Videos

In this video, Solomon Hykes, Co-Founder both Dagger and Docker reviews why containerizing applications with Docker was so key and why we now need to containerize our pipelines.

In this demo, Lev Lazinskiy shows how to integrate Dagger pipelines with Jenkins. He explains the setup process for a Jenkins pipeline using Dagger and covers both a simple and a modular approach to managing CI pipelines effectively.

In this demo, Kambui introduced the concept of agentic workflows, particularly highlighting their role in AI-driven processes involving language models. He shared his journey of using Dagger to streamline and optimize continuous integration pipelines.

In this demo, Marcos Lilljedahl explains how to run Kubernetes clusters using Dagger. He addresses the challenges and solutions in integrating Kubernetes within Dagger and shares a practical setup using the k3s Dagger module.

In this demo, Andrea Luzzardi shows how to enhance debugging capabilities in Dagger pipelines by integrating terminal commands directly into the pipeline code. This allows setting breakpoints and inspecting the state of the container at various stages of execution.

In this video, Gerhard Lazu shows the advanced functionalities of Dagger beyond its typical use in CI/CD workflows. He begins by exploring the connection between the Dagger CLI and the Dagger engine, emphasizing the role of Docker and how running commands in debug mode can provide deep insights into their interaction. The video covers various methods to connect the Dagger CLI to the engine, including Docker and Podman containers, Kubernetes, and using TCP or Unix sockets. Gerhard also demonstrates the use of custom Docker images and ensures compatibility across different environments.

In the demo, Sam walks through the process of using Snowpark Container Services with a focus on creating a Dev environment using Dagger.

The demo highlights the efforts to optimize the performance of the TypeScript SDK. By using Dagger Cloud, Tom compares the execution times of current and new runtime engines. The new engine shows a significant reduction in initialization time from 25 seconds to 17 seconds.

In this demo, Marcos shows us how to build an AI RAG pipeline using Dagger, focusing on simplifying the process of integrating AI models and vector databases for handling large documents and creating meaningful responses without the need for extensive Python programming.