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Route Analysis

Data Detour: Almaty to Saipan via Moscow, 3104 km Off Course

📍 Moscow, RU: the hub the traffic detours through

When internet traffic from Almaty, Kazakhstan, is directed to Sugar Dock on the island of Saipan in Micronesia, it seems logical to expect it to take the shortest route via fiber-optic backbones. However, the reality, as recorded by GeoCables on September 15, 2026, turned out to be far more convoluted: the data first traveled through Moscow, deviating 3,104 km from a straight line, before reaching its final destination.

🇰🇿Almaty1 ms🇷🇺Moscow58 ms🇲🇵Saipan434 ms
Direct ~7 151 km · actual ~12 807 km · ×1.8

Why was the route so complicated?

To begin with, let’s examine the network providers through which the traffic passed: Signal Telecom LLP (Kazakhstan), JSC Kazakhtelecom (Russia), and PTI Pacifica Inc. The Micronesian Telecommunications Corporation (Micronesia). These companies represent autonomous systems (AS) that facilitate data transport through their backbones. However, there are no direct peering agreements or backbone cables connecting Kazakhstan and Micronesia. As a result, the route was forced to transit through Moscow, where Kazakhtelecom has major points of presence and peering with other global operators.

This routing pattern can be explained by economic logic: providers choose paths through backbones with the lowest data transmission costs. Moscow, as a major telecommunications hub, serves as a transit point due to its high level of peering with international operators. However, this lengthens the path and increases latency, which becomes particularly noticeable when compared to the theoretical minimum: instead of 72 ms (the latency of light in fiber over a direct distance), the actual RTT was 434 ms, nearly six times higher.

Practical consequences for users

Such latency can significantly impact the performance of many digital services. For instance, in real-time video calls, a 434 ms delay can lead to connection drops or desynchronization of audio and video. Online gaming, where every millisecond counts, would also suffer: players would experience lag, making gameplay virtually impossible. In the financial sector, where speed is critical, delays could result in missed trades, especially in highly volatile markets. Cloud services, such as remote desktops or data processing, would also become less efficient, reducing user productivity.

Infrastructure-related causes of the detour

The key reason for this routing is the lack of direct cable connections between Central Asia and Micronesia. In the Almaty region, the main point of presence is Signal Telecom LLP, which hands off data to Kazakhtelecom. The latter has a strong presence in Moscow, where it connects with international operators. From there, the data travels through global backbones to the Pacific region, connecting to PTI Pacifica Inc. in Saipan.

In the context of this route, it is worth mentioning recent geological events in the region, which, as GeoCables data shows, did not affect the routing but add context to the overall picture. For example, earthquakes with magnitudes of 5.1 in Kyrgyzstan (76 km south of Daroot-Korgon) and 5.0 near Chayek occurred in June and August, respectively. However, these events were hundreds of kilometers away from the route. They did not impact the physical cable infrastructure and were not the cause of the detour.

What can be done?

To address such issues, investments in direct submarine cables connecting Central Asia with the Pacific region or the expansion of peering agreements between local and international providers are necessary. These steps would help reduce latency, improve connection quality, and lower transit costs.

GeoCables continues to monitor global routes, identifying bottlenecks and proposing ways to optimize them. Every detoured route is a challenge that can be resolved through infrastructure development and improved network collaboration.

Evgeny Korolev
Written by
Evgeny Korolev
Infrastructure Engineer · Founder of GeoCables
Built GeoCables to monitor submarine cables in real time. Runs his own distributed network of measurement servers, including in regions poorly covered by public internet measurements.

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