Azure Elastic SAN: Scalable Cloud Storage for Modern Workloads

1. The Need for Scalable Cloud Storage

Enterprises today generate more data than ever, and the pace of growth shows no signs of slowing. Traditional on-premises Storage Area Networks (SANs) have long provided dependable performance for databases, analytics, and ERP systems. Yet, as workloads expand and diversify, these systems struggle with inflexible capacity, complex upgrades, and high operational costs.

Cloud computing has redefined expectations: storage must be elastic, available on demand, and integrated across multiple compute platforms. Businesses now seek infrastructure that can grow seamlessly while maintaining predictable performance and cost transparency.

Azure Elastic SAN is Microsoft’s answer to this evolution a cloud-native, fully managed SAN that blends the reliability of enterprise storage with the flexibility of the Azure cloud. It enables organizations to consolidate workloads, scale both performance and capacity independently, and modernize without redesigning core applications.

In essence, Elastic SAN empowers enterprises to achieve SAN-grade performance without SAN-grade complexity, making it a strategic choice for modernization, consolidation, and hybrid-cloud transformation.

2. Architecture Overview

Core Components

Azure Elastic SAN is built around three logical layers that simplify management and scaling:

1. Elastic SAN Resource: The top-level construct that defines total capacity and performance allocation.
2. Volume Groups: Logical containers that organize volumes by workload type or policy, such as performance or encryption settings.
3. Volumes: Individual block-storage units accessed via iSCSI, attachable to multiple compute targets.

This layered model makes it easier to manage shared resources across varied workloads while maintaining clear isolation boundaries.

Decoupled Performance and Capacity

One of Elastic SAN’s biggest differentiators is the ability to scale performance and capacity separately. In traditional SANs, performance often depends on hardware configuration; Elastic SAN abstracts that limitation.

This design ensures that storage investments align directly with workload demand no more over-provisioning for peak traffic.

Connectivity Options

Elastic SAN uses the iSCSI protocol, enabling broad compatibility across Azure compute services:

• Azure VMs: Attach volumes for high-performance or shared application storage.
• Azure Kubernetes Service (AKS): Provide persistent storage for stateful containers.
• Azure VMware Solution (AVS): Extend on-prem virtualization environments to the cloud with minimal reconfiguration.

Together, these options position Elastic SAN as a versatile backbone for mixed workloads from large transactional systems to scalable container platforms.

3. Planning and Design Considerations

Effective adoption of Azure Elastic SAN begins with sound planning that connects technical sizing to business priorities.

Assessing Workload Profiles

Start by profiling workloads based on access patterns and performance sensitivity:

• Transactional applications (e.g., databases): Focus on high IOPS and minimal latency.
• Analytical or archival workloads: Emphasize sustained throughput and cost efficiency.
• Shared environments: Seek a balanced mix, leveraging performance pooling across volumes.

Mapping these characteristics early helps determine the right mix of capacity and performance units.

Choosing Redundancy and Region

Azure Elastic SAN offers two redundancy models:

• Local Redundant Storage (LRS): Keeps three data copies within a single data center suitable for test, dev, or non-critical workloads.
• Zone Redundant Storage (ZRS): Distributes data across availability zones recommended for production and mission-critical systems.

Redundancy Selection

Before deploying, verify feature availability in your target region, as not every redundancy tier is supported everywhere.

Cost and Capacity Planning

Elastic SAN pricing is based on capacity units and performance units. A pragmatic approach:

1. Deploy an initial baseline configuration.
2. Observe real workload behavior through Azure Monitor.
3. Scale performance or capacity incrementally based on sustained utilization.

This iterative strategy prevents overspending while ensuring responsive applications.

When Elastic SAN Makes Business and Technical Sense

Elastic SAN delivers clear value when organizations need:

• High-performance shared storage without maintaining hardware.
• Simplified consolidation of multiple workloads under one management plane.
• Predictable scalability for hybrid or multi-application environments.

However, for small, isolated workloads, Azure Managed Disks may remain the more economical choice highlighting the importance of matching solution complexity to workload size.

4. Networking Architecture

Efficient connectivity is critical to Azure Elastic SAN performance. The service uses the iSCSI protocol for communication between compute and storage, delivering enterprise-grade block-storage access across Azure’s private network fabric.

iSCSI Network Flow in Azure

Elastic SAN operates entirely within private VNets. Compute nodes (VMs, AKS pods, or AVS instances) initiate iSCSI sessions directly to SAN targets via private IPs.
This ensures that storage traffic remains within Azure’s secure backbone, providing low latency and predictable throughput.

Typical flow:

1. Compute node initiates an iSCSI login to the SAN target.
2. The SAN authenticates and maps the request to the assigned volume.
3. Data flows over TCP (port 3260) within the virtual network boundary.

Designing Connectivity for Scale

Key considerations:

• Dedicated Subnets: Isolate storage traffic from general workloads.
• Routing: Use User-Defined Routes (UDRs) for predictable data paths.
• Bandwidth Planning: Align VM SKU and NIC throughput with workload requirements.
• Latency Zones: Keep compute and SAN resources within the same Availability Zone when possible.

Connectivity Patterns for Clustered or Multi-VM Workloads

This matrix helps architects select the optimal connectivity model based on workload type, scale, and resilience requirements.

5. Operations and Performance Management

Operational efficiency in Elastic SAN revolves around performance, automation, and cost optimization.

Scaling and Performance Optimization

Elastic SAN separates performance from capacity, enabling fine-grained adjustments:

• Performance Units: Increase IOPS and throughput for high-demand workloads.
• Capacity Pools: Expand storage size independently of performance.
• Combined Scaling: Adjust both for simultaneous high-load and growing datasets.

Scaling Options

Monitoring via Azure Monitor and Metrics Explorer ensures consistent performance and allows proactive adjustments.

Automation and Lifecycle Management

Simplify provisioning and operations using:

• ARM templates / Bicep: Declarative, repeatable deployments.
• Terraform: Cross-cloud or hybrid automation.
• Azure Policy & Tags: Governance, cost tracking, and compliance enforcement.

Automation reduces human error, speeds up deployment, and maintains operational consistency.

Cost Optimization via Shared Performance Pools

Elastic SAN allows multiple volumes to draw from a shared performance pool.

• Prevents over-provisioning per volume.
• Enables reallocation of under-utilized capacity to heavy workloads.
• Supports predictable budgeting by balancing usage across multiple workloads.

6. Security and Encryption

Azure Elastic SAN implements defense-in-depth security using encryption, access control, and network isolation.

Encryption at Rest and in Transit

• At Rest: AES-256 encryption is applied automatically.
• In Transit: iSCSI CHAP authentication and TLS 1.2 protect data integrity across the network.

Customer-Managed Keys (CMK) Integration

For regulated industries or compliance-heavy workloads, Elastic SAN integrates with Azure Key Vault for Customer-Managed Keys (CMK).
This allows organizations to rotate, audit, and revoke keys independently, satisfying standards like ISO 27001, HIPAA, and PCI DSS.

Key Management Options

Access Control and Governance

• Apply RBAC with least-privilege principles.
• Limit SAN connectivity to approved subnets and private endpoints.
• Enable Azure Monitor Logs for auditing and incident response.

7. Data Protection and Disaster Recovery

Ensuring data protection and business continuity is critical for any enterprise deploying Azure Elastic SAN. The platform provides snapshots, automated backups, and replication, enabling organizations to safeguard critical workloads and meet recovery objectives.

Snapshots offer lightweight, point-in-time copies of volumes for rapid recovery without impacting operations. For databases, application-consistent snapshots maintain transactional integrity. Azure Backup automates offsite storage and retention, with options for zone-redundant storage (ZRS) or geo-redundant storage (GRS), adding resilience for disaster recovery scenarios.

Designing a business continuity plan involves aligning strategies with Recovery Time Objectives (RTO) and Recovery Point Objectives (RPO). Regular testing, such as quarterly failover drills, ensures readiness. Resource placement co-locating compute and storage within regions or zones is essential for meeting recovery targets.

Decision Matrix: Backup & Replication Options

8. Monitoring and Observability

Monitoring ensures predictable performance and early detection of potential issues. Key metrics include IOPS, throughput, latency, and utilization, which together provide a clear view of storage health and workload behavior.

Azure Monitor and Log Analytics help collect, visualize, and analyze these metrics. Alerts can be set for thresholds such as latency spikes or IOPS peaks, enabling proactive response before they affect operations. Trend analysis allows organizations to forecast growth, plan scaling, and prevent bottlenecks.

Actionable insight: Focus on meaningful metrics and trends rather than monitoring every detail. This approach provides CXOs with visibility into operational health while giving technical teams practical guidance for tuning and scaling.

9. Workload Fit and Practical Use Cases

Azure Elastic SAN supports diverse workloads, from high-performance clustered databases to containerized applications. For clustered databases like SQL FCI, Oracle RAC, or SAP HANA, it delivers low-latency shared storage, ensuring nodes operate efficiently without contention.

Containerized applications in AKS or virtualized workloads in AVS benefit from persistent volumes and shared storage across multiple VMs, supporting high-availability configurations.

Organizations migrating from on-premises SANs gain a straightforward lift-and-shift path to the cloud. Elastic SAN reduces dependency on legacy hardware while allowing independent scaling of performance and capacity, addressing common bottlenecks of traditional SAN deployments. Combined with robust backup and monitoring strategies, it provides a reliable, enterprise-ready storage foundation.