# Multi-Cloud

Multi-cloud refers to the practice of using cloud computing services from two or more cloud providers within a single architecture. Rather than relying on a single vendor for all infrastructure needs, organizations distribute workloads across providers such as AWS, Google Cloud, Azure, and others to take advantage of each provider's strengths, pricing, or regional availability.

## Why adopt a multi-cloud strategy

Organizations pursue multi-cloud for several practical reasons:

* **Avoid vendor lock-in**: Spreading workloads across providers makes it easier to migrate away from any single platform if pricing, features, or terms change.
* **Leverage specialized services**: Different providers excel at different capabilities. A team might use Google Cloud for machine learning workloads while running its primary API services on AWS.
* **Geographic coverage**: Not all providers have data centers in every region. Multi-cloud enables organizations to place workloads closer to users by choosing the provider with the best regional presence.
* **Resilience and redundancy**: Distributing critical services across providers reduces the blast radius of a single-provider outage.
* **Regulatory compliance**: Some regulations require data to reside in specific jurisdictions. Multi-cloud gives teams the flexibility to meet these requirements using whichever provider operates in the required region.

## Challenges of multi-cloud

Multi-cloud introduces complexity that must be managed deliberately:

* **Consistent security policies**: Each provider has its own identity, networking, and encryption models. Enforcing uniform access controls and audit logging across providers requires careful planning.
* **Operational overhead**: Teams need expertise across multiple platforms, and tooling such as infrastructure-as-code templates and CI/CD pipelines must work with each provider.
* **Networking and latency**: Cross-cloud communication adds latency and data transfer costs. Architects need to minimize cross-provider calls for latency-sensitive paths.
* **Observability**: Aggregating logs, metrics, and traces from multiple providers into a unified view requires additional tooling.

## Multi-cloud and API gateways

An API gateway that is not tied to a specific cloud provider is a natural fit for multi-cloud architectures. The gateway serves as the single entry point for API consumers, abstracting the fact that backend services may be spread across different clouds. It handles authentication, routing, and policy enforcement in one place, regardless of where the upstream service runs.

Serverless API Gateway runs on Cloudflare Workers, which operates on Cloudflare's global edge network rather than on any single public cloud. This means the gateway itself is provider-neutral. It can route incoming requests to backend services running on AWS, Google Cloud, Azure, or any other provider with a reachable HTTP endpoint. Teams define their upstream servers in the gateway configuration, and each path can route to a different backend regardless of where that backend is hosted.

Because Cloudflare Workers follow a pay-per-request model and scale automatically, the gateway layer does not require capacity planning tied to any single cloud provider's compute model. This makes it practical to add, remove, or replace backend providers without modifying the client-facing API surface.

## Related documentation

* [Servers Configuration](/configuration/servers.md) - Define upstream servers across multiple cloud providers
* [Configuration Overview](/configuration/overview.md) - Declarative gateway configuration
* [Deployment with Wrangler](/deployment/wrangler.md) - Deploy the gateway to Cloudflare's edge network
* [Getting Started](/getting-started/introduction.md) - Set up your first multi-cloud API gateway


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