When using Domain-Driven Design (DDD) separating the concerns of a large system into bounded contexts with each context using its own data store there is often a need to share some common data. One way of doing that is to let each context publish events about changes, events that others can listen to, Julie Lerman recently explained in MSDN Magazine.
A common context for Command-Query Responsibility Segregation (CQRS) is a collaborative domain with multiple users working on the same set of data, it is less suitable in domains with only a single user working on a piece of data, Udi Dahan explained when discussing CQRS in an interview.
Leslie Lamport is the author of some of the most cited computer science papers and won a Turing Award in 2013 for his seminal work in distributed and concurrent systems. This is a summary of an interview that Lamport gave to Software Engineering Radio touching themes such as his early work in distributed systems and the importance of precise thinking in programming.
State transitions are an important part of our problem space and should be modelled within our domain, Greg Young states in a recent presentation focusing on basic event sourcing and how CQRS fits in.
Robert C. Martin's advice is to start with shared libraries and a plugin architecture and only when that becomes insufficient consider microservices. Giorgio Sironi argues against this, emphasising how different interactions between microservices are compared to interactions between objects and warns for the cost of retrofitting microservices over an existing code base.
Vaughn Vernon describes a reactive process manager supervising the process of finding the best loan quotes from banks with a focus on the reactive part, using Actor model for the implementation with examples written in Scala using Akka and C# using his recently published Dotsero toolkit.
CQRS and Event Sourcing provide a clear and concise way to build distributed applications that adhere to the reactive manifesto, Duncan DeVore claimed in a recent presentation sharing his experiences building a distributed application using Akka and Scala.
At the Bacon Conference last May, bitly Lead Application Developer Sean O'Connor explained the most relevant lessons bitly developers learned while building a distributed system that handles 6 billions clicks per month.
Last week at the Microsoft Worldwide Partner Conference, Microsoft took the wraps off of Azure Event Hubs. This service – in preview release until General Availability next month – is for high throughput ingress of data streams generated by devices and services. Event Hubs resembles Amazon Kinesis and uses an identical pricing scheme based on data processing units and transaction volume.
DDD and CQRS are great for building scalable software considering concepts like bounded contexts, transaction boundaries and event based communication and is together with Akka a complete platform for building enterprise applications, Pawel Kaczor starts a three-part series building an reactive application based on these concepts.
Delay of message sending into the future is a very powerful pattern and is often the preferable way of dealing with temporal problems compared to batch job that will run a query on the domain model and update some aggregates, Greg Young explained at the recent DDD Exchange conference in London.
DataTorrent is a real-time streaming and analyzing platform that can process over 1B real-time events/sec.
Using size for defining microservices is useless when determining a service responsibility, Jeppe Cramon states in a series of blog posts explaining his view on microservices and the coupling problems he finds in synchronous two-way communication.
We have to maximize locality of reference and minimize contention to make systems scale, Jonas Bonér, creator of the Akka project, stated in a recent presentation about scalability in reactive systems. By using a share nothing architecture, build on an event-driven foundation and adhering to core principles that have been proven to work for ages we can write really scalable systems.
Typesafe has announced the early preview of Akka Streams, an open source implementation of the Reactive Streams draft specification using an Actor-based implementation. Reactive Streams is an initiative to provide a standard for asynchronous stream processing with non-blocking back pressure on the JVM. Back pressure in needed to make sure the data producer doesn't overwhelm the data consumer.