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Openshift 4.20: AI Workloads, Virtualization, and Zero Trust Security: Deploy Leaderworkerset, Openshift Lightspeed, Post-Quantum Crypto, and Producti
Paperback
Operating SystemsComputer SecuritySystem Administration
Publisher: Independently Published
Published: Jan 18 2026
Pages: 316
Weight: 1.21
Height: 0.66 Width: 7.00 Depth: 10.00
Language: English
Build production ready AI, virtualization, and zero trust clusters on OpenShift 4.20 with confidence.
Running LLM inference, GPU workloads, and virtual machines on the same Kubernetes platform is powerful, but it quickly becomes painful when drivers, storage, routing, and security are glued together ad hoc. Outages show up during upgrades, GPU nodes get overwhelmed, and auditors ask questions the platform cannot answer clearly.
This book gives you a complete, opinionated blueprint for OpenShift 4.20 that treats AI, OpenShift Virtualization, and zero trust security as first class concerns. Step by step, you move from a clean baseline cluster to GPU capable model serving, distributed LLMs, segmented VM workloads, and hardened identity and crypto that hold up in real incidents.
- Design node pools, MachineSets, and capacity plans that keep GPU, VM, and general workloads from colliding.
- Install and validate GPU enablement stacks, enforce realistic resource requests, and keep accelerators stable under load.
- Serve LLMs in production using OpenShift AI and vLLM, including batching, KV cache tuning, autoscaling, and resilience patterns.
- Use LeaderWorkerSet to run multi node, multi GPU distributed inference with predictable routing and failure handling.
- Choose storage patterns for models, datasets, and VM disks using object storage, PVCs, and CSI in ways that match throughput and recovery needs.
- Run OpenShift Virtualization alongside AI workloads with clear placement rules, live migration plans, and storage and networking guardrails.
- Route inference traffic safely with TLS, auth, rate limits, Gateway API routing, service mesh mTLS, and canary releases for new models.
- Adopt OpenShift Lightspeed for cluster operations in a controlled way, with scoped permissions and auditable data flow.
- Secure the AI supply chain, from image signing and artifact controls to secrets hygiene, egress policy, and network segmentation for model servers.
- Implement workload identity for zero trust using Workload Identity Manager, SPIFFE, CSI mounted identities, and OIDC based service to service auth.
- Plan for post quantum crypto and compliance by enforcing TLS profiles, crypto policies, PQC ready patterns, and FIPS aligned operation.
- Apply full reference builds for single node GPU serving, multi node LLM clusters with LeaderWorkerSet and ingress routing, and a virtualization enabled cluster with segmented networking.
- Use concrete production readiness checklists that cover SLOs, security controls, upgrades, disaster recovery, and failure drills.
This is a code heavy guide that includes realistic YAML, Shell, and configuration snippets you can adapt directly to your own OpenShift clusters.
Grab your copy today and turn OpenShift into a dependable platform for AI, virtualization, and zero trust workloads.
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