Disaster recovery in the cloud – is it necessary?
Mark Bentkower, CISSP, Director of Systems Engineering, ASEAN, Commvault
Disaster recovery in the cloud? Are you a sceptic?
Businesses in the Asia/Pacific region may have been more gradual in adopting cloud services but they are increasingly investing more in the cloud today for simple, off-site storage purposes. And it’s about to grow significantly – Gartner predicts that total public cloud services spending in the mature AP region will rise to $12.9 billion from $7.3 billion by 2019.
When it comes to storage space constraints and even tighter budgets, the cloud is perceived as the cure-all for many organisations. Two particularly important benefits of using the cloud are escaping capital expenditure on hardware, software and services; and reducing physical space at the office. However, IT specialists within large organisations have typically been cautious of cloud services due to security concerns. According to an IDC survey, a growing number of organisations across Asia/Pacific that are using the cloud consider security as a top pain point when migrating datasets into cloud environments.
Yet organisations remain vulnerable to unpredictable downtime. Disasters loom, both man-made and natural. Service availability cannot be interrupted in today’s technology-and data-driven business environment. An information management strategy that ensures data in the cloud is protected and readily recoverable is critical. So how can companies find that balance between ensuring security while still leveraging the cloud as part of an effective and practical DR plan?
1. Begin with a risk analysis
Before deep diving into cloud DR planning, organisations should take a step back and begin with risk analysis. Risks run the gamut from natural to man-made disasters – everything from disgruntled employees and human errors to accidents and SaaS application provider system outages. Weigh the likelihood of these disaster occurrences and map a plan for mitigating these risks.
2. Test, test, and test
Regardless of the type of DR solution, thorough testing is a must. Organisations must perform cloud recovery testing that simulates a real recovery in the event of a disaster or breach. This is to avoid any unwanted surprises and to identify what is needed to recover data from the cloud. Build this into the business culture so that in the long run, any issue can be uncovered immediately or even pre-empted, making the recoverability of information more certain.
3. A ‘restore to any’ solution
We all have our favourites when we need a trouble-shooter or service provider – preferring one over another. But in reality, it is not always rosy when organisations are trapped in vendor and technology lock-in, relying on one or two specific vendors. Leveraging a solution that supports ‘restore to any’ allows physical, remote and virtual workloads to be recovered in the cloud, on demand – regardless of vendor.
4. Address the security risks
Security is central to any DR plan. Risks stemming from the cloud are not much more different from other Internet-related risks. As such, consider implementing the same security and compliance practices and tools currently in place for the Internet on the cloud. Finally, work with your cloud provider to identify and create the required level of cloud security.
DR in the cloud is for everyone
Cloud technology is easily accessible. Essentially, any firm of any size can easily tap into backup and disaster recovery services from a cloud DR provider. Definitely, there are risks, and contingencies need to be accounted for when creating a DR plan, whether it’s in the cloud or on tape. Cloud’s agility and accessibility makes its inclusion in a robust DR plan a no-brainer. Before it’s too late, trust the cloud and make sure your DR plan is comprehensive enough to include it as an element. It just makes good business sense.
 Gartner (2015), ‘Gartner says public cloud services in mature Asia/Pacific forecast to reach $7.4 billion in 2015’
 IDC (2015), ‘The data-driven organisation: Unlocking greater value from data and minimising its associated costs and risk
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