Multi-Cloud Region Latency Calculator

Latency between cloud regions is dominated by three factors: geographic distance (which sets a hard physical lower bound based on the speed of light in fiber), the number of network hops between backbone peering points, and congestion or queuing in intermediate routers. Cloud providers like AWS, GCP, and Azure maintain private backbone networks between their own regions, which typically have lower latency than public internet paths. However, inter-provider traffic (e.g., a user on AWS eu-west-1 hitting an Azure service in West Europe) must traverse public internet exchange points (IXPs), adding 5–30ms of extra overhead. Geographic distance alone explains roughly 80% of observed RTT variance across regions.

In active-active, all regions simultaneously serve live traffic and accept writes. Requests are routed to the nearest region, achieving the lowest possible latency for users worldwide. The complexity cost is real-time data replication and conflict resolution — you need eventual consistency guarantees (CRDTs, vector clocks) or a globally distributed database like CockroachDB, PlanetScale, or AWS Aurora Global. In active-passive, one region ('active') handles all writes and the others ('passive') serve read traffic from replicas. Failover is simpler but write latency for non-primary users is high (users in Asia hitting a primary in US East add 150–200ms of write latency). Active-passive is the right choice for most teams until they hit meaningful global write volume.

A CDN solves latency for static and cacheable content (HTML, JS, CSS, images, API responses with TTL). It is cheaper, simpler to deploy, and delivers sub-10ms TTFB to users worldwide by serving from 200+ edge PoPs. Multi-region deployments solve latency for dynamic, personalized, or write-heavy workloads that cannot be cached. The practical rule: if your response is the same for all users or can be cached for 1+ second, use a CDN. If your response requires a database read of user-specific data, prefer regional deployment close to your users. Most production architectures combine both: CDN for static assets and cached API responses, regional origins for dynamic data. Cloudflare Workers and Fastly Compute@Edge blur this line by running full compute logic at the CDN edge.

Anycast is a routing technique where multiple servers share the same IP address. BGP routing automatically directs each user's packets to the topologically nearest node advertising that address. Cloudflare, AWS Route 53, and Google Cloud DNS all use anycast for their global networks. When you resolve a Cloudflare-proxied hostname, all users in Tokyo, London, and São Paulo get the same IP but are routed to the nearest Cloudflare PoP — without any DNS-level geo-routing. Anycast is ideal for UDP services (DNS, NTP) and stateless HTTP/HTTPS because TCP connections land on the nearest server naturally. For stateful workloads, DNS-based geo-routing (Route 53 Latency Routing, GCP Traffic Director) is more appropriate since you need session stickiness.

The absolute minimum round-trip time between two points is determined by the speed of light in fiber optic cable (~200,000 km/s, or about 2/3 of the speed of light in vacuum). The formula is: RTT_min = (distance_km / 200,000) × 2 × 1000 ms. For example, New York to London (~5,500 km) has a theoretical minimum RTT of 55ms. Real-world RTT is typically 1.3–2× the theoretical minimum due to: non-straight fiber cable routes, signal amplification delays, processing overhead in routers and switches, and TCP/TLS handshake overhead. If you are seeing latency more than 2.5× the theoretical minimum, it suggests suboptimal routing or peering — worth investigating with traceroute or tools like PerfOps.