VMware Explore 2026 ran from August 31 to September 3 in Las Vegas. The official closing recap reports more than 4,700 attendees and 400 sessions. The announcements cover private AI infrastructure, agent security, application delivery and cloud costs.
VMware Cloud Foundation (VCF) 9.1 was announced in May. VCF 9.1.1 became generally available on September 3. The sessions cover both the existing platform and the additions announced around Explore.
The announcements position VCF as a shared platform for conventional applications, models and agents. Putting an AI workload into production brings specific decisions: what data it can use, how much capacity it needs, and how it will be supported when something fails. Those decisions require agreement between the infrastructure, application and data teams.
- Data access and location
- Capacity and budget
- Agent permissions
VMware Cloud Foundation
- Named service owners
- Measured performance and cost
- Tested recovery and controls
// TAKEAWAY 01
Start with an AI operating model
The problem
A production AI workload needs accelerators, a model endpoint and access to data. It also needs owners for patching, identity, model access, recovery and cost. These responsibilities often span infrastructure, application and data teams. Agree on them before deployment so support does not depend on finding the right person during an incident.
At Explore
The VMware Private AI Cloud announcement describes VCF as the infrastructure for virtual machines, Kubernetes, data services and model serving. The aim is to manage lifecycle, policy, monitoring and costs across those workloads. VCF 9.1.1 adds some of the capabilities discussed at Explore; other parts of the Private AI Cloud announcement remain planned. Each deployment still needs a check against the relevant product release.
Sources: VMware Private AI Cloud · VCF 9.1.1 GA
What to do next
Choose an AI workload scheduled for production. List its compute, data, model serving, identity, network, recovery and monitoring requirements. Assign an owner and a service target to each, including cost. Resolve gaps in ownership before the pilot becomes a production service.
Check first. Check the availability and licensing of each required capability. The Private AI Cloud announcement covers multiple products and release schedules.
Related sessions
// TAKEAWAY 02
Plan capacity beyond GPUs
The problem
GPU capacity is only part of an AI workflow. Agents also retrieve context, apply policy, call tools, wait for APIs and evaluate results. CPU, memory, network or data service limits can delay those steps even when GPU capacity is available. Sizing needs to account for the complete workflow.
At Explore
The VMware AI Factory announcement covers model serving and infrastructure operations. The session descriptions discuss pooled accelerators, mixed compute, time to first token, throughput and utilization. The Private AI Services architecture session compares managed model services, VMware vSphere Kubernetes Service (VKS) and Deep Learning VMs. The validated-model program adds supported models, each of which still needs testing against workload requirements.
Sources: VMware AI Factory · validated models · AI innovations in VCF
- Retrieve context
Data services
- Apply policy
Control plane
- Model inference
Accelerators
- Tools + evaluate
CPU, network, APIs
What to do next
Measure inference and the surrounding agent workflow separately in a pilot. Record time to first token, tokens per second, GPU utilization, CPU time spent in orchestration, retrieval latency and cost per completed workflow. Use those measurements to size the next deployment.
Check first. Test the model, quantization, context length, data path and concurrency pattern you plan to use. Model validation alone does not establish performance on your data.
Related sessions
// TAKEAWAY 03
Give agents identities and boundaries
The problem
An agent can choose which tool to call and what data to pass to it. A service account identifies the caller, but the system also needs to check whether each action is permitted. Model Context Protocol (MCP) connects agents to tools and data. Those connections need owners, access controls and records of what the agent did.
At Explore
The AgentMinder announcement describes controls for agent identity and actions. It evaluates actions against mission, intent, tools, resources and risk, with traces for later review. The MCP administration session covers the infrastructure that connects agents to enterprise systems. The announcements also describe agent-aware vDefend, Avi, gateway and framework controls. Several of those capabilities are planned for future releases.
Sources: AgentMinder · agentic security
- Agent / model
Identity + mission
- Action decision
Allow · deny · escalate
- Tools / MCP
Explicit permissions
- Enterprise data
Scoped access
What to do next
Choose a low-risk internal agent and document its permissions before granting tool access. Define its purpose, allowed tools, data access, behavior after a denial, escalation contact and audit fields. Test permitted and prohibited tasks. Check that denials work and that the records explain each tool call.
Check first. Use controls available in the pilot environment to enforce permissions. Planned agent security features cannot provide protection until they are deployed.
Related sessions
// TAKEAWAY 04
Make self-service governable
The problem
A self-service portal can provision a cluster while leaving developers to arrange policy checks, deployment and monitoring. Teams need a supported process that covers all of these steps. Agent-assisted development increases the need for automated checks because agents can submit changes faster than people can review them manually.
At Explore
The application modernization sessions cover VKS, GitOps and Tanzu in software delivery. The agentic SDLC tutorial follows work items through source changes, governed MCP services and deployment. The new Tanzu AI data and agent capabilities are planned for general availability in Fall 2026. TrueSource provides commercially supported, verifiably built open-source artifacts. These address two practical needs: controlling how code reaches production and checking the origin of its dependencies.
Sources: Tanzu AI-ready data foundations · TrueSource
- Approved work item
Intent and owner
- Source and policy
Checks before merge
- Deployment
GitOps, supported runtime
- Runtime evidence
Monitoring and rollback
What to do next
Build a supported delivery process for a small internal service, from an approved work item to deployment and monitoring. Measure delivery time, manual handoffs and policy failures caught before release. Test recovery after a failed change, then automate the steps causing the most delay or rework.
Check first. Assign owners for versions, policy, upgrades, rollback and support. Developers need to know which parts of the process the platform team maintains.
Related sessions
// TAKEAWAY 05
Move security inside the workload
The problem
Perimeter controls do not cover every connection between internal workloads. They also cannot determine whether an agent used an approved tool for an authorized purpose. Teams need to understand traffic between applications before restricting it. That applies to conventional applications as well as new AI services.
At Explore
The vDefend journey session describes four stages: protect shared services, segment broad environments, secure application tiers and restrict the remaining traffic. The security announcements add plans for discovery and protection of MCP, agents and AI data paths. Existing segmentation controls can support work today; the planned agent-aware features have separate availability requirements.
Sources: end-to-end agentic security
- Shared services
DNS, identity, NTP
- Environment zones
Production, test, dev
- Application tiers
Web, app, data
- Remaining traffic
Default deny
What to do next
Choose an application or shared service. Record its normal traffic, identify dependencies and test a limited set of segmentation rules. Measure policy coverage, unexpected connections, change effort and incident investigation time. Test rollback before expanding the policy.
Check first. Observe traffic before enforcing rules. Record planned agent security features as outstanding requirements until they are available and deployed.
Related sessions
// TAKEAWAY 06
Put cloud economics into the architecture review
The problem
Cloud cost comparisons often use different assumptions. A public cloud estimate may assume steady demand, while a private cloud estimate may count hardware but omit operating costs. An AI pilot may report GPU hours without including model usage, data movement or idle capacity. Those omissions can change the placement decision.
At Explore
The VCF FinOps sessions cover resource consumption, cost drivers, rate cards, showback and chargeback. ValueOps covers comparisons across private and public clouds, including AI token costs. The vSAN session covers compression, deduplication and automation, which also affect the cost of running workloads.
- Same service outcome
Service level, resilience
- Full cost inputs
Utilization, egress, tokens
- Placement options
Private, public, hybrid
- Revisit at 30 days
Variance sets the rule
What to do next
Compare the cost of running a representative workload in each suitable location. Use the same service and resilience requirements, and include utilization, data egress, licensing, migration, operating labor and token consumption. After thirty days of representative use, compare actual costs with the estimate and revise the placement decision if needed.
Check first. Document the measurement period, utilization assumptions, risk allowance and migration costs. A comparison is only useful if these assumptions are consistent.
Related sessions
Own Your Cloud Costs: FinOps Capabilities in VMware Cloud Foundation
Kelcey Lemon · Sujatha David
Mastering the Hybrid Estate: Strategy for Public Clouds and VMware Cloud Foundation with ValueOps by Broadcom
Emma Price · Francois Cattoen
What’s New in VMware vSAN for VMware Cloud Foundation 9.1
Pete Koehler · Junchi Zhang
// CHECK THE DEPENDENCIES
Availability and planned releases
Record the status of each dependency in the pilot design. A committed delivery date needs a fallback for anything still in preview or planned. These labels reflect the official announcements as of September 5, 2026.
✓ Available / GA
- VMware Cloud Foundation 9.1.1
Generally available on September 3, 2026.
- Multi-tenant Model Sharing
Generally available with VCF 9.1.1.
- AgentMinder
Announced as generally available on August 31, 2026.
- TrueSource
Listed as available for supported open-source artifacts.
◇ Technical preview
- Native Argo CD GitOps service
Introduced as a technical preview in VCF 9.1.1.
- vSAN Object Storage
A previously announced technical preview, not a new GA service at Explore.
→ Announced / future
- VCF Private AI Services: AI Gateway, Secure Agent Framework and Model Autoscaling
Described as capabilities planned for future releases.
- New agent-aware vDefend and Avi controls
Agent discovery, shadow AI monitoring, AI-generated IDPS signatures, tool misuse prevention and sensitive-data protection were announced; no availability date was stated.
- Tanzu Platform AI data and agent capabilities
General availability planned for Fall 2026.
THE BOTTOM LINE
Plan a pilot
Choose a workload with a named owner and agreed service requirements. Measure the complete workflow, test permissions and recovery, and track its operating costs. Record where the available products meet those requirements and where additional work is needed.
Use those results to decide what to deploy next. Any production plan that depends on a preview or future release needs an alternative if that capability is delayed.
// WHERE TO START
Six sessions to open first.
These six sessions cover the main topics above. Durations are taken from the official video library.
// SOURCE NOTES
Official announcements and further reading
The official library listed 189 recordings on September 5, 2026. This article draws on the published descriptions of eleven sessions and the official announcements linked below.
- VMware Explore 2026 video library
- VMware Explore 2026 Las Vegas: Day 4 recap
- VMware Explore 2026 Las Vegas media kit
- Broadcom introduces VMware Private AI Cloud
- Broadcom announces VMware AI Factory
- VMware Cloud Foundation brings leading AI models to private AI
- AI-ready data foundations for VMware Tanzu Platform
- AgentMinder enterprise solution for AI agent governance
- End-to-end security, identity and observability for agentic AI
- TrueSource supported open-source software
- VMware Cloud Foundation 9.1.1 generally available
- VMware AI Factory and other AI innovations in VCF