Cloud Location Finder now GA: Programmatic Multi-Cloud Placement for DevOps

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As infrastructure scales across heterogeneous environments, manual location mapping becomes a bottleneck for CI/CD and automated provisioning. Architecting for low latency or regulatory compliance requires more than a static map; it requires a dynamic, queryable source of truth.

Last year, we introduced Cloud Location Finder in preview. Today, we are announcing its General Availability (GA). This service provides a unified API surface to find cloud locations (like regions, zones, Google Distributed Cloud Connected) based on up-to-date location metadata like territory, carbon footprint, and distance across Google Cloud, AWS, Azure, and OCI.

Natalie Godec, a Senior Cloud Architect at Zencore, describes the tool as a game-changer for migration planning: “Cloud Location Finder has revolutionized our architecture strategy by turning complex location decisions into a simple, data-driven process. Balancing latency requirements, data sovereignty constraints, and carbon requirements across cloud regions used to require extensive research - now we can identify the optimal deployment location for our clients in minutes.”

What’s new in the GA Release?

1. Google Distributed Cloud (GDC) Edge Visibility

For low-latency applications with multiple locations (e.g., gaming, healthcare), Cloud Location Finder now exposes metadata for GDC Connected locations. This allows your placement logic to treat edge nodes as first-class targets alongside standard public regions, enabling more granular workload distribution.

2. Enhanced proximity queries & cross-cloud search

We have enhanced the search functionality to support more complex queries. Previously you could run inter-provider search queries only, finding the nearest cloud location across providers (e.g. Find the nearest GCP region from an AWS region or vice versa).

Today, we are enhancing this to support intra-cloud search (e.g. find the nearest Azure region from an AWS region us-east-1). This is critical for performance optimization, multi-cloud networking, and data egress optimization. The search scenarios CLF supports are now:

  • Intra-provider search: Identify the optimal secondary location for failover within a single cloud. For example, “What is the nearest GCP location to my GCP location?”

  • Inter-provider search: Programmatically determine the nearest location between two providers, such as Google Cloud, AWS, Azure, or OCI. For example, “What is the nearest AWS region to my Azure region to minimize cross-cloud latency?”

Implementing Cloud Location Finder

This service provides a REST API that returns JSON metadata. The example below shows how to use the gcloud CLI or API to automate GKE region selection

# Example: Query for GCP region nearest to an AWS region us-east-1

curl -H "Authorization: Bearer $(gcloud auth print-access-token)" -H "X-Goog-User-Project:clf-e2e-testing" "https://cloudlocationfinder.googleapis.com/v1/projects/clf-e2e-testing/locations/global/cloudLocations:search?sourceCloudLocation=projects/clf-e2e-testing/locations/global/cloudLocations/aws-us-east-1&query=cloud_provider=CLOUD_PROVIDER_GCP%20AND%20cloud_location_type=CLOUD_LOCATION_TYPE_REGION&page_size=1"

Technical specifications & attributes

With Cloud Location Finder, you can count on reliable data which is refreshed every 24 hours to ensure your automated placement scripts are targeting based on your proximity, territory, provider, and sustainability requirements.

  • Unified Schema: Standardized JSON responses for Google Cloud, AWS, Azure, and OCI.

  • Rich Metadata: Includes ISO territory codes, RTT-based nearest location, and real-time sustainability data (for GCP regions and zones).

  • No-Cost API: Access these datasets programmatically without incurring additional egress or API call fees.

For leaders managing massive compute needs, this visibility is vital. “As we scale our global AI backbone, Cloud Location Finder is critical to programmatically embedding sustainability into our infrastructure,” says JC Escalante, who manages AI infrastructure for thousands of users. “It ensures every workload we deploy automatically aligns with our carbon reduction goals without sacrificing performance.”

Next steps for developers

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