Data science

Learn how to overcome compatibility challenges when deploying OpenShift AI and OpenShift Service Mesh 3 on one cluster.

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

Learn how to build a Model-as-a-Service platform with this simple demo. (Part 3 of 4)

This article introduces Models-as-a-Service (MaaS) for enterprises, outlining the challenges, benefits, key technologies, and workflows. (Part 1 of 4)

Learn how to secure, observe, and control AI models at scale without code changes to simplify zero-trust deployments by using service mesh.

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

Deploy AI at the edge with Red Hat OpenShift AI. Learn to set up OpenShift AI, configure storage, train models, and serve using KServe's RawDeployment.

Members from the Red Hat Node.js team were recently at PowerUp 2025. It was held

Discover how IBM used OpenShift AI to maximize GPU efficiency on its internal AI supercomputer, using open source tools like Kueue for efficient AI workloads.

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

Learn how to use pipelines in OpenShift AI to automate the full AI/ML lifecycle on a single-node OpenShift instance.

Learn how to set up NVIDIA NIM on Red Hat OpenShift AI and how this benefits AI and data science workloads.

Learn how the dynamic accelerator slicer operator improves GPU resource management in OpenShift by dynamically adjusting allocation based on workload needs.

Explore how Red Hat Developer Hub and OpenShift AI work together with OpenShift to build workbenches and accelerate AI/ML development.

This article demystifies AI/ML models by explaining how they transform raw data into actionable business insights.

Learn how to integrate NVIDIA NIM with OpenShift AI to build, deploy, and monitor AI-enabled applications efficiently within a unified, scalable platform.

Podman AI Lab, which integrates with Podman Desktop, provides everything you need to start developing Node.js applications that leverage large language models.

Discover Sparse Llama: A 50% pruned, GPU-optimized Llama 3.1 model with 2:4 sparsity, enabling faster, cost-effective inference without sacrificing accuracy.

Explore how vLLM's new multimodal AI inference capabilities enhance performance, scalability, and flexibility across diverse hardware platforms.

Learn how to securely integrate Microsoft Azure OpenAI Service with Red Hat OpenShift Lightspeed using temporary child credentials.

Learn how to build a ModelCar container image and deploy it with OpenShift AI.

Learn how to integrate Model Context Protocol (MCP) with LLMs using Node.js

Integrating large language models into applications is an important skill for

This year's top articles on AI include an introduction to GPU programming, a guide to integrating AI code assistants, and the KServe open source project. 

In our previous blog post, we introduced the RamaLama project, a bold initiative