Depending on the scale of your organization and the current IT infrastructure, we can implement a Hybrid Cloud model to serve the needs and improve security. A combination of private servers and public data centers is possible and available for any business purpose.

Nutanix uses its industry-leading, 100% software-defined hyperconvergent infrastructure to deliver a single cloud platform that seamlessly revitalizes your hybrid and multi-cloud strategy. Whether on-site or in the cloud, you get standardized management and standardized processes with one-click simplicity, intelligent automation, and constant availability.

Amazon Web Services (AWS) is the most comprehensive and widely used cloud platform in the world and offers over 200 fully functional data center services worldwide. Millions of customers – including the fastest growing startups, the largest corporations and leading government agencies – use AWS to cut costs, become more agile and innovate faster.

Microsoft Azure, commonly referred to as Azure, is a cloud computing service created by Microsoft to create, test, deploy, and manage applications and services through Microsoft-managed data centers. It offers software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS), and supports many different programming languages, tools, and frameworks, including software specific to Microsoft and third-party systems.

Azure is the best-selling commercial service provider in the cloud, although this label is partly due to the “power of the company in Office 365 Commercial and Microsoft 365,” which can artificially add to the company’s overall “clean cloud”.

The Google Cloud Platform (GCP) offered by Google (Enterprise) is a set of cloud computing services that run on the same infrastructure that Google uses internally for its end-user products, such as Google Search, Google Mail, File Store, and YouTube.

In addition to a range of management tools, it also offers a range of modular services in the cloud, including Computing, Data Storage, Data Analysis and Machine Learning.