G-Core Labs, an international provider of cloud and edge solutions, has opened the second region of its public cloud in Moscow. The solution is a multi-functional virtual data center that allows companies in various industries, including media, online retail, game developers and publishers, banks and insurance companies, educational and medical organizations and services, to scale up their IT infrastructure in minutes, as well as significantly accelerate the development, testing and launch of new products and services.
The first G-Core Labs public cloud region in Luxembourg was launched in November 2019.
"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.
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 fast & seamless automatic scaling, their load balancer, system backup and data disaster recovery. G-Core Labs allows its clients to 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.
Another useful feature of G-Core Labs IaaS service is an option to manage resources by distributing them among projects (cost centers). This makes the use of resources by projects or departments transparent for the clients. It means that the users can see not just the lump number of resources used within a certain period of time for all projects, but detailed info about how much was spent on each project.
Within platform services, or PaaS, G-Core Labs plans to add an option of autodeploying 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.