Overview
Discover how to achieve strong eventual consistency in distributed systems using actor models and Amazon Web Services in this 36-minute conference talk. Learn about sidestepping the CAP theorem through simple rules and principles demonstrated with C# code samples. Explore the implementation of Conflict-free Replicated Data Types (CRDTs), event sourcing, and immutability to ensure consistent data across distributed nodes without direct communication. Gain insights from real-world applications at Domain.com.au, including recovery from catastrophic data failures in clickstream events. Delve into topics such as weak eventual consistency, querying, merging, and the importance of immutability in distributed systems. Examine practical examples of clickstream pipelines, multiple actor systems, and continuous deployment in distributed swarms. Understand how to handle data recovery and utilize tools like Elastic Search, SQS, and hash sets in cloud-based architectures.
Syllabus
Introduction
Philips background
Weak Eventual Consistency
XP Analogy
Simple Principle
Conflictfree replicated data types
Cap theorem
CRDTs
Querying
Merge
I dont understand
Union is all you need
Commutative
Why Immutability
How to Store
What do you do
ClickStream Pipeline
ClickStream Events
Multiple Actor Systems
Actor Systems App
Elastic Search
Continuous Deployment
Distributed Swarm
Catastrophic Failure
Data Recovery
Last Batch Request
Hash Sets
SQS
Questions
Taught by
NDC Conferences