We have reached an exciting milestone in the development of Argoflows, a Rust library designed to integrate and manage Argo Workflows—a leading project in the Cloud Native Computing Foundation (CNCF) ecosystem—directly from Rust applications. In this video, we publish the first version of Argoflows to crates.io, marking a significant step in making this library available to the Rust community. This release includes the foundational components necessary for developers to start integrating Argo Workflows into their Rust applications.

In this video, we continue the development of Argoflows, a Rust library designed to integrate and manage Argo Workflows—a leading project in the Cloud Native Computing Foundation (CNCF) ecosystem—directly from Rust applications. We focus on implementing the ConfigBuilder, a crucial component that allows users to configure the Argoflows library with the necessary parameters to connect to an Argo Workflows server. This builder pattern provides a flexible and intuitive way to set up the library, enabling users to specify details such as the server URL, authentication methods, and other configuration options.

In this video, we continue the development of Argoflows, a Rust library designed to integrate and manage Argo Workflows—a leading project in the Cloud Native Computing Foundation (CNCF) ecosystem—directly from Rust applications. We focus on implementing the get_version endpoint of the Info API, which provides essential information about the Argo Workflows server, including its version and build details. This endpoint is crucial for ensuring that the Argoflows library can interact correctly with the Argo Workflows server and to provide users with the necessary context about the server they are interacting with.

In this video, we kick off the development of Argoflows, a Rust library designed to integrate and manage Argo Workflows—a leading project in the Cloud Native Computing Foundation (CNCF) ecosystem—directly from Rust applications. We start by defining the foundational structures that will form the backbone of Argoflows. This includes: Modules: Organizing the code into logical components for better maintainability. Types: Defining the data structures that represent Argo Workflows and their components, ensuring type safety and clarity in our API.

In this video, we continue building our own wc tool in Rust. We are using the wc command as a reference. The wc command is a Unix utility that counts the number of lines, words, and characters in a file. The name wc stands for “word count”. In the previous video, we started building our own wc tool in Rust. We implemented the basic functionality of the wc command, which is to count the number of lines, words, and characters in a file.

In this video, we introduce Argoflows, a Rust library designed to seamlessly integrate and manage Argo Workflows—a popular CNCF project—directly from your Rust applications. We delve into the motivation behind Argoflows, its development goals, and how it fits into the broader Cloud Native ecosystem. We also walk through the initial project setup: creating a new Cargo project adding the necessary dependencies organizing the code structure. Emphasis is placed on maintaining consistent coding style and following best practices in modern Rust development.

The video is meant for beginners, who are just getting started with the Rust programming language. In case you are new to the language, I would recommend you checkout the previous video. In this video, we try to build our own wc tool following the steps layed out in the John Crickett’s coding challenge - https://codingchallenges.fyi/challenges/challenge-wc/. We could only get too far, so stayed tuned for Part 2. The video is meant for beginners, who are just getting started with the Rust programming language.

The video is meant for beginners, who are just getting started with the Rust programming language. In this video, we first explore cargo (the build system and package manager for Rust) and then build a simple guessing game. On our way, we talk about immutability, enums, match expressions, and Result in Rust.

The very first live stream on Rust Hours. We started from zero to building a very small CLI application. The stream aims to help everyone learn Rust with a “follow along” approach.

The talk delves into 3 key paradigms - Go’s CSP model for concurrency, Rust’s data race prevention through ownership and borrowing, and Rust’s opt-in shared memory model.