Spring Reactive

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https://www.reactivemanifesto.org https://projectreactor.io/docs/core/release/api/reactor/core/publisher/Flux.html

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Reactive systems have certain characteristics that make them ideal for low-latency, high-throughput workloads.

Reactive programming is a programming paradigm where the focus is on developing asynchronous and non-blocking components. The core of reactive programming is a data stream that we can observe and react to, even apply back pressure as well. This leads to non-blocking execution and hence to better scalability with fewer threads of execution.

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• Responsive: A reactive system should provide a rapid and consistent response time and hence a consistent quality of service
• Resilient: A reactive system should remain responsive in case of random failures through replication and isolation
• Elastic: Such a system should remain responsive under unpredictable workloads through cost-effective scalability
• Message-Driven: It should rely on asynchronous message passing between system components

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Problems:

• Failure in either inventory service or shipping service can have a cascading effect
• The calls to external systems and database are all blocking in nature
• The deployment cannot handle failures and fluctuating loads automatically

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• Difference between mono and flux it's the same as one-many relation. Mono can have only 1 item, where flux can have arrays.

val f1 = Flux.just(1, 2, 3, 4, 5) // the values need to be consumed

f1.subscribe { println(it) } // here we add a subscriber to consume the Flux

Tips:

• every method that returns an object and not a mono or a flux, it's a blocking method (don't use)