# Commvault Flex Appliance Deployment Models

For Commvault Flex Appliance, there are effectively three deployment and data path modes that determine how backup data reaches the external S3 storage platform.

## 1. Storage Accelerator Mode (Direct-to-S3)

Best for: Clients that have direct network connectivity to the S3 storage endpoint.

Characteristics

- Backup data flows directly from the client to the S3 object store.
- Flex node manages metadata, indexing, retention, and orchestration.
- Lowest latency and highest throughput.
- Reduces load on Flex nodes.
- Requires network reachability from clients to the S3 endpoint.

## 2. Proxy Mode (Through Flex Node)

Best for: Segmented networks, security zones, or environments where clients cannot access the S3 endpoint.

Characteristics

- All backup traffic passes through the Flex node.
- No direct client access to S3 is required.
- Simplifies security and network design.
- Uses Flex node resources for data movement.
- Common in highly secured enterprise environments.

## 3. Hybrid Mode

Best for: Large enterprises with multiple sites, network zones, or mixed workload requirements.

Characteristics

- Some workloads use direct-to-S3 acceleration.
- Other workloads use the Flex node as a proxy.
- Allows optimization based on network topology and security requirements.
- Often the preferred design in large, distributed environments.

## Flex Deployment Architecture Options

Separately from the data path modes, Flex Appliance supports the following deployment architectures.

Architecture | Description
--- | ---
2-Node Flex Cluster | Minimum supported deployment; provides resiliency and availability.
Scale-Out Flex Cluster | Additional Flex nodes are added to increase throughput and capacity management.
Independent Compute/Storage Scaling | Flex nodes and external S3 storage can be expanded independently.

Flex Appliance is always deployed with:

- Two or more Flex nodes.
- Certified Dell, HPE, or Lenovo servers.
- Certified external S3 storage.
- 100Gb networking recommended for large-scale deployments.

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