Podcasts

James Clark on How Ballerina Handles Network Interaction, Data, and Concurrency

Charles Humble discusses the design of the Ballerina programming language with its lead designer James Clark. They discuss how the goals of the language inform a number of design choices including: the type system, error handling, the concurrency model, and the language’s built in support for visualization of program flows.

Rosaria Silipo on Codeless Deep Learning and Visual Programming

In the podcast, Rosaria Silipo talks about the emerging trends in deep learning, with focus on low code visual programming to help data scientists apply deep learning techniques without having to code the solution from scratch.

Francesca Lazzeri on Machine Learning for Time Series Forecasting

In the podcast, we speak with Dr. Francesca Lazzeri on machine learning for time series forecasting as the main topic which included automated machine learning and deep learning for time series data forecasting, as well as other emerging trends in machine learning development and operations areas including data science lifecycle.

Alex Matyushentsev on Argo CD, Argo Rollouts, and Continuous Delivery with Kubernetes

In this podcast Alexander Matyushentsev, principal software engineer at Intuit and core engineer on the Argo CD and Argo Rollouts projects, sat down with InfoQ podcast host Daniel Bryant and discussed the Argo projects, continuous delivery with Kubernetes, and how platform teams can help developers embrace modern release techniques and related technologies.

Lucas Cavalcanti on Using Clojure, Microservices, Hexagonal Architecture and Public Cloud at Nubank

In this episode of the InfoQ podcast, Charles Humble talks to Lucas Cavalcanti about Nubank’s early architectural choices, including starting with Clojure and microservices. They discuss the challenges of using public cloud for financial services in Brazil, Nubank’s use of Alistair Cockburn's Hexagonal Architecture and immutable architecture, and lessons learnt as the startup scaled.