Gitpod Revamps Dev Automation Tool

Gitpod announced today it refreshed the dashboard for its namesake open source tool for automating the deployment of development environments, in addition to making Microsoft VS Code its default tool for editing code.

In addition, Gitpod has included support for sudo privileges and Docker images using an advanced user namespace to map and limit access to workloads using a built-in Supervisor capability.

Fresh off raising an additional $13 million in funding, Gitpod CEO Sven Efftinge said now that it’s clear developers will be working from anywhere for the foreseeable future, the need for a tool to automate setting up a developer environment on a local machine outside of an office has become more apparent.

Gitpod claims there are now more than 350,000 developers using its tool that creates a Kubernetes pod on each developer machine to deploy a complete application development environment, including the integrated development environment (IDE), plugins, compilers, build tools, code generators, databases and application servers. Gitpod makes use of the version control systems provided within, for example, a continuous integration/continuous delivery (CI/CD) platform as the single source of truth for configuring an application development environment.

The overall goal is to eliminate the time developers waste setting up application development environments so they can write code on their own machines. That approach also makes it simpler for developers to collaborate around the same application development environment regardless of where they happen to be physically located.

Efftinge said Gitpod provides DevOps teams with a tool to automate setting up development environments across any Git repository that is the equivalent of the Codespaces tool that GitHub recently made available. Rather than having that capability for only one repository, Efftinge noted that most developers work on projects that span multiple types of repositories.

Automating that process also makes it simpler to align development environments with production environments. One of the reasons why code doesn’t work in a production environment when it is first deployed is because the local development environment has been manually configured in a way that doesn’t accurately reflect the production environment. That issue can become even more problematic when developers are working on multiple projects involving, for example, separate microservices constructed using different repositories.

In the wake of the COVID-19 pandemic and the acceleration of multiple digital business transformation initiatives there’s naturally a lot more focus on automation and developer productivity. Most developers will be working outside the office for the foreseeable future. Of course, most developers have been writing code outside the office for years. The challenge now is enabling teams of developers to develop applications as efficiently as possible, no matter where they are in the world. In fact, now that development teams have become more distributed, organizations are becoming more comfortable hiring developers wherever they find them.

Eliminating inefficient manual tasks, such as maintaining development environments, is, of course, going to be a prerequisite for making it possible for those developers to, over time, navigate multiple application development projects without ever having met their colleagues in person.