As agile grows-out of its years of self-obsession and teenage petulance into a post-agile state, ‘Predictable Agile Delivery’ feels like a realistic goal that advantages both the business sponsor and their development stakeholders. This article share some ‘good, bad and ugly’ examples of practices that often work and some that always fail for improving large organizations.
The best product owners are insatiably curious about their customers; they observe them in action, interview them, and collaborate with them and bring them into the development process, said Geoff Watts. In his new book Product Mastery he explores what he calls “the difference between good and great product ownership”.
Artificial intelligence (AI) is increasingly hyped by everyone, from well-funded startups to well-known software brands. In this article the author describes the need for high-quality, structured data before AI technologies can be of use to organizations and their customers.
A practical approach to designing and building a modular monolith, can result in better solution than microservices, especially for complex domains, such as enterprise applications. 4
The choice of issue tracking tools and usage seems a no-brainer: pick the tool that does the job best. But in today's world of continuous delivery and operations, teams need to work closer than ever.
For larger dev/test projects or companies, individual agile teams are rolled up into one agile environment at enterprise scale. Yousef Awad presents lessons learned and words to the wise.
Sergey Laptick shows how to create web components to display data in the form of different types of lists using the Webix UI Library.
What does a team look like, and what do they have to help them be a successful team? This article discusses some of the tools and techniques that teams use to become and maintain team effectiveness.
Does your approach to application and data center security change when adopting cloud services? InfoQ reached out to Pete Cheslock, from Threat Stack to learn more.
In the age of microservices, "monolith" has become a dirty word. Yet, monoliths, designed with an emphasis on modularity, can be a better solution for complex domains, such as enterprise applications. 9
Monte Carlo planning provides a rigorous, quantitative account of what the future may bring. It has advantages over standard average case approaches and you can start with a simple Excel spreadsheet.
In this article, author discusses Apache Spark GraphX used for graph data processing and analytics, with sample code for graph algorithms like PageRank, Connected Components and Triangle Counting. 1