Version 1.0 is "a major milestone in the evolution of Apache Storm", writes Apache Software Foundation VP for Apache Storm P. Taylor Goetz, and it includes many new features and improvements. In particular, Goetz claims a 3x–16x boost in performance.
Embrace decentralization, build service-based systems and attack the problems that come with distributed state using stream processing tools, Ben Stopford urged in his presentation at the recent QCon London conference.
With many databases in a system they are rarely independent from each other, instead pieces of the same data are stored in many of them. Using transactions to keep everything in sync is a fragile solution. Working with a stream of changes in the order they are created is a much simpler and more resilient solution, Martin Kleppmann stated in his presentation at the recent QCon London conference.
Lightbend, the company behind Akka, has released an open source microservices framework, Lagom built on their Reactive Platform, in particular the Play Framework and the Akka family of products together with ConductR for deployment. By default, Lagom is message-driven and asynchronous, and using distributed CQRS persistence patterns with event sourcing as the primary implementation.
Netflix has shed light on how the company uses the latest version of their Keystone Data Pipeline, a petabyte-scale real-time event stream processing system for business and product analytics. This news summarizes the three major versions of the pipeline, now used by almost every application at Netflix.
Command Query Responsibility Segregation (CQRS) separates the part that changes the state from the part that queries the state in an application. Axon is a Java framework implementing the building blocks of CQRS to help in when building CQRS applications, Dadepo Aderemi, writes in a series of blog post explaining CQRS by building a small demo application based on the Axon Framework.
Architecting a scalable and dynamic system without caching is explained by Peter Morgan, head of engineering for the sports betting company William Hill. The values of the bets on sporting events change constantly. No data can be cached; all system values must be current. Distributed Erlang processes model domain objects which instantly recalculate system values based on data streams from Kafka.
A key problem with the whole Reactive space and why it’s so hard to understand is the vocabulary with all the terms and lots of different interpretations of what it means, Peter Ledbrook claims and also a reason for why he decided to work out what it’s all about and sharing his knowledge in a presentation.
Yahoo! has benchmarked three of the main stream processing frameworks: Apache Flink, Spark and Storm.
Storing events in a relational database and creating the event identity as a globally unique and sequentially increasing number is an important and maybe uncommon decision when working with an event-sourced Command Query Responsibility Segregation (CQRS) system Konrad Garus writes in three blog posts describing his experiences from a recent project building a system of relatively low scale.
Modern software increasingly operates on data in near real-time. There is business value in sub-second responses to changing information and stream processing is one way to help turn data into knowledge as fast as possible, Kevin Webber explains in an introduction to Reactive Streams.
Eventual consistency is a design approach for improving scalability and performance. Domain events, a tactical element in Domain-Driven Design (DDD), can help in facilitating eventual consistency, Florin Preda and Mike Mogosanu writes in separate blog posts, each describing the advantages achievable.
Command Query Responsibility Segregation (CQRS) is the starting point of a change that will have a profound impact on system architecture, Dino Esposito claims in three articles in MSDN Magazine. It’s the first step in an evolution transitioning software architects from the idea of “models-to-persist” to the idea of “events-to-log” and about event-based data instead of data snapshots.
Looking at Command Query Responsibility Segregation (CQRS) in a larger architectural context there are other architectural styles available. There are database technologies solving the same problems but in a simpler way, Udi Dahan states looking into ways of approaching CQRS. There is also a way that fulfils a lot of the CQRS goals but with fewer moving parts when CQRS is really needed.
To make microservices awesome Domain-Driven Design (DDD) is needed, the same mistakes made 5-10 years ago and solved by DDD are made again in the context of microservices, David Dawson claimed in his presentation at this year’s DDD Exchange conference in London.