Operate Kubernetes as a service application teams can depend on. Define workload profiles, service objectives, upgrade evidence, disruption capacity, and recovery criteria before expanding the platform.
TL;DR The AI infrastructure market has spent too much time treating GPU acquisition, Kubernetes deployment, workload scheduling, model serving, and platform governance as separate purchases. Enterprises and neoclouds do not experience them separately. They experience the gaps between them, where driver mismatches, operator ordering, network configuration, tenant policy, lifecycle ownership, and support boundaries turn expensive … Explore: Why Mirantis k0rdent AI Is the AI Factory…
TL;DR AI coding tools are reducing the effort required to produce software, but they are not removing the work required to make software safe, supportable, observable, and valuable. The constraint is moving downstream into architecture review, test design, security analysis, release governance, documentation, production operations, and cost control. CIOs should not treat lines of code, … Explore: Code Abundance, Operational Scarcity: Why AI-Generated Software Is…
TL;DR The CIO’s AI operating model cannot stop at selecting models, deploying copilots, or funding agent pilots. It must define how a human-agent workforce makes decisions, executes work, owns outcomes, operates platforms, handles exceptions, and responds when an AI-enabled process fails. The durable model is centralized control with federated business ownership. Employees retain judgment, accountability, … Explore: The Human-Agent Operating Model: How CIOs Should Redesign…
TL;DR Neoclouds may begin by selling access to scarce GPU capacity, but long-term differentiation requires more than racks, drivers, and a booking portal. A production AI cloud must convert bare-metal servers, virtual machines, GPU pools, storage, networks, and external cloud resources into secure, repeatable, tenant-aware services. The missing layer is vendor-neutral AI infrastructure orchestration. It … Explore: GPUs Are Not a Cloud: Why Neoclouds Need…
TL;DR VCF Protection and Recovery 9.1 changes disaster recovery from a service that infrastructure administrators configure manually into a capability that organization administrators, project administrators, and authorized users can consume through VCF Automation. That does not mean every tenant should be allowed to create arbitrary replication relationships, reserve unlimited recovery capacity, or initiate a production … Explore: Self-Service Disaster Recovery with VCF Automation: Multi-Tenant Protection…
TL;DR Platform engineering is becoming a CEO-level productivity strategy because software delivery is now a direct constraint on revenue, customer experience, operational change, regulatory response, and AI adoption. A well-designed internal developer platform reduces repeated engineering work, shortens delivery queues, embeds security and reliability controls, and gives product teams a supported path from idea to … Explore: Why Platform Engineering Is Becoming a CEO-Level Productivity…
