No enterprise application exists in a vacuum. Applications interact with services, other applications, external resources, databases, and more. As these applications scale, so does the complexity—more containers, more datasets, and more moving parts.

At Red Hat, our view is that most developers should not need to manage containers or Kubernetes directly. The most effective approach is to focus on writing business logic and push code to production through a platform like Red Hat OpenShift, using capabilities such as Red Hat OpenShift Dev Spaces and the OpenShift application platform to handle the underlying complexity.

At the same time, there are important use cases where advanced developers and platform engineers need direct access to container workflows, whether for building complex, multitiered application architectures, creating base images, or designing the platform itself. This is where Red Hat Desktop plays a critical role. Our goal is to minimize the amount of tedious, repetitive work developers and platform engineers must do throughout their workdays, while providing a consistent path from development to the environments where applications ultimately run.

Today, Red Hat Desktop brings cloud-native development to the desktop, enabling developers and platform engineers to build and test containerized applications locally in ways that align with Kubernetes environments, without requiring cluster access. For developers and platform engineers who work directly with containers, it serves as a testing ground before scaling with the power of OpenShift, providing a consistent, container-based development experience that aligns local workflows with enterprise environments.

Bridging the gap between laptop and logic

The desktop remains where most software development happens, with an iterative loop of writing, running, testing, and refining code. But the environments in which applications are developed and where they ultimately run are often very different.

What happens when issues only surface later because those environments are not aligned? What if testing requires coordinating multiple services—the database, the message queue, and more?

Those dependencies don’t naturally exist on a laptop. They must be recreated or accessed through shared environments, and test clusters are not always available. In practice, managing these environments can be as complex as production itself, highlighting the gap between desktop development and cloud-native deployment.

This gap is where local container-based workflows play an important role, enabling developers and platform engineers to build and validate applications before handing off to OpenShift.

Red Hat Desktop complements the model

Designed for developers and platform engineers who need to work directly with container workflows locally, Red Hat Desktop enables those staff to build and validate applications before handing off to OpenShift. It delivers an enterprise-supported local development environment, centered on the hardened and supported Red Hat build of Podman Desktop.

This new offering will continue to evolve and will include Kaiden, a local desktop application for building and running secure agentic sandboxes, with enterprise governance across models, data, and Model Context Protocol (MCP) integrations.

We’re expanding our focus on developers to give them options. Developers are increasingly pushing code early to shared environments, using tools like OpenShift Dev Spaces and OpenShift to validate applications closer to production—without needing to manage containers or Kubernetes directly.

At the same time, for more complex use cases developers and platform engineers rely on local container-based workflows to build, test, and shape the environments applications ultimately run in. Both approaches ultimately lead to OpenShift, providing a consistent path from development to production across either workflow.

Red Hat build of Podman Desktop

Red Hat build of Podman Desktop enables developers and platform engineers to build and validate containerized applications locally, particularly for scenarios where direct access to container workflows is required.

The upstream version of Podman Desktop has already been downloaded over 4 million times and is an easy-to-use desktop application for working with images, containers, and pods. It runs on macOS, Windows, and Linux and can interface with Docker as easily as Podman.

By making it easy to build and validate applications locally, developers can identify issues earlier and better prepare their applications for the Kubernetes environments in which they will ultimately run.

The Red Hat build of Podman Desktop is highly extensible, and with the Red Hat extension pack for Podman Desktop, there’s deeper integration with Red Hat technologies locally, giving you tools to manage everything from bootable container disk images to direct integrations with other Red Hat services. These are all designed to bridge your desktop environment with the Kubernetes and cloud environments. The Red Hat extension pack for Podman Desktop provides a set of extensions that eliminate the need for manual, individual installations. These extensions include:

  • Red Hat OpenShift local: Spin up and manage a local OpenShift cluster directly from the user interface (UI).
  • bootc: Build bootable container disk images for deployment on bare-metal or cloud environments.
  • Podman AI lab: Run large language models (LLMs) locally and experiment with agentic workflows.
  • Red Hat Hardened Images: Provides a catalog of minimal, hardened, distroless container images designed to reduce the security burden on developers. Integrated with Grype, it also enables vulnerability scanning of applications.

As the first addition to Red Hat Desktop, the Red Hat build of Podman Desktop sets the foundation for a new class of developer-focused tools. 

Where security-focused, agentic development begins

Red Hat Desktop will continue to evolve to support how developers are building software today. As AI becomes a core part of development workflows, new challenges are emerging, particularly around safely running autonomous agents and AI-generated code without compromising the developer’s machine or enterprise data.

This is where Kaiden comes in—an upstream, open source project and local AI development platform designed to give developers a safe, self-contained environment on their desktops for building with AI agents. It addresses the risks of modern AI development by providing sovereign, isolated environments under developer and enterprise control, where agent execution and untrusted code remain contained, protecting the host system and enterprise assets.

Beyond security, Kaiden enables hybrid AI workflows by allowing developers to:

  • Run low-latency tasks locally using available CPU/GPU resources.
  • Offload more intensive workloads to enterprise-managed environments such as Red Hat OpenShift AI.
  • Connect agents to governed enterprise assets, including internal architecture and business context, specific Red Hat skills, and MCP integrations.

This represents an early step in Red Hat’s approach to enterprise-ready agentic development—bringing enhanced structure, security, and governance to how AI is used in the software development process. We also plan to integrate Kaiden with upstream projects like OpenShell to extend these security-focused, local agentic sandboxes into broader development workflows.

We’re excited to evolve Kaiden over the coming years. To learn more about the project, visit the official project website. And if you’re interested in downloading Red Hat Desktop, including the Red Hat build of Podman Desktop, explore this page, which also has more information on service and support offerings.

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執筆者紹介

Balaji is the Head of Product, Developer Tools at Red Hat, where he leads the development of products to address the needs of developers, including Red Hat Developer Hub (based on Backstage.io) and Podman Desktop. Before joining Red Hat, Balaji served as the Executive VP of Product at OpsMx, where his primary focus was enabling companies to achieve intelligent and secure multi-cloud application delivery at scale. Prior to that, he led product management of cloud native solutions at Cisco. 
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