APIs

AI agents are where things get exciting! In this episode of The Llama Stack Tutorial, we'll dive into Agentic AI with Llama Stack—showing you how to give your LLM real-world capabilities like searching the web, pulling in data, and connecting to external APIs. You'll learn how agents are built with models, instructions, tools, and safety shields, and see live demos of using the Agentic API, running local models, and extending functionality with Model Context Protocol (MCP) servers.Join Senior Developer Advocate Cedric Clyburn as we learn all things Llama Stack! Next episode? Guardrails, evals, and more!

Explore a fashion AI search on Red Hat OpenShift AI with EDB Postgres AI.

Learn how to integrate Ansible Automation Platform with Red Hat Advanced Cluster Management for centralized authentication across multiple clusters.

Building AI applications is more than just running a model — you need a consistent way to connect inference, agents, storage, and safety features across different environments. That’s where Llama Stack comes in. In this second episode of The Llama Stack Tutorial Series, Cedric (Developer Advocate @ Red Hat) walks through how to:- Run Llama 3.2 (3B) locally and connect it to Llama Stack- Use the Llama Stack server as the backbone for your AI applications- Call REST APIs for inference, agents, vector databases, guardrails, and telemetry- Test out a Python app that talks to Llama Stack for inferenceBy the end of the series, you’ll see how Llama Stack gives developers a modular API layer that makes it easy to start building enterprise-ready generative AI applications—from local testing all the way to production. In the next episode, we'll use Llama Stack to chat with your own data (PDFs, websites, and images) with local models.🔗 Explore MoreLlama Stack GitHub: https://github.com/meta-llama/llama-stackDocs: https://llama-stack.readthedocs.io5.

Learn how Red Hat has re-architected the REST API to provide direct and efficient access to event notifications, complying with the latest O-RAN standards.

Runtimes, frameworks, and services to build applications natively on Red Hat OpenShift.

Learn how to use Cryostat 4.0’s Kubernetes API discovery configurations with Quarkus-native image applications, leveraging GraalVM's JFR and JMX observability feature support.

Everything you need to coordinate microservices in a service mesh with powerful

Red Hat build of Apache Camel 4.10 brings enhanced integration components, unified observability, expanded cloud and messaging support, and more.

Fill out the form to request early access to Red Hat Connectivity Link

Learn how to receive notifications about the status of Red Hat's services.

This video demonstrates how to protect the signing data produced by the Red Hat Trusted Artifact Signer using the OADP (OpenShift APIs for Data Protection) Operator.

Explore this year's most popular articles on Kafka data storage and migration, API management, software security, identity and access management, and more.

Red Hat build of Apache Camel 4.8 brings enhancements in contract-first API development, optimized OpenShift-based workflows, and improved developer tooling.

Connect, secure, and protect your distributed Kubernetes services with

Runtimes and APIs for building and running .NET applications on Linux and in

The first article in a series exploring the journey of building an IDP using Red Hat Developer Hub, a platform based on Backstage, to streamline development workflows and boost team productivity.

The Kuadrant open source project helps platform engineers and developers connect, secure, and protect services and infrastructure across multiple clusters.

Agile, distributed, containerized, and API-centric solution to integrate