Yandex Releases Perforator to Help Businesses Cut Server Costs

Posted by By Dan Taylor 2 Min Read

Yandex has made the source code for Perforator publicly available. This tool helps businesses optimize their services’ code and reduce server maintenance costs. It is designed for both large companies and startups.

Real-Time Application Analysis

Perforator monitors applications running on a server in real time. It shows how server resources are distributed and identifies which programs consume the most. Despite its deep analysis capabilities, the tool does not interfere with the code or affect program operations. It also requires minimal resources to function.

Security remains a priority, as Perforator does not transfer code-related data outside a company. This ensures compliance with information security requirements.

Yandex’s Internal Use and Future Plans

Yandex uses Perforator to manage server loads and improve the performance of major services like Search and Advertising. Now, developers, companies, and researchers worldwide can take advantage of the tool.

Alexey Gusakov, Yandex Search STO, stated that Yandex released Perforator as open-source to share expertise with the IT community. The company also plans to enhance the tool further. Future updates will include better support for programming languages like Python and Java, along with features to integrate Perforator with automated code optimization solutions.

Availability on GitHub

The Perforator source code is available on GitHub, allowing developers to access and contribute to its development.

Previously, Yandex also released its YaFSDP library, which speeds up the training of large open-source language models by up to 25%.

Dan Taylor
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Dan Taylor is the founder and editor of International Search Insights (ISI), the publication behind ReadIsi, and a Partner and Head of Innovation (Search & AI) at SALT.agency. He has worked in search for more than a decade, in-house and agency-side, and is regarded as one of the West’s leading voices on search engines beyond Google, including Yandex, Baidu, Naver and Cốc Cốc. On ReadIsi, Dan covers the engines and AI answer platforms that English-language coverage tends to miss: Baidu and ERNIE, Yandex and Alice AI, Naver, Cốc Cốc, Shenma, Sogou, WeChat and Weibo search, plus DeepSeek and Alibaba’s Qwen. He also keeps dated records of documented changes, such as the Yandex, Baidu and Naver algorithm update histories and the DeepSeek, ERNIE and Qwen model update histories. His approach is to take learnings from global search engines and apply logic with a high evidence threshold. A claim needs a source, patterns seen in one market are treated as a hypothesis until they are checked in another, and where the evidence is thin he says so. For brands, that means advice built on what can be shown, with measurement that separates being cited from being chosen. Dan is credited with coining the term “edge SEO” and won the inaugural TechSEO Boost research competition in 2018 for his work on CDN and edge changes for SEO. In 2026 he was credited with coining “Infinite Tail” to describe how keyword research is changing with AI search. He is the author of AI Search Marketing For The Travel Sector, writes for Search Engine Journal, Search Engine Land and Travel Marketing Guy, and has advised technology, SaaS, travel and enterprise ecommerce brands, including Cloudflare, GitLab and Airbnb. He has given multiple talks and panels at the International Search Summit in Barcelona, and has also spoken at Optimization Moscow, brightonSEO, Google Search Central Live Deep Dive Asia in Bangkok, Athens SEO and the Asia SEO Virtual Summit 2026, where his talk looked at how Baidu, Naver, DeepSeek, Tencent, Cốc Cốc and Yandex built their own AI answers.
Founder & Editor