Understanding Cloud Disaster Recovery Challenges

Cloud Disaster Recovery (DR) is to provide an organization with an automated and reliable approach (es) to data recovery and failover in the event of a man-made or natural catastrophe.

Disaster recovery as a service is perceived as a future low-cost service designed after the cloud computing nomenclature is expected to offer flexible replication be it physically or virtually. This phenomenon allows the recovery of data center infrastructures and critical servers to be replicated in the cloud as a service. The architecture is configured with pre-built options to support virtual recovery environments characterized by network connectivity, security, and server failover. However, there are some challenges that one might face during cloud disaster recovery. Let’s understand them in detail.

Disaster recovery as a service is perceived as a future low-cost service designed after the cloud computing nomenclature is expected to offer flexible replication be it physically or virtually. This phenomenon allows the recovery of data center infrastructures and critical servers to be replicated in the cloud as a service. The architecture is configured with pre-built options to support virtual recovery environments characterized by network connectivity, security, and server failover. However, there are some challenges that one might face during cloud disaster recovery. Let’s understand them in detail.

Dependency: Customers are totally dependent on cloud service providers
due to lack of control over the system and the data as the data backup is on
premises of service providers.

Cost: Cloud service providers annually charge differently for interrelated
DR systems as a service operation annuls the initial cost savings expectation of the consumers. These costs include the initializing cost, a
form of a liquidated annual cost, ongoing cost (storage cost, data transfer
cost and processing cost), and disaster cost (charges for recovered disasters
and associated cost of unrecoverable disasters).

Failure detection: A failure detection time is expected to be very short so
that the system downtime can be adequately managed on time. Hence, it
is highly expedient to report a failure immediately when it is detected to
facilitate quick DR and reduce system downtime.

Security: Cyber terrorism attacks and natural disasters are major problems.
Mechanisms must be developed to protect important data and ensure its
recovery in the case of a disaster.

Data storage: Storage single points of failure and data loss are critical
challenges to store data in cloud service providers’ DR solutions. To manage
this, the following are suggested as potential solutions:

• Local backup: An alternative backup plan can be made for both data and complete the application at the customer’s end using a Linux box and seamlessly updated through a secured channel. In case of a disaster, the local backup can be leveraged for recovery purposes.
• Geographical Redundancy and Backup (GRB): With this approach,
  two cloud zones are located at different geographical locations, and one synchronously mirrored as a replication of the other. A monitor is deployed to detect the disaster at each zone. However, it is expensive and
  unaffordable.
• Inter-Private Cloud Storage (IPCS): This approach provisions three
  different geographical backup locations for business data storage such that each backup location is dedicated to backup only one of the servers, local backup server (LBS) or remote backup server (RBS).

Resource management: Improved technologies for hardware and software
application management must be deployed for seamless critical data DR services. Examples include the use of the fastest disk technology, changing dirty page threshold, and replacement of risky devices by determining factors like heat dissipation, power consumption, carbon credit utilization, and so on from time to time.

Hope this was helpful.