{"id":73276,"date":"2026-05-06T10:12:25","date_gmt":"2026-05-06T08:12:25","guid":{"rendered":"https:\/\/www.schneider.im\/?p=73276"},"modified":"2026-05-06T10:12:25","modified_gmt":"2026-05-06T08:12:25","slug":"how-vcf-9-0-and-microsoft-azure-work-together-hybrid-cloud-done-right","status":"publish","type":"post","link":"https:\/\/www.schneider.im\/lu\/how-vcf-9-0-and-microsoft-azure-work-together-hybrid-cloud-done-right\/","title":{"rendered":"How VCF 9.0 and Microsoft Azure Work Together: Hybrid Cloud Done Right"},"content":{"rendered":"

Cloud strategy is no longer\u00a0an either-or decision<\/strong>. Most organizations need\u00a0both a private datacenter and a public cloud<\/strong>, so each application can run\u00a0where it performs best and costs the least<\/strong>.\u00a0Customers have asked us how to structure a successful hybrid approach, so here is a solid solution:<\/p>\n

VMware Cloud Foundation (VCF) 9.0<\/strong>\u00a0is the software that powers a company\u2019s\u00a0private datacenter<\/strong>.\u00a0Microsoft Azure<\/strong>\u00a0is Microsoft\u2019s\u00a0public cloud<\/strong>\u00a0that rents computing power, storage, and AI services over the internet. The two are\u00a0designed to work together <\/strong>and complement each other<\/strong>.<\/p>\n

This article explains, how\u00a0VCF 9.0 and Microsoft Azure<\/strong>\u00a0combine to\u00a0cut costs<\/strong>, reduce<\/strong> complexity<\/strong> and maximize value<\/strong>.<\/p>\n

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 <\/p>\n

Why is the hybrid cloud more crucial than ever before?<\/h2>\n

A few years ago, many companies believed they should move\u00a0everything<\/strong>\u00a0into the public cloud. While the public cloud remains the main option, it is not an either-or-decision: Today, most enterprises run a\u00a0mix of both worlds<\/strong>, because each side has clear strengths and clear limits.<\/p>\n

Enterprises now face several\u00a0persistent challenges<\/strong>:<\/p>\n

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  • Different workloads belong in different places<\/strong>\n
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    • Some applications run\u00a0better on-premises<\/strong>: for example, when they need fast response times, must follow strict regulations, or have steady, predictable usage that is cheaper to host in your own datacenter (which has become more seldom with increased hardware costs since 2025).<\/li>\n
    • Other applications run\u00a0better in a public cloud<\/strong>: for example, when demand swings up and down, when users are spread around the world, or when modern AI services are needed.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
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      • AI is changing infrastructure decisions<\/strong>\n
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        • Sensitive company and customer data<\/strong>\u00a0often must stay inside the company\u2019s own walls for legal or privacy reasons. At the same time,\u00a0Azure AI services<\/strong>\u00a0have become important productivity tools. Both needs have to be served.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
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          • Operational complexity must be reduced<\/strong>\n
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            • Running\u00a0two completely separate technology stacks<\/strong>\u00a0(one on-premises, one in the cloud) is expensive and slow. Customers want\u00a0one consistent way of working<\/strong>\u00a0that covers both.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
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              • Skilled people are scarce<\/strong>\n
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                • A hybrid model only works if the on-premises and cloud sides\u00a0use the same tools and the same skills<\/strong>. This alignment of tools reduces the need for completely separate skillsets.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n

                  In practice this means:<\/p>\n

                    \n
                  • Pure public cloud<\/strong>\u00a0can create compliance issues in heavily regulated or sensitive environments.<\/li>\n<\/ul>\n
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                    • Pure on-premises<\/strong>\u00a0misses out<\/strong>\u00a0on the global reach, flexibility and AI services that Azure provides.<\/li>\n<\/ul>\n
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                      • Hybrid done right<\/strong>\u00a0requires\u00a0real expertise on both platforms<\/strong>\u00a0so that the two halves behave like one system.<\/li>\n<\/ul>\n

                        Under these conditions,\u00a0integrating VCF 9.0 with Microsoft Azure<\/strong>\u00a0becomes a\u00a0primary value lever<\/strong>\u00a0for the business. Let’s explore how you can combine these two solutions to get the best of both worlds:<\/p>\n

                        \"\"<\/p>\n

                         <\/p>\n

                        How VMware Cloud Foundation (VCF) 9.0 and Microsoft Azure work together<\/h2>\n

                        1) Run VMware natively in Azure with Azure VMware Solution (AVS)<\/h3>\n

                        \"\"<\/p>\n

                        Azure VMware Solution (AVS)<\/strong>\u00a0is a\u00a0Microsoft service inside Azure<\/strong>\u00a0that runs\u00a0VMware Cloud Foundation directly on Microsoft\u2019s own datacenters<\/strong>. It uses the\u00a0same building blocks<\/strong>\u00a0your IT team already knows from on-premises:\u00a0vSphere, vSAN, and NSX<\/strong>.<\/p>\n

                        In simple terms:\u00a0vSphere<\/strong>\u00a0is the engine that runs\u00a0virtual computers<\/strong>.\u00a0vSAN <\/strong>takes the hard drives sitting inside your servers and combines them into one big shared storage pool, so every virtual computer can use the same space.\u00a0NSX<\/strong>\u00a0handles\u00a0networking and security<\/strong>\u00a0between those virtual computers.<\/p>\n

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                         <\/p>\n

                        Maximize value through consistency<\/h4>\n
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                        • No application rewrite when moving to Azure<\/strong>\n
                            \n
                          • A\u00a0virtual machine (VM)<\/strong>\u00a0is a\u00a0software-based computer<\/strong>\u00a0that runs on top of physical hardware. With<\/strong> AVS<\/strong>, those VMs<\/strong>\u00a0move to Azure as they are<\/strong>: you need almost no code changes, re-engineering, or re-testing of every application.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
                              \n
                            • Same skills on both sides<\/strong>\n
                                \n
                              • Administrators use the\u00a0identical tools and dashboards<\/strong> on-premises and in Azure. That significantly reduces additional training needs compared to heterogeneous stacks.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n

                                \"\"<\/p>\n

                                  \n
                                • Disaster recovery and burst capacity become simple<\/strong>\n
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                                  • Workloads can\u00a0fail over to Azure<\/strong>\u00a0during an outage, or\u00a0temporarily expand into Azure<\/strong>\u00a0when demand spikes. This works without building and paying for a second physical datacenter.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n

                                    \"\"<\/p>\n

                                    Result:\u00a0lower migration risk<\/strong>\u00a0and\u00a0faster cloud adoption<\/strong>, while keeping the existing on-premises VCF investment fully usable.<\/p>\n

                                     <\/p>\n

                                    2) Manage everything in one place with Azure Arc<\/h3>\n

                                    \"\"<\/p>\n

                                    Azure Arc<\/strong>\u00a0is a\u00a0Microsoft management layer<\/strong>\u00a0that\u00a0extends Azure governance, policies, security, and monitoring<\/strong>\u00a0to systems that are\u00a0not inside Azure<\/strong>\u00a0(including a VCF 9.0 environment that runs on-premises).<\/p>\n

                                    Azure Arc acts as the\u00a0cockpit<\/strong>\u00a0from which everything is configured and watched. The actual workloads keep running where they are; only the\u00a0management view becomes one<\/strong>.<\/p>\n

                                    Reduce complexity through unified management<\/h4>\n
                                      \n
                                    • Single inventory across VCF and Azure<\/strong>\n
                                        \n
                                      • Servers, virtual machines,\u00a0Kubernetes clusters<\/strong>\u00a0(the standard environment for modern container-based applications), and SQL databases all appear in\u00a0one Azure portal view<\/strong>. This eliminates the need to log into separate tools.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
                                          \n
                                        • Consistent policy enforcement<\/strong>\n
                                            \n
                                          • Security baselines, naming and tagging rules apply the same way\u00a0no matter where the workload runs<\/strong>.\u00a0The same goes for Role-Based Access Control (RBAC)<\/strong>, which defines who is allowed to do what.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
                                              \n
                                            • Centralized monitoring and security<\/strong>\n
                                                \n
                                              • Azure Monitor<\/strong>\u00a0(the central health and performance dashboard) and\u00a0Microsoft Defender for Cloud<\/strong>\u00a0(the central security tool) keep an eye on\u00a0both<\/strong>\u00a0the on-premises VCF estate\u00a0and<\/strong>\u00a0the Azure estate.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n

                                                Result:\u00a0lower operational complexity<\/strong>\u00a0and a\u00a0stronger compliance posture<\/strong>, without forcing any workload to move.<\/p>\n

                                                 <\/p>\n

                                                3) Run AI workloads end-to-end with VCF Private AI Foundation and Azure AI<\/h3>\n

                                                \"\"<\/p>\n

                                                VCF 9.0<\/strong>\u00a0includes\u00a0VMware Private AI Foundation with NVIDIA<\/strong>, which lets companies\u00a0run AI models on their own hardware<\/strong>, using\u00a0sensitive internal data<\/strong>\u00a0that should never leave the building.\u00a0Microsoft Azure<\/strong>\u00a0adds the\u00a0complementary side<\/strong>\u00a0(Azure OpenAI, Azure AI Foundry, and Azure AI Search<\/strong>) for AI tasks that benefit from public cloud scale.<\/p>\n

                                                Accelerate AI without compromising data control<\/h4>\n
                                                  \n
                                                • Sensitive AI workloads stay on VCF<\/strong>\n
                                                    \n
                                                  • Customer data, contracts, financial records, and other confidential information\u00a0never leave the customer\u2019s perimeter<\/strong>. This keeps your company aligned with\u00a0regulatory and confidentiality<\/strong>\u00a0requirements such as GDPR or sector-specific rules.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
                                                      \n
                                                    • Generative AI applications use Azure AI services<\/strong>\n