By Riccardo Terrell
In this article, you’re going to implement one of the most common coordination techniques—the pipeline pattern. In general, a pipeline is composed of a series of computational steps, organized as a chain of stages, where each stage depends on the output of its predecessor and usually performs a transformation on the input data.
By Jeff Smith
Many people don’t even mention data collection when discussing the work of building machine learning systems. This article discusses the collection of uncertain data and collecting data at scale.
By Ivan Čukić
This article discusses laziness implementation in C++, using a common example – calculating Fibonacci numbers.
By John Carnell
This article discusses client-side resiliency patterns intended to help make your app more robust and resistant to failure.
By Morgan Bruce and Paulo A. Pereira
This article explores approaches to software engineering using the microservice architecture and ways that you can build and design new features using microservices, instead of the traditional monolithic style.
By Brandon Byars
This article discusses a unique kind of service testing – testing a service that depends on a fictional “Abagnale” service. It involves doing something which has probably never been done before in the history of mocking frameworks: we need to create a virtual imposter that pretends to be a real imposter.
By Kalle Rosenbaum
This article discusses the basics of cryptographic hashes, which
are used all over the place in Bitcoin. Trying to learn Bitcoin without knowing what cryptographic hashes are is like learning chemistry without knowing what an atom is.
By Anthony Williams
This article explores how to synchronize concurrent operations in the C++ programming language and how this relates to threads and their respective function.
By Chris Richardson
In this article, you will learn about various strategies for breaking up applications into their component services, and the advantages and disadvantages of each approach.
By Riccardo Terrell
In this article, we discuss the need for concurrency, common issues specific to developing concurrent applications in either imperative or object-oriented programming (OOP) and functional programming, and why the functional programming paradigm is ideal for solving common concurrency issues.