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Chapter 8. Developer Preview features
Review Developer Preview features that are available in Red Hat Enterprise Linux 10.2.
For information about Red Hat scope of support for Developer Preview features, see Developer Preview - Scope of Support.
8.1. Installer and image creation
Review Developer Preview features available for installer and image creation in Red Hat Enterprise Linux 10.2.
- Unified storage for bootc is available as a Developer Preview
With this Developer Preview feature, you can configure
bootcto pull the host image into bootc-owned container storage, enhancing container image management efficiency. This feature reduces the need for repeated image pulls on the same host, allowing the host image to be reused by container runtimes, such as podman for running and building layered images. It improves overall network performance by usingzstdchunking when available and streamlines development and testing processes.As a result, by configuring the unified storage feature on your system, you can store, manage, and utilize container images more efficiently, providing a seamless bootc container management experience.
Jira:RHELDOCS-21395[1]
8.2. RHEL Lightspeed
Review Developer Preview features available for RHEL Lightspeed in Red Hat Enterprise Linux 10.2.
gooseas an alternative for the existing RHEL command-line assistant back-end serviceThis update introduces
gooseas an alternative to the command-line interface (CLI) client for the existing RHEL command-line assistant (CLA) back-end service. These changes do not affect thecommand-line assistantback end, and functionalities remain the same. Thegoosepackage is available on the RHEL Extensions repository. You can use thegoosetext chat interface interactively during the chat session.When you use
goose, before you execute the MCP server or a local Linux command, it prompts you to confirm that the LLM does not break your system or workflow.For more information, see the Red Hat Knowledgebase article link:https://access.redhat.com/articles/7142302Optimize the RHEL command-line assistant tasks by using goose-redhat].
ImportantThe existing RHEL command-line assistant (CLA) that uses a Red Hat-provided LLM is still available and integrated directly into the RHEL 10 (and late RHEL 9) ecosystem. It is usually installed by using standard DNF repositories and is a core part of the RHEL Lightspeed offering.
Jira:RSPEED-2846[1]
- Agent skills for Red Hat Enterprise Linux are available (Developer Preview)
With this Developer Preview, Red Hat Enterprise Linux introduces two new agent skills designed to enhance AI-driven administration and troubleshooting for Red Hat Enterprise Linux (RHEL). The Agent skills for RHEL are built on the Agent Skills (
SKILL.md) open standard. These integrations equip AI agents, such as Cursor and Claude Code, with workflows and domain expertise directly from Red Hat.By using these skills, you can help ensure that the AI-generated guidance aligns with RHEL standards, moving away from generic Linux advice toward recommended Red Hat methodologies.
- Best Practices Skill for RHEL focuses on proactive maintenance, system health, and troubleshooting. It provides the AI tool with a structured framework to assist with diagnosing complex RHEL environments.
Translator Skill for RHEL is designed for users migrating from other distributions or earlier systems. This skill translates general Linux concepts into RHEL-native equivalents.
For more information, see Best practices agent skill for Red Hat Enterprise Linux and Translator agent skill for Red Hat Enterprise Linux.
Jira:RHELDOCS-22164[1]
8.3. Developer Preview features identified in RHEL 10.1
Review Developer Preview features that were introduced in Red Hat Enterprise Linux 10.1.
8.3.1. RHEL Lightspeed
Review Developer Preview features introduced for RHEL Lightspeed in Red Hat Enterprise Linux 10.1.
- The
linux-mcp-serverfor Red Hat Enterprise Linux is available (Developer Preview) This Developer Preview introduces the
linux-mcp-serverfor Red Hat Enterprise Linux (RHEL), which is designed to bridge the gap between RHEL systems and large language models (LLMs). By using this Model Context Protocol (MCP) server, you can enable AI applications to perform context-aware troubleshooting on RHEL systems, including log and performance analysis. For more details, see Using the MCP server for RHEL to enable AI assistants to run, discover, and troubleshoot complex issues.Jira:RHELDOCS-21153[1]
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