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The latest News and Information on DevOps, CI/CD, Automation and related technologies.

Components Deep Dive: Docker-Compose in Bunnyshell

Discover how to easily create an environment in Bunnyshell using your docker-compose.yaml file. This developer-focused video walks you through the process of importing your services and configuring your components using 100% Docker-compose syntax. Learn how to expose public hosts, attach volumes, and set up build arguments. We'll wrap up with a demonstration of how to deploy your environment in just a few minutes.

Components Deep Dive: Helm & Kubernetes in Bunnyshell

Learn how to deploy an environment in Bunnyshell using Helm charts and Kubernetes manifests. This developer-centric video breaks down the process of configuring components such as the frontend, backend, and databases. Dive into the details of using Helm components, running user-defined scripts, creating values files, and leveraging Helm's templating system. We also explore how to use Kubernetes manifests and perform replacements within your application.

Components Deep Dive: Generic Components in Bunnyshell

Discover how to work with generic components in Bunnyshell, a powerful tool for developers. This video provides a practical example of integrating a serverless database, Neon, into an environment. Learn about the configuration of generic components, how they run on images, and their use of deploy and destroy scripts. We also explore how to use exported variables within the same component or other components, and how to organize and manage scripts.

Automating Preview Environments in Bunnyshell

Learn how to set up and automate preview environments in Bunnyshell to improve code reviews, gather feedback, and facilitate QA testing. This video demonstrates how to enable automatic preview environment creation, configure settings for deployment and destruction, and manage pull requests See how to create a new environment, modify the source environment, and view the changes made in the application. This video also covers the automatic deletion of environments after a pull request has been closed or merged.

Troubleshooting with Bunnyshell

This video demonstrates how to troubleshoot various issues using Bunnyshell, including failed builds, broken backend, and issues caused by generic components. Learn how to access pipeline logs, container outputs, and Kubernetes resources for debugging, as well as how to perform SSH into containers and port forward for databases. By utilizing these techniques, you can efficiently identify and resolve problems without needing direct access to the Kubernetes cluster or infrastructure.

Create Environments from a Template in Bunnyshell

In this tutorial, learn how to create environments in Bunnyshell using custom templates. Templates help to streamline the process of setting up environments, making it faster and more reliable. The video demonstrates how to create environments for development and staging from custom templates and provides an overview of how to deploy them. By using templates, you can ensure consistency and predictability across your projects.

CTO Fundamentals II - 3:4 CTO Legacy Webinar Recording

Corneliu Fatulescu has more than 23 years of experience in SaaS, two-sided markets, user-generated content, and media products. Currently, he's leading a team of 60 engineers working on defining the technology strategy and vision at the group level. Have you ever assumed another CTO's legacy? Did you say, "Wow! I love it. We have a solid foundation. We need to keep going, and everything will be alright"? Or was it more like, "this is a sinking mess"?

CTO Fundamentals II - 2:4 CTO Decision-Making Webinar Recording

Corneliu Fatulescu has more than 23 years of experience in SaaS, two-sided markets, user-generated content, and media products. Currently, he's leading a team of 60 engineers working on defining the technology strategy and vision at the group level. The majority of CTOs acknowledge that they rarely select from the best set of available options when making judgments. No one would select from these choices if they were taken out of context.

Four Challenges for ML data pipeline

Data pipelines are the backbone of Machine Learning projects. They are responsible for collecting, storing, and processing the data that is used to train and deploy machine learning models. Without a data pipeline, it would be very difficult to manage the large amounts of data that are required for machine learning projects.

The Complex Reality of Multi-Cloud Environments

Most companies today have multiple cloud instances with multiple cloud service providers (CSPs) as well as an on-premises environment. It’s complex, but that doesn’t make it inherently wrong—there are usually good business reasons behind the decisions. It does, however, create management challenges.