Open source

Learn how to run OpenClaw on Red Hat OpenShift with production-grade security and observability. We cover default-deny network policies for blast radius containment, container-level sandboxing with OpenShift, Kubernetes Secrets for credential management, and end-to-end OpenTelemetry tracing with MLflow, so every decision your AI agent makes is isolated, auditable, and safe by default. Whether you're a developer exploring AI agents for the first time or a platform engineer thinking about running agentic workloads at scale, this is the infrastructure story that makes it production-ready.

Learn how to use Lola, a unified package manager for AI context. Treat your AI context as versioned, auditable code with Lola modules and marketplaces. Improve your AI assistant workflow with this open source tool.

Announcing a technology preview of Red Hat build of Perses in the cluster observability operator 1.4 for OpenShift and Red Hat Advanced Cluster Management consoles.

Learn how to set up and run a local AI audio transcription using an Red Hat open source model.

Learn how to manage the security threats and access controls associated with adopting the new Agent Skills functionality.

Learn how to run high-performance computing workloads managed by Slurm within a containerized OpenShift environment using the Slinky operator.

Learn about the RHEL Geospatial Data Abstraction Library (GDAL) compatibility package for geospatial workloads, a solution providing full functionality.

Explore big versus small prompting in AI agents. Learn how Red Hat's AI quickstart balances model capability, token costs, and task focus using LangGraph.

Learn how to deploy Voxtral Mini 4B Realtime, a streaming automatic speech recognition model for low-latency voice workloads, using Red Hat AI Inference Server.

Headed to DevNexus? Visit the Red Hat Developer booth on-site to speak to our expert technologists.

Learn how to use Crane to automatically convert your OpenShift BuildConfig resources to Builds for Red Hat OpenShift.

Headed to DeveloperWeek? Visit the Red Hat Developer booth on-site to speak to our expert technologists.

Take a look back at Red Hat Developer's most popular articles of 2025, covering AI coding practices, agentic systems, advanced Linux networking, and more.

Discover 2025's leading open models, including Kimi K2 and DeepSeek. Learn how these models are transforming AI applications and how you can start using them.

Learn how to implement retrieval-augmented generation (RAG) with Feast on Red Hat OpenShift AI to create highly efficient and intelligent retrieval systems.

Learn how to run privileged commands in OpenShift Dev Spaces cloud development environments more securely, using OpenShift sandboxed containers (Kata containers).

Most log lines are noise. Learn how semantic anomaly detection filters out repetitive patterns—even repetitive errors—to surface the genuinely unusual events.

What RHEL 8 and 9 users need to know about Python 3.9 reaching the end-of-life phase upstream.

Run the latest Mistral Large 3 and Ministral 3 models on vLLM with Red Hat AI, providing day 0 access for immediate experimentation and deployment.

Learn how to optimize AI inference costs with AWS Inferentia and Trainium chips on Red Hat OpenShift using the AWS Neuron Operator.

Simplify LLM post-training with the Training Hub library, which provides a common, pythonic interface for running language model post-training algorithms.

Learn why prompt engineering is the most critical and accessible method for customizing large language models.

Discover how LF Energy SEAPATH, an open source reference design for real-time platforms, is being used on RHEL to modernize electrical substation automation.

Now .NET 10 is available for RHEL and OpenShift, bringing new features like C# 14/F# 10 support, performance improvements, and updated APIs.

Learn how to use the new RHEL 10 soft reboot feature in image mode (bootc) to significantly reduce downtime for OS updates.