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Method for Proactive and Predictive RPO Calculation on Complex Hybrid Cloud IT Environments by Implementing a Smart Provisioning Model

IP.com Disclosure Number: IPCOM000246256D
Publication Date: 2016-May-20
Document File: 7 page(s) / 170K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a system and method to calculate a Recovery Point Objective (RPO) and a Recovery Time Objective (RTO) for complex IT environments. This solution equips IT teams with a system and method to pro-actively react to/prepare for future unfortunate events and reduce or eliminate the negative impact to the business.

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Method for Proactive and Predictive RPO Calculation on Complex Hybrid Cloud IT Environments by Implementing a Smart Provisioning Model

In the era of technology, business continuity is critical to a company as a means of preventing damage to operations and loss of revenue due to unplanned eventualities.

The Recovery Point Objective (RPO) is the maximum period in which data might be lost from an Information Technology (IT) service due to a major incident and the targeted duration. The Recovery Time Objective (RTO) is maximum duration to achieve system restoration after a disaster or disruption in order to avoid unacceptable consequences associated with a break in business continuity. Business continuity plans include RPOs and RTOs in order to define the maximum downtime and data loss that a company is willing to accept.

Existing solutions can help clients measure the ability to meet set RPO and RTO objectives. Current tools can:

Monitor the replication connectivity between two storage subsystems Identify single points of failures within an IT infrastructure
Warn IT administrators about upcoming issues that might impact the core business

These techniques are limited, however, to include very few of the elements of a complex IT infrastructure. This can cause inaccurate RPO calculations and produce reactive, rather than proactive, solutions when disaster occurs. In addition, changes to the infrastructure can have a negative impact on the performance and response times from that point forward .

The novel contribution is a system and method to calculate RPO and RTO for complex IT environments . This solution equips IT teams with a system and method to pro-actively react to/prepare for future unfortunate events and reduce or eliminate the negative impact to the business.

The method provides a central processor that enables several capabilities. The system dynamically reallocates and/or provides recommendation on infrastructure resources to meet RPO on mixed environments (e.g., adjust bandwidth, or limit IOPS for one

APP to increase IOPS on another, etc.). This is easy to implement with tiers for cloud resources. Using cloud Infrastructure analytics (historic and actual data), the system can dynamically determine and predict points in time where RPO/RTO could not meet customer needs. The system can consider architecture latency and other external factors (e.g., bottlenecks) outside the data center infrastructure to predict RTO/RPO in cloud environments and then use those as triggers to apply live adjustments and update environment variables. In addition, the system can apply a real time on demand thin provisioning how-to model for

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dynamically assigning resources to meet RPOs in a hybrid cloud environment.

In an alternative embodiment, the system can use social analytics of historic user demands and upcoming social behavior to determine when peaks of infrastructure usage will occur and make the adjustments needed...