Hybrid cloud makes the data center one possible home for workloads—not the default destination for all of them. Organizations combine local infrastructure with cloud services and, where needed, edge locations or other clouds, placing each workload according to its technical and business requirements.
What is hybrid cloud?
Hybrid cloud combines cloud services with infrastructure and workloads in data centers, edge locations, and potentially other cloud environments. It is a placement model, not simply a halfway stage on a one-way migration from a data center to the cloud. Microsoft’s Azure hybrid options guidance recommends starting with workload and organizational requirements rather than the location of existing hardware.
A data center remains important in this model: it can host systems that need local processing, close access to equipment or data, or continued operation without an external connection. At the same time, workloads that fit managed services can run in the cloud. The result is a set of locations with different roles, governed by explicit placement and management rules.
What is a data center’s role in a hybrid architecture?
A data center is a facility for computing infrastructure such as servers, storage, and networking. AWS’s overview, What is a Data Center?, describes the facility and infrastructure context. In a hybrid architecture, the data center is one part of the organization’s computing environment rather than the assumed home for every application and dataset.
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Depending on the workload, the local site may host existing systems, provide compute near users or physical equipment, process data before sending selected results elsewhere, or support operations that must continue when connectivity is unavailable. Cloud services can complement those roles with managed capabilities or additional capacity. Neither location is automatically best for every application.
Which workloads should stay on premises?
Keep a workload local when a requirement makes local execution materially more suitable. Microsoft’s guidance highlights several considerations for deciding where workloads and data belong:
- Latency or physical dependencies: An application may need fast access to nearby users, devices, machinery, or systems that are difficult to move.
- Local data processing or data gravity: Processing data where it is generated can matter when moving large volumes elsewhere would be impractical or when local systems depend on that data.
- Data and control constraints: Residency, privacy, confidentiality, retention, access, and key-ownership obligations may affect placement. Validate the actual controls against the organization’s legal and contractual requirements rather than assuming that a particular location alone meets them.
- Connectivity and resilience: If a site has intermittent connectivity—or must keep selected functions running during an outage—identify what can operate locally and what depends on an external service.
- Existing infrastructure and scale: Supported servers or virtualization may be reusable where they fit; other requirements may call for validated infrastructure. Product-specific hardware, deployment, and scale limits still apply.
These factors do not mean that an entire application must stay in one place. A design may keep a latency-sensitive component near equipment while using cloud services for other functions, provided the dependencies and failure behavior are understood.
When does cloud placement make more sense?
Use a managed cloud service when it meets the workload’s requirements and its dependencies, data controls, and availability needs are acceptable. This can reduce the need to operate some infrastructure locally, but it does not establish that the overall design will cost less: costs depend on the organization’s workload, network use, service choices, existing assets, and operating model.
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AWS identifies migration, disaster recovery, low-latency workloads, and international expansion as hybrid-cloud use cases in its hybrid cloud architecture best practices. These are possible design goals, not proof that hybrid architecture is the right choice for every organization or that it guarantees a particular outcome.
How do local cloud services fit?
Some services bring cloud-consistent infrastructure or management closer to local systems. They can help address specific placement needs, but they do not remove facility requirements or make all cloud capabilities available in every operating mode.
Azure Arc and Azure Local
Microsoft describes Azure Arc as a way to govern supported resources outside Azure. Azure Local provides validated, Azure-consistent infrastructure for certain local needs. The available capabilities, hardware requirements, and lifecycle differ by product and deployment. In particular, Azure Local’s disconnected operations use a local control plane and provide a subset of Azure capabilities; do not assume that every Azure feature works offline. Consult Microsoft’s hybrid options guidance for the relevant deployment considerations.
AWS Outposts
AWS describes Outposts as extending AWS infrastructure, services, APIs, and tools into a data center, colocation space, or another on-premises facility. It is intended for workloads that need low latency or local data processing. AWS also discusses using cloud resources to extend local capacity, support disaster recovery, and place selected services nearer to users or existing systems in its hybrid cloud use cases.
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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsLocal cloud infrastructure still needs a suitable site. AWS’s Outposts prerequisites and limitations cover facility power, environmental conditions, connectivity to the parent Region, and an applicable support plan. The requirements also specify a sustained internet or Direct Connect connection, including minimum throughput and maximum round-trip latency. Because product requirements can change, verify the current figures and conditions with AWS before designing or deploying a site.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to make workload-placement decisions
Set a placement policy before choosing a product or moving an application. Use a consistent review for each workload:
- State the business objective. Define what the placement must accomplish, such as supporting a local process, meeting an availability target, or enabling a particular service.
- Map the workload and its dependencies. Identify users, connected systems, data sources, physical equipment, and services it relies on. Note which components can be separated and which must remain close.
- Record data and control obligations. Document residency, privacy, confidentiality, retention, access, and key-management requirements, then confirm that a proposed design can satisfy them.
- Classify connectivity and outage behavior. Determine whether each site is reliably connected, intermittently connected, or expected to operate disconnected. Specify which functions must continue during an outage and which may stop or degrade.
- Choose the operating and management boundary. Decide whether a cloud-hosted management plane is acceptable or whether local or disconnected control is needed. Check exactly which capabilities and lifecycle operations are supported in the chosen mode.
- Validate infrastructure, skills, and economics. Check facility, network, hardware, scale, and support requirements. Evaluate staffing and total cost using the organization’s own workload and operating assumptions; the cited architecture guidance does not establish a neutral, general cost or staffing advantage.
- Apply the rule consistently. Document why each workload belongs in a particular location and what conditions would trigger a review, such as a change in data obligations, connectivity, or application dependencies.
What hybrid cloud changes—and what it does not
Hybrid cloud changes the data center from the presumed center of organizational computing into one location within a broader architecture. That gives organizations more placement options, but also makes decisions about connectivity, dependencies, data location, management boundaries, and outage behavior more explicit. It does not make migration inevitable, guarantee lower cost, or eliminate the need to operate and support local infrastructure.
An AWS Architecture Blog post dated September 18, 2024, describes athenahealth’s use of two geographically distributed data centers alongside Outposts and AWS Local Zones. AWS says the arrangement let the company deploy containerized applications near existing databases and supported high availability and disaster recovery. This is an AWS-published customer example of one design, not independent evidence that the same architecture or benefits will apply elsewhere: athenahealth’s hybrid cloud journey.
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