Draft a rollback and hot-patch deployment runbook for pushing zero-downtime security patches to containerized AI inference services running on customer-managed OpenShift clusters in PCI-DSS environments

Generate draft a rollback and hot-patch deployment runbook for pushing zero-downtime security patches to containerized ai inference services running on customer-managed openshift clusters in pci-dss environments for Computer Systems Design and Related Services industry

Computer Systems Design and Related Services

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Current OpenShift cluster security posture report including PCI-DSS compliance status, vulnerability scans, and existing patch levels
Select the scope and rigor level for evaluating patch impact on AI inference services
Define the review and approval process required for patch deployment
Specify maintenance windows, global operational hours, and blackout periods for zero-downtime deployment
Define specific technical and business thresholds that trigger automatic rollback including model accuracy degradation, latency increases, and security scan failures
Select specific PCI-DSS requirements that must be validated post-patch deployment
Define the service level agreement parameters that govern patch deployment urgency and rollback behavior
List critical AI inference service characteristics including model size, GPU requirements, memory constraints, and multi-model dependencies
Specify cluster configuration details including version, node architecture, platform operators, and custom security policies
Define how deployment status, rollback decisions, and incident communications are handled