Podcasts

Linda Rising on the Importance of Patterns, Her Journey & Patterns for Driving Change/Innovation

On the InfoQ Podcast this week, Wes Reisz talks with the Queen of Patterns, Linda Rising. Linda discusses her thoughts on the importance of patterns, she answers questions about what really is a pattern, and how she became involved in working with them. She discusses a variety of organizational and personal patterns and finally wraps with patterns to apply when driving change and innovation.

Nora Jones on Establishing, Growing, and Maturing a Chaos Engineering Practice

Nora Jones, a senior software engineer on Netflix’ Chaos Team, talks with Wesley Reisz about what Chaos Engineering means today. She covers what it takes to build a practice, how to establish a strategy, defines cost of impact, and covers key technical considerations when leveraging chaos engineering.

Security Considerations and the State of Microservices with Sam Newman

Wesley Reisz talks with Sam Newman about microservices. They explore the current state of the art with regards to the architectural style and corresponding tooling and deployment platforms. They then discuss how microservices increase the surface area of where sensitive information can be read or manipulated, but also have the potential to create systems that are more secure.

Jessica Kerr on Productivity, Slack Chatbots, Yak Shaving, & Why Diversity Matters for Innovation

Wesley Reisz talks with Jessica Kerr about her focus on developer productivity. Topics include her work at Atomist building Slack Chatbots, an approach to categorizing Yak Shaving (in an effort to prioritize and automate development dependencies), how an innovation culture drives diversity, and, finally, the role of 10x developers in the lifecycle of a company or product.

Martin Hadley on R and the Modern R Ecosystem

In this podcast Werner Schuster talks to Martin Hadley, data scientist at University of Oxford. They discuss the state of the R language, the rich R ecosystem that covers development (RStudio), notebooks for publication (R Notebooks, RPubs), writing web apps (Shiny), and the pros/cons of the different data frames implementations.