For an AI inference deployment, put the locations of your users and data dependencies into the site brief alongside power capacity. Ask the application team to define the response time it needs, then have the network team evaluate the paths each candidate site could use to meet that target.

A useful comparison starts with named destinations and a measurement plan. It gives the acquisition team a way to assess whether a site’s connectivity suits the intended service before committing to carrier construction or a property purchase.

Map the destinations that matter

List the user markets, customer facilities, cloud regions, data stores and other services involved in the application. Give each destination a priority and identify the traffic that must travel to it. Ask which dependencies can be placed at the proposed site and which will remain elsewhere.

AWS’s location-selection guidance recommends evaluating placement against both user and data locations to improve latency and throughput. Apply that question to your physical-site shortlist: where does the application need to communicate, and what path will carry that traffic? AWS guidance on workload location and network requirements

Define the response-time budget

Ask the application team to separate the user-facing response target into measurable stages, including network travel, request handling, model execution and any external data retrieval. Specify what is being measured. A target for the first response from a streaming service differs from a target for completing the entire request.

Have the network team state the metric, endpoints, traffic conditions and acceptance threshold. Keep network measurements alongside representative application tests so the buyer can see how the proposed connection supports the actual service.

Measure the proposed path

Request the carrier’s service proposal, handoff locations, upstream connections and available performance evidence. Ask how closely any test path matches the service that would be delivered to the parcel. Record the date, destination, circuit and test conditions with each result.

Google Cloud’s Performance Dashboard documentation distinguishes packet loss from latency measured as round-trip time and explains that reported results depend on the measurement method. Ask your network team to document those details in the site comparison. Google Cloud documentation on network performance metrics

For a development site, identify the gap between the available evidence and the final connection. A test from a carrier’s nearby facility can inform the review, while the service to the proposed building still needs its own delivery and acceptance plan.

Test the backup route against the same targets

Ask the carrier and network team to describe what happens when traffic moves to the alternate circuit or upstream provider. Request the expected route and destination performance under that condition. Check the physical paths using our fiber due diligence guide.

Consider a hypothetical application with a 250-millisecond response target and an internal 50-millisecond network round-trip budget. Site A’s proposed primary route meets that network budget in testing, but its alternate route measures 80 milliseconds. Site B’s tested routes each remain within the budget. Ask the application team to assess the effect on user service and document the remaining design choices. These figures illustrate a review method and describe no actual site.

Bring performance and delivery into one shortlist

For each candidate, retain the destination list, proposed circuits, test evidence, unresolved questions and expected activation dates. Include any additional carrier work in the deployment cost comparison and review the operating scenarios with the facility team.

Explore the Ace Miners powered-land directory or share your AI inference site requirements. Include your target user markets, critical network destinations, initial IT load and required deployment date so the search reflects both power and application needs.