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Distributed Transactions in
Akka.NET
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Network
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Transaction Start
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Transaction Success
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Transaction Failure
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Actors - Start
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Actors - Working
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Actors - Commit
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Actors - Fail
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Editor's Notes

  1. INTRO SELF / DID BOOTCAMP TRAINING / TALK YESTERDAY => 1.0 last week => COMMON QUESTION going to show you a model for doing transactions in a distributed application, like the ones you can build with Akka .NET high level outline here, gonna teach you the model since only have 5 minutes no Leslie Lamport shit in here Pebble story => AVOID DUPES, ENSURE CRITICAL OPS DONT HAVE DUPES you can use this for many things large batch jobs, such as crawling / scraping
  2. THIS IS A TWO PHASE COMMIT preparing for the transaction => can we do this? committing the transaction => use case specific gonna model a distributed transaction, which you’d wrap in some more retry plumbing what is a transaction? => an atomic unit of work that can’t be divided any more, and succeeds or fails as a unit CAP theorem is really a tradeoff, a way of making decisions between consistency and latency if you have super high consistency requirements, it’s doable but a longer convo
  3. HOW WOULD YOU SCALE THIS to scale this in production, need more plumbing around this to ensure parallelization (following a consistent hashing model similar to C*), but this is the core model this is similar to how cassandra does it
  4. THIS CAN SCALE OUT ACROSS MANY MACHINES USING CLUSTERING HOW YOU DO THAT? => WE CAN SHOW YOU
  5. ONLY HAVE TO WRITE 2 ACTORS TO DO THIS (VERY LITTLE CODE) CAN SCALE IT OUT USING THE ACTOR SYSTEM EVEN THO ONE TRANSACTION AT A TIME, MANY IN PARALLEL
  6. WANT SCALABLE? GO HERE AND BOOK A TRAINING OR TALK TO ME AFTER