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. The second part of this 2-part series covers a practical approach to creating a successful, modular monolith.
Separate issue tracking systems for Development and IT Operations are a source of conflict and ineffectiveness for many organizations. For effective Database Lifecycle Management (DLM), we typically need shared issue tracking systems where DBA teams can see upcoming work from Development and Development teams can see details of live service issues logged from Production.
The biggest reason for adopting agile at scale is that despite the fantasy that a collection of agile teams will somehow organically integrate to deploy a program, that is not the reality. That’s why for larger dev/test outfits or projects, companies sometimes roll up individual agile teams 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.
Clemens Szyperski (Microsoft), Martin Petitclerc (IBM), and Roger Barga (Amazon Web Services) talk about challenges when building scalable, big data systems, and how to address them.
Just like during test execution process using an ‘exploratory’ technique guided by solid analytical thinking and randomness, we can reuse or automate scripts to achieve similar results. Here’s how.
In the book Agile Engagement, Santiago Jaramillo and Todd Richardson explore why employees can be disengaged, and provide solutions for measuring and driving engagement in organizations. 1