What is your Multi Cloud Business Data Strategy

As the familiarity and understanding of cloud computing across industries becomes the norm, a new yet vital development from it called multi cloud has been touted in the last few years. Major industry players like Microsoft Azure, Amazon Web Service (AWS), Google and even IBM have been offering range of products through their respective cloud services. This in turn has businesses to consider a definite multi cloud strategy.

Having a multi cloud strategy was used by many because of the uncertainty during cloud services initial introduction. Businesses leveraged on multi cloud providers as a way to minimize risks associated with going with a single cloud service provider. However, after the initial uncertainty multi cloud strategy could now offer more than just a redundancy plan to prevent data loss or downtime due to a localized component failure in cloud services.

Although having redundancy is not bad when it comes to multi cloud strategy, businesses should look beyond that scenario as using multi cloud strategy could also prevent vendor lock-in. Vendor lock-in is a scenario where businesses using a product or service cannot easily transition to a competitor’s product or service. Using multi cloud strategy would prevent this unnecessary complication.

Further multi cloud strategy could also be looked from legal, finance and technical goals perspective.  Legally some businesses are required by law or policies for data sovereignty reasons, require data storage to physically reside in certain geographical locations. Multi cloud strategy could help in this case as businesses could choose regional and zonal data centres to meet the legal or policy needs for data storage location. It would also enable businesses to locate compute resources as close as possible to end users to achieve optimal performance and minimal latency.

Having a multi cloud strategy could also affect costs hence financial aspects is one more reason for the said strategy. For example, Microsoft Azure offers $200 in services for 30 days, while Amazon offers a 12-month package for access on their AWS Free Tier. Although both don’t have standard menu as most business needs are different both do however offer online service calculators to help customers estimate costs while Google offers pay-as-you-go service for their BigQuery data services. By having a strategy in place businesses could then compare and evaluate appropriate financial commitments for the data service best suited for them.

The more tedious aspect of data storage especially from a multi cloud angle would be related to the technical aspects from the choosing a right multi cloud service. This is because technical need would determine which service providers would be able to meet the businesses system requirements. Implementation of multiple software as a service (SaaS) or platform as a service (PaaS) for multi cloud deployment will need an understanding of the technical aspects of the system itself. Some service providers might not meet certain technical requirements. In this case when comparing Azure and AWS which has GPU instance since 2015 and 2011 respectively, Google is lacking for its GPU instance. The technicalities involved in writing GPU code for data analytics is a high-value skill, given the incredible performance boosts that GPUs offer. Hence Google’s lack of a GPU instance family might not meet some businesses technical requirement although its supported by both Azure and AWS. Having a strategy again would be the best avenue to overcoming the technical aspects of multi cloud deployment.

End of the day, businesses should have a sound data strategy in place not just for the reasons mentioned above but for reasons related to the strategic planning of the business itself. By doing so businesses would achieve its organizational goals without being hampered by overlooking the strategic importance in their multi cloud data roadmap.

By |2019-04-04T07:20:32+00:00April 4th, 2019|Articles, Data Centre, Latest Articles, Networking|