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  • Virtual Panel: Microservices in Practice

    Microservices have gone from development practices for the select few to something many developers in a range of organisations are embracing. Some believe that technologies that can assist with developing and adopting microservices are ineffective without associated changes within the organisations. We spoke with panelists to get different perspectives on the state of the art with microservices.

  • How to be Agile with Distributed Teams

    Based on several decades of experience, we have developed an agile framework for distributed teams. We defined 8 bubbles: Culture, Organization, Product, Team, Architecture, Engineering, Communication and Tools. Each bubble contains questions, virtues and practices to help organize distributed work. In this article, we describe culture and organization.

  • Getting Components to Communicate in Angular

    Components are the building blocks of Angular and every visual element in an Angular application is made with components. When we start breaking components apart into smaller components, we need to make sure they're able to pass data back and forth. That's when proper component communication becomes essential in our apps to keep all of our data in sync.

  • Q&A on the Book Scaling Teams

    The book Scaling Teams by Alexander Grosse and David Loftesness provides strategies and practices for managing teams in fast growing organizations. It explores five areas which often pose challenges when organizations need to scale -- hiring, people management, organization, culture and communication -- and gives solutions for recognizing and dealing with those challenges.

  • Size Estimation Approaches for Use with Agile Methods

    Reifer’s software sizing survey identifies five commonly used methods for sizing agile projects along with their strengths and weaknesses. Size is used as the basis for measurement and estimation. Stories/story points is the most popular, while function points are used at the project level. Sizing by analogy, proxies, Halstead vocabulary and hybrids are used by others as the situation warrants.

  • Product Owner Raison d'Etre in an Agile Team

    Companies may claim they're implementing Scrum, but is the claim really valid? Do they uphold the philosophy of Scrum? It turns out it's not, as a lot of companies are still practicing a distorted version of Scrum. Part of the common dysfunction is the misunderstood role of the product owner: a role essential to success with Scrum. What then is the actual job of a good product owner?

  • Q&A on The Great ScrumMaster

    In The Great ScrumMaster Zuzana Šochová explores the ScrumMaster role and provides solutions for dealing with everyday and difficult situations. She describes the #ScrumMasterWay, a concept which defines three levels of operation of ScrumMasters.

  • Practicing Machine Learning with Optimism

    Using machine learning to solve real-world problems often presents challenges that weren't initially considered during the development of the machine learning method. This article addresses a few examples of such issues and hopefully provides some suggestions (and inspiration) for how to overcome the challenges using straightforward analyses on the data you already have.

  • The Misaligned Middle and Getting off the Hamster Wheel Using Kanban

    At the Agile 2016 conference, Dominica DeGrandis and Julia Wester of Leankit gave talks on helping middle managers adapt to change and how Kanban can be used to identify problems in workflows, which people need to address.

  • More Than React: Why You Shouldn’t Use ReactJS for Complex Interactive Front-End Projects, Part I

    Does React function as well in complex interactive front-end projects as it does in simple interactive websites? In this article, Yang Bo introduces several problems encountered when using React in large projects and why he decided to develop a new framework to compete.

  • Introduction to Machine Learning with Python

    This series will explore various topics and techniques in machine learning, arguably the most talked-about area of technology and computer science over the past several years. We’ll begin, in this article, with an extended “case study” in Python: how can we build a machine learning model to detect credit card fraud?

  • Might the Blockchain Outlive Bitcoin?

    Crypto-currency remains controversial, and Bitcoin, a leading open source initiative to create an alternative form of currency, is at the center of this controversy. Here, the author provides an update on the state of Bitcoin in particular, and examines the future of crypto-currency in general.

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