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Is Multi-Cloud Architecture Right For Your Data?

Authors Photo Christopher Tozzi | June 20, 2020

Could a multi-cloud architecture improve your data management strategy? That’s a question more and more companies are likely to ask themselves as multi-cloud computing grows in popularity.

What is multi-cloud computing?

Multi-cloud computing refers to cloud computing architectures in which organizations leverage multiple clouds at once.

In some cases, multi-cloud architectures involve spreading the same workload across multiple clouds in order to provide resiliency and high availability. For example, you might host copies of the same database on two clouds at once so that if one cloud fails, the data is still available.

In other instances, multi-cloud architectures can entail running different workloads on different clouds. The chief motivations for doing this are cost-efficiency and features. One cloud might be the best fit for hosting one of your applications, while a different cloud can host a different application at lower cost. Rather than limiting yourself to one cloud and hosting everything on it, a multi-cloud architecture enables greater flexibility.

Multi-cloud architecture and data

Usually, when people talk about multi-cloud architectures, they tend to be thinking about the IT needs of the business as a whole, not just data management.
Yet there is a lot to think about when it comes to deciding whether a multi-cloud setup is the best fit for your data management needs specifically. While a multi-cloud strategy can offer important benefits for data management, it can also increase complexity. Determining whether to adopt a multi-cloud architecture requires deciding whether the downsides outweigh the benefits from a data-management perspective.

Questions when considering a multi-cloud architecture

Toward that end, here are some questions you should ask yourself when evaluating the potential benefits of a multi-cloud architecture’s impact on data:

1. How much data do you store in the cloud?

This is the first and most obvious question to ask. If you don’t use the cloud extensively for data storage and data management, then you probably don’t need to factor data management needs into your multi-cloud assessment at all.

2. Do you depend on platform-specific tools for cloud-based data management?

If you do take advantage of data hosting or data management tools in the cloud, are your team and processes dependent on those provided by a specific cloud? How readily can they be adapted to work on another cloud? If you’re currently using AWS, for example, but are considering moving some data workloads to Azure, will your data management team struggle to learn an entirely new cloud platform? Or are their skillsets more adaptable?

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3. What are your data availability needs?

While maximizing data availability is always a good thing, the fact is that not all data availability needs are the same. A business that can tolerate a day-long disruption to data availability will require different data management practices than one that can survive for only an hour without its data. If you have very high data availability needs, investing in a multi-cloud architecture might be worth the trouble, whereas businesses with less extreme data availability requirements might not see a big payoff from a multi-cloud architecture in this respect.

4. How effective are your data integration tools and processes?

When you spread your data workloads across multiple clouds, your data integration needs become more complex. You have to collect, transform and interpret data from more than one cloud environment. Can your existing data integration solutions handle this? Or are they specific to a particular cloud vendor, and therefore difficult to adapt to a multi-cloud architecture?

5. How will you secure multi-cloud data?

Are your data security tools and processes dependent on a specific cloud, or can they work on any type of cloud? Will you be able to encrypt data on multiple clouds at once? You want to make sure you can answer data security questions like these before you jump into the multi-cloud game.

6. How will you keep data in sync?

If you spread redundant copies of the same data across multiple clouds, how will you keep that data in sync? Are your data management tools up to this task?

7. How will multi-cloud data impact your compliance initiatives?

Depending on which industry and jurisdiction you are in, a multi-cloud strategy may create new data compliance challenges. For example, the GDPR imposes relatively strict data auditing requirements. Will your tools provide the logging and aggregation features necessary to create an adequate logging trail across multiple clouds?

While multi-cloud computing is the popular thing to do these days, it is not necessarily the best choice in all situations. Before jumping on the multi-cloud bandwagon, it’s essential to evaluate how a multi-cloud architecture could impact your data management tools and processes.

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