles of distributed system design to meet Amazon S3 requirements:

  1. Decentralisation: Use fully decentralised techniques to remove scaling bottlenecks and SPOF


In the current connected world — Websites, Mobile Apps, IoT Devices collect a large volume of users’ personally identifiable activity data. These collected data is used for varied purposes of analytics, marketing, personalisation of services, etc. Data is assimilated through site cookies, tracking device IDs, embedded JavaScripts, Pixels, etc. to name a few. Many of these tracking and usage of collected data happens behind the scene and is not apparent to an average user. Consequently, many Countries and Regions have formulated legislations (e.g. …


Attribution: https://timoelliott.com/

This is a quick note on the key considerations that I have made over the years while designing and developing large scale distributed real time data processing systems. These principles follow evolving usage patterns and use cases.

  1. Processing Semantics
  • “Exactly Once” processing semantics or “at-least once”. Choose your semantics based on your use case needs. It is possible to configure different semantics for each use case.

Subhadip Mitra

Distributed Systems, Artificial Intelligence, Blockchain, Theoretical Physics, Open Source

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