Automation and management

Learn about critical lessons from building an MCP-powered AI agent for ServiceNow, including how to structure testing environments, best practices for implementing safeguards, and a phased approach to deploying enterprise AI integrations.

Learn how to execute Red Hat Ansible Automation Platform automations in a hybrid environment using a cloud-hosted management cluster controlling on-premise bare-metal Red Hat OpenShift Virtualization clusters. This approach eliminates the need for dedicated execution nodes, leverages cloud-native capabilities, and reduces latency.

Learn how to implement an automated CI framework using Red Hat Ansible Automation Platform, Podman, and Horreum to measure the performance of etcd, the primary data store for Red Hat OpenShift cluster state and configuration. This framework provides early detection of performance impacts from both upstream Go releases and Red Hat-specific modifications, ensuring optimized, reliable builds that meet your performance and compliance requirements.

Discover how the Model Context Protocol server for Red Hat Lightspeed transforms the manual process of managing a RHEL fleet lifecycle into an AI-driven strategy.

Discover how OpenShift Commatrix CLI solves firewall misconfiguration in OpenShift by automatically generating ingress communication matrix for your specific cluster. Learn about key improvements over manual approach.

Learn how the multicluster global hub agent functions as an event exporter, solving large-scale multicluster challenges and enabling enterprise automation.

Explore the spending transaction monitor AI quickstart, demonstrating agentic AI for intelligent financial monitoring on enterprise-grade infrastructure. Lower the barrier to entry for AI experimentation and refine your AI strategy.

Explore the four pillars of AI coding: vibes, secs, skills, and agents, and learn how they can improve the coding quality and reduce the encoding/decoding gap. Discover the benefits of a spec-driven approach and the importance of modular specs and skills in achieving harmony.

Implement disaster recovery with storage replication and OpenShift APIs for Data

Learn how to integrate Red Hat Advanced Cluster Management with Argo CD for efficient application control. Discover how to use both push and pull models, and configure Argo CD to watch Policy resources.

Learn how to build reliable AI agents with our 8-stage evaluation framework. We explore DeepEval, multi-turn testing, and CI/CD integration for Red Hat AI.

Discover a solution for simplifying and automating the management of multi-network policies (MNP) at scale using Red Hat Advanced Cluster Management.

Announcing the Red Hat Advanced Cluster Management 2.16 general availability (GA) of namespace and virtualization right-sizing recommendations.

Learn how to build agentic AI workflows using cicaddy and MCP servers directly in your existing CI pipeline.

Learn how PatchPatrol, an AI-powered code review tool, helps enterprise development teams maintain high quality and security standards on Red Hat OpenShift.

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

Learn how the Responses API in Llama Stack automates complex tool calling while maintaining granular control over conversation flow for AI agents. Discover the benefits and implementation details.

The Dynamic Scoring Framework is an open source project that helps automate cluster scoring based on Prometheus metrics for intelligent workload distribution in multi-cluster environments. It acts as a bridge between your monitoring system and the Placement API, continuously evaluating clusters and updating their scores. The framework consists of three key components: DynamicScorer, DynamicScoringConfig, and DynamicScoringAgent.

Discover how I used an AI assistant to develop a production-grade Ansible Playbook to audit RHEL versions across a fleet of servers, generating a clean report.

Discover what’s new in cloud automation with amazon.aws 11.0.0 and a major update to the Red Hat Ansible Certified Content Collection for AWS.

This guide shows how to stop managing storage users by hand and start using a GitOps approach to do it automatically.

Learn about the improvements and capabilities of Red Hat OpenShift Service on AWS with hosted control planes, including alert routing, operator observability, metrics retention, ease of compute configuration, and cost savings. Get started now.

Learn how hosted control planes reduce costs without compromising performance by using intelligent scaling.

Learn how to fine-tune AI pipelines in Red Hat OpenShift AI 3.3. Use Kubeflow Trainer and modular components for reproducible, production-grade model tuning.

OpenShift networking moves to real routing (CUDN/BGP), eliminating NAT and Geneve tunnels for better performance, L3 integration, and full visibility.