Runtimes

Learn how to deploy and optimize Red Hat Data Grid for cross-site replication in OpenShift. Discover three deployment approaches, JGroups cross-site communication, and solutions to common challenges.

Learn how to diagnose and address application misbehavior after a Red Hat OpenShift upgrade, with a focus on container awareness.

Discover a practical and reproducible methodology for latency-sensitive DPDK workloads running on bare-metal OpenShift.

Red Hat Customer Portal now offers Temurin JDK 25 for 64-bit Windows, providing another supported, production-ready option for running Java on Windows.

Discover the RHEL 10.1 new features and updates, designed to improve the developer experience.

Your Red Hat Developer membership unlocks access to product trials, learning resources, events, tools, and a community you can trust to help you stay ahead in AI and emerging tech.

Red Hat build of Quarkus 3.27 offers enhanced data handling, observability, and

Learn how to choose between Apache Artemis and Apache Kafka, messaging systems to meet your transactional, batch, and real-time data streaming needs.

Dive into Node.js 20's container-aware memory management. Understand default heap sizing, how to override it, and troubleshooting memory leaks.

Welcome back to Red Hat Dan on Tech, where Senior Distinguished Engineer Dan Walsh dives deep on all things technical, from his expertise in container technologies with tools like Podman and Buildah, to runtimes, Kubernetes, AI, and SELinux! In this episode, Eric Curtin joins to discuss Sorcery AI, a new AI code review tool that has been helping to find bugs, review PRs, and much more!

Deploy DialoGPT-small on OpenShift AI for internal model testing, with step-by-step instructions for setting up runtime, model storage, and inference services.

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

Learn how to implement Llama Stack's built-in guardrails with Python, helping to improve the safety and performance of your LLM applications.

Discover how to use the security benefits of confidential computing in OpenShift Pipelines to run trusted builds on untrusted and shared infrastructure.

This tutorial shows you how to use the Llama Stack API to implement retrieval-augmented generation for an AI application built with Python.

Learn how to deploy .NET applications in OpenShift Container Platform 4, along with .NET troubleshooting steps.

Explore JVM tuning considerations for Red Hat Data Grid on Red Hat OpenShift 4, from allocating adequate CPU resources to benchmarking your application.

Harness Llama Stack with Python for LLM development. Explore tool calling, agents, and Model Context Protocol (MCP) for versatile integrations.

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

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

More Essential AI tutorials for Node.js Developers

Get an introduction to AI function calling using Node.js and the LangGraph.js framework, now available in the Podman AI Lab extension.

Red Hat build of Quarkus 3.20 offers enhanced observability, a modern WebSocket extension, and performance optimizations for faster, native-ready applications.

Things that are essential to know about the Red Hat build of Node.js.

A listing of Essential Node.js Observability Posts from Red Hat Developer and