TL;DR · 30-second read
The Short Version
Ukrainian drones have knocked out two of the five huge computer buildings run by Yandex, the company known as Russia’s Google. Russians then reported trouble reaching a video streaming service, an online bank and the national railway.
One building held two of the three supercomputers Yandex uses to teach its chatbot. That is a lot of eggs in one basket.
Ukraine called the strikes a response to Russian attacks on its own computer buildings, which disrupted phone and internet service for thousands. The internet lives in real buildings, and those buildings are now wartime targets.
Ukrainian drone strikes on October 8 and 9 knocked out two of the five data centers operated by Yandex, the Russian technology company that runs the country’s most popular search engine, Ars Technica reported, citing Reuters and the independent Russian publication Meduza. The sites are in the Sasovo and Kaluga regions. Sasovo houses two of the three supercomputers Yandex uses to train its YandexGPT AI model, and Kaluga is the company’s largest data center.
Yandex said no employees were hurt and acknowledged disruptions to some services. Russian users reported problems reaching media websites and the apps of video platform Ivi, digital bank T-Bank and state-owned Russian Railways. Ukrainian President Volodymyr Zelenskyy described the attacks as a “symmetrical response” to a Russian drone campaign against Ukraine’s data centers, which has disrupted mobile and internet service for thousands of Ukrainians since late September.
Executive Summary
The strikes hit two different kinds of concentration in a single campaign. Sasovo held most of Yandex’s AI training machines by count, while Kaluga is its largest facility. Together they represent 40% of the company’s data center sites, and Yandex’s AI chatbot and other online services have struggled to keep running as a result.
The episode matters beyond Russia because it isolates a design tension in AI infrastructure. Large-scale AI training favors packing machines tightly into one location, while resilience favors spreading them apart. In a conflict zone, that tradeoff stops being an abstract engineering preference and becomes a question of how much capability a single attack can remove.
It is also not an isolated event. Iranian drones knocked out multiple Amazon data centers in Bahrain and the United Arab Emirates earlier in 2026, and Russia has been striking Ukrainian facilities since late September. For operators and their customers in exposed regions, physical attack now belongs in the same risk discussion as power, cooling and connectivity.
Two Supercomputers, One Address
The most consequential number in this story is not two of five data centers. It is two of three supercomputers at a single site. A supercomputer used for AI training is a large group of processors linked by very fast internal networks, because the machines must constantly exchange data as a model learns. That requirement pulls hardware physically together: distance adds delay, and delay slows the job. Concentration is therefore often a sensible engineering choice rather than an oversight.
The same choice creates a single point of failure, meaning one location whose loss removes a disproportionate share of a capability. By count, Sasovo held two-thirds of the supercomputers Yandex uses to train YandexGPT. Count is not the same as capacity, since the machines may differ in size, and the extent of damage to each has not been itemized. The exposure is still clear: one site carried most of the company’s named training systems, and an attack on that site put them at risk together.
Those most directly affected are the teams that depend on those machines to build and update models. Ordinary backup does not fully solve the problem. Copies of data and model checkpoints, which are saved snapshots of a model in training, can be stored elsewhere, but the specialized compute needed to resume work at the same scale cannot simply be restored from a file.
Training Can Wait. A Chatbot Cannot.
AI workloads fall into two broad categories with very different tolerance for interruption. Training builds or updates a model and can often be paused and resumed later, at a cost in time. Inference is the live work of answering user requests, and when it fails, customers notice immediately. The reported struggle to maintain Yandex’s chatbot shows that the strikes reached the service people use, not only the long-term development pipeline.
The Kaluga strike illustrates the second half of that risk. Losing a company’s largest facility tests whether the remaining sites can absorb its traffic. Good failover, the automatic shifting of work to surviving locations, depends on keeping spare capacity available. That capacity is expensive to hold in reserve during normal operation, which is why it tends to be most tightly rationed when demand for AI compute is high.
The list of reported disruptions also carries a lesson for buyers. It ranged from a bank and a railway to a dating app, a real estate aggregator, a self-publishing platform and a leading soccer club’s website. Organizations that see their digital operations as distributed may still rely on one provider’s physical footprint. For enterprise customers, the practical questions are which sites their services actually run on, whether they can move to another region or provider, and whether that move has been tested under realistic conditions.
Site Security Stops at the Fence
Data center security has traditionally focused on perimeters, access control and insider threats. Those measures do little against one-way attack drones, which are uncrewed aircraft designed to strike a target and not return. Firepoint, the Ukrainian company whose FP-1 drones it said were involved in the Kaluga strike, makes that class of weapon. Defending against them is largely a matter for national air defenses, not facility managers, and Ukraine’s own shortage of interceptor weapons shows how difficult that defense can be even for a state at war.
That shifts the operator’s realistic options from preventing every hit to limiting what any one hit can do. The available tools are geographic dispersal, spare capacity, separated power and network paths, offsite copies of critical data, and rehearsed recovery plans. Each costs money and some reduce efficiency, particularly for tightly linked training clusters. The decision is therefore a business tradeoff: how much performance and capital to give up in exchange for surviving the loss of a site.
This should not be stretched into a claim that every data center faces the same danger. The reported attacks are tied to active conflicts, and most facilities operate far from them. Yet Amazon’s affected sites were in Bahrain and the UAE, not in the countries that launched the February attack on Iran, which suggests that regional exposure can extend beyond the main combatants. For operators and customers choosing locations in or near geopolitical flashpoints, conflict risk belongs in siting decisions alongside land, power and connectivity.
Testing the Competing Claims
The parties describe the same events in markedly different terms. Zelenskyy said Ukraine was responding “with high precision,” adding: “Another data center was hit as well—our symmetrical response.” Yandex’s acknowledgment of disruptions to “some services” is narrower than the picture of two facilities knocked out. Satellite imagery from Planet Labs shows damage at Sasovo, which supports the fact of a strike there but cannot on its own establish how much computing capacity was lost or how long it will stay offline.
Each statement deserves scrutiny in light of its author’s interests. A government at war has reason to emphasize precision and effect, a drone manufacturer benefits from being associated with a successful strike, and a company has reason to reassure customers and users. The measure that will ultimately matter is operational: how quickly Yandex’s services stabilize, and when its training work resumes at full scale.
Background
A data center is a secured building filled with the computers, power systems and cooling equipment that keep online services running. Yandex operates Russia’s most popular search engine and has developed its own family of AI models under the YandexGPT name. Before these strikes it ran five data centers, three of which remain outside the reported damage.
Russia has regularly launched mass missile and drone attacks on Ukrainian cities since beginning its full-scale invasion in February 2022, hitting power grid infrastructure, transportation hubs and residential buildings. Ukraine has expanded its own medium-range and long-range drone campaign, focusing on Russian military bases, supply lines, Russian-linked shipping and energy infrastructure such as oil refineries. In summer 2026, it also targeted warehouses of the Russian e-commerce companies Wildberries and Ozon, before turning to Yandex’s data centers in October. Source: Ukraine’s drones knock out AI data center belonging to “Russia’s Google” (Ars Technica), on Ukrainian drone strikes against Yandex data centers in Russia’s Sasovo and Kaluga regions.Sources