Method and device for estimating optimal resources for server virtualization

An estimation computing device for estimating optimal resources for server virtualization, comprising:

• a processor;
• and
• a memory communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which are executed by the processor to perform operations comprising:
• on execution, causes the processor to:
• receiving input data relating to requirements of server virtualization from a user device, wherein the input data comprises asset information, type of workload, breakup of each data center location, application information, hardware specification and architectural consideration;
• filtering the input data by applying filtering rules, wherein the filtering rules filters out applications which are legacy in nature, operating system which are not considered for consolidation, and server locations which are outside the scope of server virtualization:
• generating current Information Technology (IT) landscape information of set of servers using the filtered input data;
• determining values of virtualization parameters for a set of target servers using the current IT landscape information and predefined rules;
• and
• determining IT landscape information of the set of target servers using the current IT landscape information and the values of virtualization parameters for estimating optimal resources for server virtualization.

A non-transitory computer readable medium including instructions stored thereon that when processed by at least one processor cause an estimation computing device to perform operations comprising:

• receiving input data relating to requirements of server virtualization from a user device, wherein the input data comprises asset information, type of workload, breakup of each data center location, application information, hardware specification and architectural consideration;
• filtering the input data by applying filtering rules, wherein the filtering rules filters out applications which are legacy in nature, operating system which are not considered for consolidation, and server locations which are outside the scope of server virtualization;
• generating current Information Technology (IT) landscape information of set of servers using the filtered input data;
• determining values of virtualization parameters for a set of target servers using the current IT landscape information and predefined rules;
• and
• determining IT landscape information of the set of target servers using the current IT landscape information and the values of virtualization parameters for estimating optimal resources for server virtualization.