What Is Hybrid Cloud Architecture

Hybrid cloud architecture solves a real problem: organizations cannot simply abandon on-premises infrastructure overnight. Legacy applications, regulatory constraints, data sovereignty, and existing investments require a bridge. Rather than maintaining separate silos with different tools and processes, hybrid cloud architecture provides a single control plane and consistent experience across all infrastructure.

Azure’s hybrid approach uses two primary tools: Azure Arc extends Azure management to any infrastructure, and Azure Stack HCI runs Azure services directly on-premises.

What Problems Hybrid Architecture Solves

Without a hybrid strategy:

• On-premises and cloud infrastructure operate with separate tools and policies
• Teams manage multiple identity systems and access controls
• Workload portability requires re-architecture or manual migration
• Compliance and governance policies must be defined and enforced separately
• Organizational silos deepen between “cloud teams” and “infrastructure teams”

With hybrid architecture:

• Single Azure management plane controls on-premises and cloud resources
• Unified identity and access control through Entra ID across all infrastructure
• Workloads can run on-premises, cloud, or move between them with consistent policies
• Compliance policies apply uniformly regardless of where resources run
• Teams use the same tools and processes everywhere, reducing training and context switching

How Hybrid Architecture Differs from Pure Cloud

Architects from pure cloud backgrounds should understand key differences:

Azure Arc: Extending Azure Management Everywhere

What Azure Arc Provides

Azure Arc is Azure’s management plane for resources outside Azure. It allows you to view, govern, and manage servers, Kubernetes clusters, data services, and applications running anywhere (on-premises, in other clouds, or at the edge) as if they were part of your Azure subscription.

Azure Arc projects resources into your Azure environment so that you manage them with the same Portal experience, policies, and identity system as native Azure resources.

What Arc enables:

• Servers: Windows and Linux machines running on-premises or in other clouds appear as Azure resources with Entra ID login and access control
• Kubernetes: Any Kubernetes cluster (EKS, GKE, self-hosted, or on-premises) becomes an Arc-connected cluster managed through Azure
• SQL Server: SQL Server instances running on-premises can be managed, monitored, and updated through Azure
• Data services: PostgreSQL, MySQL, and SQL Managed Instance can run in containers on your infrastructure and be billed through Azure
• Applications: Azure App Service and Azure Functions can run in containers on your on-premises infrastructure

Arc-Connected Servers

Arc-connected servers are on-premises or multi-cloud machines that install the Azure Connected Machine agent. Once enrolled, they appear in your Azure subscription and can be managed with Azure policies, access control, monitoring, and tooling.

Installation process:

1. Install the Azure Connected Machine agent on a Windows or Linux machine
2. Agent authenticates to Azure with a managed identity (for on-premises) or Azure service principal
3. Machine appears as a resource in your Azure subscription
4. You assign policies, monitor it, and control access just like an Azure VM

What you can do with Arc-connected servers:

• Enforce Azure policies on configuration, security, and compliance
• Use Role-Based Access Control (RBAC) to control who can manage the server
• Connect to the machine through Azure Bastion instead of managing your own jump hosts
• Assign it to an Azure resource group and include it in subscriptions-wide governance
• Monitor performance through Azure Monitor (same agent as Azure VMs)
• Manage extensions (anti-malware, monitoring, patch management) consistently

Arc-Connected Kubernetes

Arc-enabled Kubernetes brings any Kubernetes cluster (whether hosted on AWS, Google Cloud, on-premises, or edge devices) under Azure management.

How it works:

1. Deploy the Azure Arc agent to your Kubernetes cluster
2. The cluster appears as an Arc-enabled Kubernetes resource in your Azure subscription
3. Deploy policies, monitor the cluster, and use GitOps for configuration management
4. Deploy applications directly from the Azure Portal to any cluster, regardless of location

What you can do:

• Deploy applications across multiple Kubernetes clusters using Azure Arc’s application model
• Enforce Azure policies on cluster configuration and pod security
• Monitor cluster and workload health through Azure Monitor
• Use Azure App Service and Azure Functions on your Kubernetes cluster (create App Service plans that target the Arc cluster instead of cloud regions)

Arc-Enabled Data Services

Arc-enabled data services (PostgreSQL, MySQL, and SQL Managed Instance) run on your infrastructure in containers while being billed and managed through Azure.

When to use Arc data services:

• SQL Server workloads that must stay on-premises but you want cloud management experience
• PostgreSQL or MySQL instances that must remain in your datacenter for data residency
• Lifting and shifting databases from other clouds to your infrastructure without re-platforming

Trade-offs:

• You manage the underlying infrastructure (compute, storage, networking)
• Azure manages the database engine and patches
• Billing flows through your Azure subscription with consumption-based pricing
• Requires containerization of the database (Docker/Kubernetes backend)

Azure Stack HCI: Hybrid Infrastructure Platform

What Azure Stack HCI Is

Azure Stack HCI is a hyperconverged infrastructure (HCI) solution that runs Azure services, Windows Server, and Kubernetes on your hardware while maintaining the operational model of on-premises infrastructure. It bridges the gap between traditional on-premises systems and cloud-native architectures.

HCI consolidates compute, storage, and networking into a converged appliance. Stack HCI adds Azure integration so you can run Arc-enabled services, deploy containers, and manage everything through Azure.

Core Components

Hardware:

• Integrated systems from OEMs (Dell EMC, HPE, Lenovo, others) with pre-qualified components
• Minimum two nodes (for high availability), typical configurations start at 4 nodes
• Local NVMe for performance tier, SATA for capacity tier storage

Software:

• Windows Server as the underlying OS
• Hyper-V for virtualization
• Storage Spaces Direct for converged storage
• Software-defined networking (SDN) for network virtualization
• Azure Stack HCI agent connecting to Azure

Operational model:

• Managed through Windows Admin Center (on-premises UI) or increasingly through Azure Portal via Arc
• Updates coordinated by Microsoft but deployed and managed locally
• Capacity is fixed at deployment (unlike public cloud elasticity)

What You Can Run on Stack HCI

Azure Virtual Machines: Windows and Linux VMs run on HCI exactly like cloud VMs, with the same ARM templates and configuration

Kubernetes: AKS on Stack HCI lets you run Kubernetes workloads on-premises with Arc management and billing through Azure

Arc-enabled applications: Deploy Azure App Service and Azure Functions as containers on HCI

Traditional workloads: Windows Server applications, VMs, Hyper-V clusters continue running as before

When to Choose Stack HCI

Stack HCI makes sense in specific scenarios:

Choose Stack HCI when:

• You have substantial existing datacenter infrastructure and investment in Hyper-V
• You need to run cloud-native workloads on-premises for data sovereignty or latency
• You want to defer or avoid wholesale cloud migration while modernizing management
• You need hybrid mobility (run workloads on-premises during normal times, burst to cloud during peaks)
• Regulatory requirements mandate data residency in your controlled facilities

Don’t choose Stack HCI when:

• You’re building new infrastructure from scratch (public cloud is often cheaper at scale)
• You lack datacenter and virtualization expertise (operational complexity is high)
• You want full cloud elasticity and auto-scaling (HCI has fixed capacity)
• Your workloads are already cloud-native and stateless

Azure Stack Hub vs Azure Stack HCI vs Azure Stack Edge

Understanding the differences between Azure Stack variants prevents selecting the wrong tool:

Decision framework:

1. Need full disconnected Azure environment? → Stack Hub
2. Want hybrid infrastructure with cloud management? → Stack HCI
3. Running at the edge with AI/IoT? → Stack Edge

Hybrid Networking Patterns

Connecting on-premises infrastructure to Azure requires careful network design.

Connectivity Options

Site-to-Site VPN:

• Uses IPsec encryption over the internet
• Suitable for initial hybrid connectivity or backup links
• Higher latency due to internet routing variability
• Provides disaster recovery if ExpressRoute fails
• Quick to set up with VPN Gateway in Azure

ExpressRoute:

• Private dedicated connection from your datacenter to Microsoft network
• Consistent low latency and high bandwidth
• Requires coordination with your ISP or connectivity partner
• Connects at multiple points (primary and secondary redundancy)
• More expensive but essential for mission-critical workloads

Hybrid approach (ExpressRoute + VPN):

• Use ExpressRoute for primary connectivity
• VPN as failover if ExpressRoute fails
• Provides highest reliability and resiliency

For detailed connectivity architecture, see the ExpressRoute & VPN Gateway guide.

Hybrid Networking Architecture

Hub-and-spoke with on-premises connection:

On-Premises Datacenter
   ↓
[VPN/ExpressRoute Gateway]
   ↓
Azure Hub VNet (10.0.0.0/16)
├── [Azure Firewall]
├── [VPN/ExpressRoute Gateway]
├── [DNS, monitoring]
   ↓
Azure Spoke VNets (peered)
├── Spoke 1 (10.1.0.0/16)
├── Spoke 2 (10.2.0.0/16)

On-premises resources connect to the hub VNet through VPN/ExpressRoute. Spokes are peered with the hub. All inter-spoke and on-premises-to-spoke traffic flows through Azure Firewall in the hub for centralized security inspection.

Arc-connected servers and hybrid resources:

• On-premises servers with Arc agent appear in your Azure subscription
• Entra ID provides authentication and authorization
• Azure Policy applies to on-premises resources same as cloud
• Azure Monitor collects metrics and logs from everywhere

Hybrid Identity: Entra ID and On-Premises AD

Hybrid identity connects cloud identity (Entra ID) with on-premises directory (Active Directory).

Three Hybrid Identity Models

Entra ID Connect (password hash sync):

• On-premises AD passwords are hashed and synced to Entra ID every 2 minutes
• Users log in with same credentials everywhere
• Entra ID stores only the password hash, not the actual password
• Simplest to implement, no complex infrastructure
• One-way sync from AD to Entra ID

Entra ID Connect with pass-through authentication:

• Passwords are not synced; authentication requests pass through to on-premises AD
• On-premises AD validates the password
• Slightly more complex than password hash sync
• Stronger security posture (password never in cloud)
• Requires always-on connection to on-premises AD

Entra ID Domain Services:

• Managed domain in Azure that extends Entra ID capabilities
• Supports LDAP, group policy, and Kerberos authentication
• Allows VMs in Azure to join the domain just like on-premises machines
• Useful when applications require traditional AD features
• More complex and expensive than other models

Managing Hybrid Identity

Entra ID Connect is the primary tool for syncing on-premises Active Directory with cloud Entra ID.

What gets synced:

• Users and their properties (name, email, phone, etc.)
• Groups and group membership
• Contact objects and distribution lists
• Passwords (via hash sync or pass-through auth)

Sync process:

• Entra ID Connect runs on a server in your on-premises environment
• It connects to your local Active Directory and reads changes
• Changes are synced to Entra ID every 30 minutes (configurable)
• Users log in with their on-premises credentials everywhere

Disaster recovery for Entra ID Connect:

• If the sync server fails, users can still log in with cloud credentials temporarily
• Deploy a standby sync server for critical environments
• Ensure your on-premises AD is resilient

Hybrid Policy and Governance

Applying consistent policies across cloud and on-premises infrastructure prevents configuration drift and security gaps.

Azure Policy for Hybrid Resources

Azure Policy enforces organizational standards on Azure resources and Arc-connected resources.

Policy types:

Enforce compliance: VMs must have specific tags, encryption enabled, specific software versions

• Assigned to subscriptions or management groups
• Evaluated continuously as resources are created and modified
• Non-compliant resources are identified and can be remediated automatically

Audit and report: Flag resources that don’t meet your standards without blocking them

• Useful for gradual rollout of new policies
• Report on compliance across the organization

Guest configuration: Audit and enforce settings inside the OS

• Check if antivirus is running on a VM
• Ensure specific Windows registry settings
• Validate Linux system configuration files
• Works on both Azure VMs and Arc-connected servers

Unified Governance Across Hybrid Infrastructure

Management groups:

• Organize subscriptions into a hierarchy
• Apply policies at the management group level (flows to all subscriptions below)
• Use for organization-wide compliance (all VMs must be patched, encryption required, etc.)

Tags:

• Apply consistent tagging across cloud and Arc resources
• Use tags for cost allocation, environment identification, and team assignment
• Enforce tag policies to ensure all resources are tagged

Role-Based Access Control (RBAC):

• Same RBAC model applies to cloud and Arc resources
• Use Entra ID groups to manage access
• Control who can create, modify, or delete resources

Hybrid Monitoring and Observability

Monitoring workloads across cloud and on-premises requires a unified platform.

Azure Monitor for Hybrid Workloads

Azure Monitor collects metrics and logs from Azure resources, Arc-connected resources, and on-premises infrastructure.

What you can monitor:

• Azure VMs and services (native)
• Arc-connected servers (via Azure Monitor agent)
• On-premises applications and infrastructure (via Telegraf, Prometheus exporters, or custom collectors)
• Kubernetes clusters (arc-enabled or otherwise)

Key components:

• Metrics: Real-time data (CPU, memory, disk, network)
• Logs: Events, application traces, and audit logs (collected into Log Analytics workspace)
• Alerts: Notifications when metrics exceed thresholds or specific events occur
• Dashboards: Visualizations across all data sources

Arc-specific monitoring:

• Azure Monitor agent deployed to Arc-connected servers
• Same monitoring capabilities as Azure VMs (no special configuration needed)
• Create alerts that span cloud and on-premises resources

For detailed monitoring guidance, see the Observability & Monitoring guide.

Edge Computing: Azure Stack Edge and IoT Edge

Azure extends to the edge, where data is created, not just to cloud datacenters.

Azure Stack Edge

Azure Stack Edge is a compact appliance (about the size of a small switch) deployed at branch offices, factories, or remote locations.

What it does:

• Local processing and storage at the edge
• Automatic sync of data to Azure (uploads periodically or continuously)
• Kubernetes support for containerized workloads
• GPU options for machine learning inference
• Works disconnected (batches data, syncs when connected)

Use cases:

• IoT data collection and preprocessing at factories
• ML inference on edge devices before uploading to cloud
• Temporary data staging before upload to Azure
• Branch office file services with cloud backup

Azure IoT Edge

Azure IoT Edge runs containerized workloads on IoT devices and gateways.

Key differences from Stack Edge:

• Lighter weight (runs on Linux or Windows devices, not appliances)
• Focuses on device and gateway intelligence
• Integrates with IoT Hub for management and telemetry
• Modules are standard containers (same as Kubernetes)

Typical IoT Edge deployment:

• Deploy containers to edge devices through Azure IoT Hub
• Devices process sensor data locally
• Send only relevant data to cloud (reduces bandwidth)
• Continue working if cloud connectivity fails

Workload Placement Decisions

Deciding where workloads should run is central to hybrid architecture.

When to Keep Workloads On-Premises

Keep on-premises when:

Data sovereignty: Laws or regulations require data to stay in specific countries or regions (GDPR, HIPAA for specific data residency, government contracts)

Existing infrastructure: You have recent, capable hardware and maintenance contracts. The ROI of cloud does not justify replacing working systems.

Low-frequency demand: Workloads run predictably without spikes. Cloud elasticity provides no value. Fixed on-premises capacity is cheaper.

Strict latency requirements: Applications require sub-millisecond latency to other on-premises systems. Network latency to cloud exceeds requirements.

Data size: Moving terabytes of data to cloud is impractical. Local processing and staging is more efficient.

When to Migrate to Cloud

Migrate to cloud when:

Variable demand: Workloads scale up and down unpredictably. Cloud elasticity saves money compared to maintaining peak capacity.

Global presence: Application needs to serve users across multiple regions. Cloud provides regional deployment and edge caching.

Operational simplicity: You want fewer infrastructure responsibilities. PaaS services (databases, message queues, APIs) reduce operational overhead.

New development: Building new applications with cloud-native design patterns. Containerization, serverless, and managed services are natural.

Modernization: Legacy applications prevent hiring and innovation. Cloud migration enables modernization investments.

Hybrid Placement Strategies

Lift-and-shift to Azure or Stack HCI:

• Move VMs as-is to cloud or hybrid infrastructure
• Minimal code changes
• Quick to move, provides breathing room for modernization
• Workloads still run on VM infrastructure (not optimized for cloud)

Re-host on cloud-native platforms:

• Move workloads to PaaS services (Azure App Service, Azure SQL, etc.)
• Requires application changes
• Takes advantage of cloud services (auto-scaling, less ops overhead)
• Better long-term economics and operational simplicity

Hybrid burst pattern:

• Keep baseline capacity on-premises
• Burst to cloud during peak demand
• Requires application design to handle distributed deployment
• Optimizes cost (pay for peak on-premises + burst cloud capacity)

Comparison with AWS and GCP Hybrid Solutions

Organizations using AWS or GCP have different hybrid options:

AWS Hybrid Solutions

AWS Outposts:

• AWS hardware and services deployed in your datacenter
• You get AWS services (EC2, RDS, S3) running on-premises
• Requires AWS to manage the hardware and maintain the connection
• Suitable when you want AWS services but cannot move workloads to cloud

EKS Anywhere:

• Run Amazon EKS on your infrastructure
• Kubernetes management plane runs on-premises
• Hybrid Kubernetes but with AWS tooling and experience
• Lighter weight than Outposts

Hybrid networking:

• AWS Direct Connect for dedicated connectivity
• VPN for backup
• Similar to Azure ExpressRoute and VPN Gateway

GCP Hybrid Solutions

Google Cloud at the edge:

• Lightweight container runtime on edge devices
• Distributed data processing at the edge
• Less mature than AWS or Azure hybrid offerings

GKE Anywhere:

• Run Google Kubernetes Engine on your infrastructure
• Kubernetes focus like AWS EKS Anywhere
• Limited hybrid services compared to Azure

Azure vs AWS vs GCP Hybrid Comparison

Why Azure Leads in Hybrid

Azure’s hybrid strengths:

• Unified management: Azure Arc extends the full Azure management plane (policies, RBAC, monitoring) to any infrastructure
• Stack HCI: Purpose-built hybrid infrastructure platform (not just services on your hardware)
• Edge scale: Azure Stack Edge and IoT Edge provide edge-specific platforms
• Identity integration: Deep on-premises AD integration with Entra ID
• Service breadth: More Arc-enabled services (databases, app service, functions) than competitors

AWS and GCP focus on extending their cloud services to hybrid environments. Azure built a comprehensive hybrid story across management, infrastructure, and services.

Common Pitfalls

Pitfall 1: Assuming Seamless Workload Mobility

Problem: Building applications assuming they can easily move between on-premises and cloud without modification.

Result: Cloud versions require significant architectural changes (statelessness, horizontal scaling, managed services). Migration takes far longer than expected.

Solution: Design applications for target platforms from the start. If the goal is mobility, use containerization and Kubernetes (both on-premises and cloud) from day one. Accept that some optimization will be needed for each platform.

Pitfall 2: Underestimating Hybrid Network Complexity

Problem: Assuming ExpressRoute or VPN “just works” without planning address spaces, firewall rules, and routing policies.

Result: Network connectivity fails, traffic takes unexpected paths, on-premises workloads cannot reach cloud resources.

Solution: Plan your hybrid network explicitly. Ensure on-premises and cloud address spaces do not overlap. Test connectivity and routing thoroughly before deploying production workloads.

Pitfall 3: Identity Synchronization Failures

Problem: Entra ID Connect sync fails silently. Users in cloud Entra ID diverge from on-premises Active Directory.

Result: Access control is inconsistent. Some users cannot log into cloud applications. Compliance audits reveal mismatched identities.

Solution: Monitor Entra ID Connect health continuously. Set up alerts for sync failures. Regularly audit user accounts in both directories. Test failover scenarios.

Pitfall 4: Inconsistent Policies Across Cloud and On-Premises

Problem: Policies are applied to cloud resources (encryption required, tags mandatory) but not to Arc-connected or on-premises resources.

Result: On-premises systems become non-compliant. Audit finds unencrypted servers or untagged infrastructure in datacenters.

Solution: Apply Azure Policy consistently to all resources, both cloud and Arc-connected. Use management groups to enforce policies organization-wide.

Pitfall 5: Forgetting Stack HCI Capacity Planning

Problem: Deploying Azure Stack HCI with insufficient capacity for expected workloads, treating it like elastic cloud infrastructure.

Result: Stack HCI fills to capacity. Adding nodes requires planning, procurement, and downtime.

Solution: Plan Stack HCI capacity for 3-5 year horizons like traditional infrastructure. Provision for peak expected demand plus growth headroom. Understand that HCI, like on-premises infrastructure, has fixed capacity.

Pitfall 6: Data Transfer Costs Wiping Out Economics

Problem: Moving large datasets between on-premises and cloud repeatedly without understanding data transfer costs.

Result: Cloud data transfer costs exceed the cost of keeping workloads on-premises.

Solution: Minimize data movement. Use local processing and caching to reduce data to cloud. Understand Azure data transfer pricing before committing to hybrid workloads. Consider periodic bulk transfers instead of continuous sync for archival data.

Key Takeaways

1. Azure Arc extends Azure management to any infrastructure. Servers, Kubernetes clusters, data services, and applications everywhere appear in your Azure subscription with consistent policies, identity, and monitoring. This eliminates maintaining separate silos for cloud and on-premises.

2. Azure Stack HCI is a hybrid infrastructure platform, not just cloud services on your hardware. It provides hyperconverged compute and storage with Azure integration, suitable for organizations modernizing on-premises infrastructure while extending cloud capabilities.

3. Hybrid identity requires synchronization. Entra ID Connect syncs on-premises Active Directory to cloud Entra ID. Users authenticate consistently everywhere. Plan for sync failures and maintain backup authentication methods.

4. Network design is critical for hybrid success. Plan address spaces to avoid overlaps. Choose between VPN (simple, lower cost) and ExpressRoute (consistent latency, higher cost) based on workload requirements. Use hub-and-spoke to centralize security inspection.

5. Workload placement decisions should be intentional, not default. Keep things on-premises if data sovereignty, latency, or existing infrastructure investment justifies it. Migrate to cloud when you need elasticity, global reach, or modernization. Use hybrid patterns for variable workloads.

6. Azure Policy applies uniformly across cloud and on-premises. Use management groups to enforce compliance everywhere. Avoid policy gaps where on-premises resources remain non-compliant while cloud resources are locked down.

7. Data transfer costs matter significantly. Minimize data movement between on-premises and cloud. Understand pricing before committing to continuous synchronization. Local processing at the edge can reduce costs dramatically.

8. Azure’s hybrid story is comprehensive. From management (Arc) to infrastructure (Stack HCI) to edge (Stack Edge, IoT Edge) to identity (Entra ID Connect), Azure provides purpose-built tools for hybrid scenarios. AWS and GCP focus on extending cloud services; Azure focuses on integrating cloud with on-premises.

9. Hybrid failures are often identity or network related. Monitor Entra ID Connect health and network connectivity continuously. Plan for failure modes (sync failures, ExpressRoute outages). Test failover scenarios before they are needed in production.

10. Start with a clear hybrid strategy. Define which workloads stay on-premises and why. Design for specific business outcomes (cost, compliance, performance) rather than trying to be hybrid-ready for all scenarios. Hybrid is a means to business goals, not a goal itself.