G-Core Labs opens public cloud region in Moscow



Vsevolod Vayner, G-Core Labs cloud platform department head Vsevolod Vayner, G-Core Labs cloud platform department head

As well as the cloud region, the company will be adding an option of auto-deploying Kubernetes clusters for container orchestration in the near future.

Cloud and edge solutions provider G-Core Labs has opened the second region of its public cloud in Moscow, Russia.

The solution is a multi-functional virtual data centre that allows companies in various industries, including media, online retail, game developers and publishers, banks and insurance companies, educational and medical organisations and services, to scale up their IT infrastructure.

The first G-Core Labs public cloud region in Luxembourg was launched in November 2019, where the company made mention that it plans to further expand internationally through other data centres.

“The opening of a new cloud point in Moscow is good news both for local customers who need to solve their business challenges within the country and have minimal latency, and foreign companies who want to start their business in Russia, meet all necessary legislation (including in the field of personal data storage) and have an international provider as a partner,” said Vsevolod Vayner, G-Core Labs cloud platform department head.


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The company added that as part of the IaaS model, the G-Core Labs solution provides the functionality of virtual machines, not limited in capacity, with the options of automatic scaling, their load balancer, system backup and data disaster recovery.

G-Core Labs users can create virtual cloud networks where they can set up private clusters to do necessary computations or to isolate a certain set of applications within their own cloud network.

Within platform services, or PaaS, G-Core Labs plans to add an option of auto-deploying Kubernetes clusters for container orchestration soon, to finish the integration of a platform for developing, testing and launching AI applications and Hadoop-based systems for working with big data.

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