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Celebrate our mascot Repo's first birthday with us as we look back on the events that shaped Red Hat Developer and the open source community from the past year.

This learning path explores running AI models, specifically large language

Simplify container image management with Skopeo. Get practical examples for faster image inspection, single-command pushing, and mirroring multiple registries.

Walk through how to set up KServe autoscaling by leveraging the power of vLLM, KEDA, and the custom metrics autoscaler operator in Open Data Hub.

Enhance your Python AI applications with distributed tracing. Discover how to use Jaeger and OpenTelemetry for insights into Llama Stack interactions.

Discover the vLLM Semantic Router, an open source system for intelligent, cost-aware request routing that ensures every token generated truly adds value.

Red Hat's Developer Subscription for Teams gives organizations easy access Red Hat Enterprise Linux for their development activities.

This is a guide that demonstrates how to implement and test container signature verification in a disconnected OpenShift 4.19 cluster.

As GPU demand grows, idle time gets expensive. Learn how to efficiently manage AI workloads on OpenShift AI with Kueue and the custom metrics autoscaler.

Llama Stack offers an alternative to the OpenAI Responses API, enabling multi-step agents, RAG, and tool use on your own infrastructure with any model.

See how a custom MCP client for Docling transformed unstructured data into usable content, reducing document prep time by over 80%.

Learn how vLLM outperforms Ollama in high-performance production deployments, delivering significantly higher throughput and lower latency.

Enterprise-grade artificial intelligence and machine learning (AI/ML) for

Learn about the advantages of prompt chaining and the ReAct framework compared to simpler agent architectures for complex tasks.

Discover how Bunsen tracks and analyzes large and busy upstream projects.

Discover the comprehensive security and scalability measures for a Models-as-a-Service (MaaS) platform in an enterprise environment.

This beginner's guide to Podman AI Lab walks through setting up Podman Desktop, installing the AI Lab extension, and launching your first RAG chatbot.

RamaLama's new multimodal feature integrates vision-language models with containers. Discover how it helps developers download and serve multimodal AI models.

Learn how to control the output of vLLM's AI responses with structured outputs. Discover how to define choice lists, JSON schemas, regex, and more.

Learn how Podman AI Lab and RamaLama work together to simplify local AI model execution, using containers and GPU support for faster, easier AI development.

Explore how to utilize guardrails for safety mechanisms in large language models (LLMs) with Node.js and Llama Stack, focusing on LlamaGuard and PromptGuard.

MINC is a new Podman Desktop extension that eases local Kubernetes development, offering a streamlined local Kubernetes experience powered by MicroShift.

PowerUP 2025 is the week of May 19th. It's held in Anaheim, California this year

LLM Compressor bridges the gap between model training and efficient deployment via quantization and sparsity, enabling cost-effective, low-latency inference.