TL;DR NSX microsegmentation is most useful when it is treated as a workload protection system, not simply as another firewall. The distributed firewall places policy close to protected workloads, while

Continue ReadingThe NSX Microsegmentation Vault: Protecting Every Workload with Distributed Firewall Policy

TL;DR Enterprise AI is not a feature that lives neatly inside one cloud, one cluster, or one vendor console. It is a distributed system that depends on physical infrastructure, network

Continue ReadingThe Living Internet: Why Enterprise AI Is a Hybrid Cloud and Edge Architecture Problem

TL;DR An enterprise can build prompt filters, model gateways, audit pipelines, fallback providers, cost controls, and kill switches, yet still be exposed if its AI vendor agreement permits broad data

Continue ReadingThe AI Contract Is Part of the Architecture: 12 Clauses CIOs Need Before Agentic Scale

TL;DR The underwater cloud city in the image is a useful architecture metaphor, but it should not be read as a literal bill of materials. Azure Local and VMware Cloud

Continue ReadingAzure Local and VMware Cloud Foundation: The Shared Operating Model Beneath a Resilient Hybrid Cloud

TL;DR Sanctioned AI agents can create the same portfolio problems as shadow technology: duplicated capabilities, conflicting actions, unmanaged dependencies, excessive token spend, orphaned identities, and operational debt. The answer is

Continue ReadingThe Agent Sprawl Crisis: How CIOs Should Register, Consolidate, and Retire Digital Workers

TL;DR A network packet contains a limited set of facts, such as addresses, ports, protocol information, flags, and payload data. The security decision surrounding that packet can be far larger.

Continue ReadingThe World Inside a Single Packet: How NSX Gateway Firewall Turns Traffic into a Policy Decision

TL;DR AI adoption data is not the same as productivity evidence. Licenses assigned, active Copilot users, prompts submitted, tokens consumed, suggestions accepted, and lines of code generated can show that

Continue ReadingThe AI Productivity Measurement Trap: Why Token Counts, Copilot Usage, and Code Volume Can Mislead the Board

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

Continue ReadingWhy Mirantis k0rdent AI Is the AI Factory Operating Layer the Market Has Been Missing