Four Hybrid Cloud Data Management Challenges

For all the advantages of hybrid cloud, there is a big drawback: data management becomes extremely complicated.

Christopher Tozzi, Technology Analyst

March 24, 2021

4 Min Read
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Hybrid cloud offers a variety of benefits. But it presents one key drawback: data management. When you move to a hybrid cloud architecture, it becomes challenging to make sure your data doesn’t get in the way of cost, performance, and security goals.

Here’s a look at the hybrid cloud data management challenges to address in order to avoid letting your data become the Achilles’ heel of your hybrid infrastructure.

Hybrid Cloud and Data

The reason data management complicates hybrid cloud is simple. As your infrastructure grows more distributed, it becomes harder to move data across it in an efficient and cost-effective way.

In other words, when you store all of your data in a single public cloud, or all in a private data center, your data doesn’t have to move very far. You might need to transfer it from one server to another, but that movement takes place on local networks, which are comparatively fast and cheap.

Not so when you build a hybrid cloud environment that consists in part of public cloud infrastructure and in part of servers running in a private data center.

Four Key Challenges in Hybrid Cloud Data Management

The distributed nature of hybrid cloud architectures complicates data management in four key ways.


Perhaps the most obvious is performance. Because data within a hybrid environment typically moves between data centers over the internet, the speed of data transfers is likely to be much lower, while latency will be higher.

Related:The Pros and Cons of Kubernetes-Based Hybrid Cloud

There are two essential ways to mitigate this issue. One is to try to minimize the frequency with which data has to move between different locations within your hybrid cloud architecture. The other is to use cloud interconnects, if they are available within your data centers and you have the budget for them. Interconnects provide a higher-performing network connection between data centers and the public cloud.


A second disadvantage of data movement within hybrid environments is that it can increase your cloud computing costs. Public clouds usually charge egress fees whenever data leaves their data centers. The more data you move, the more you pay.

Here again, minimizing data movement is one key toward minimizing the cost of data within a hybrid architecture. Compressing data can also help by reducing the size of the data transferred (and hence the egress fees charged).

And, because public clouds don’t typically charge fees when data moves into their data centers, a hybrid strategy that focuses on one-directional data movement (the movement of data from private data centers into the public cloud) won’t bloat costs. It’s better from a cost perspective if your data originates in a private data center and moves into the public cloud for processing than the other way around.

Related:What Colocation Users Should Know About AWS’s and Its Rivals’ Hybrid Cloud Solutions


In some ways, hybrid architectures can simplify data security by providing more control over where and how data is stored than you would get from a public cloud or on-premises infrastructure alone.

On the other hand, spreading data across a hybrid environment can complicate data security by making it more difficult to track where your data lives and what the access rules to it are.

Perhaps the best way to address this risk is to use IaC templates that can be applied across both private and public cloud infrastructure. That way, you can centralize your data access policies on a single platform and use them to enforce controls that meet security and compliance goals.

You may also be able to take advantage of data security tools that scan data for access risks and compliance violations, although most of the ones available to date work only for public cloud and don’t extend into hybrid environments. (Google DLP, which can work with on-premises data as well as data in the cloud, is an exception.)

Data Redundancy

Maintaining redundant copies of data in order to increase data availability can be more difficult in a hybrid environment. You can’t simply configure multiple availability zones or cloud regions to mirror your data, as you could in the public cloud, if not all of the data exists in the public cloud.

One way to rectify this challenge is to keep all important data within a hybrid environment in the public cloud so that you can mirror it there as required. Commercial backup tools designed to support hybrid clouds may also be helpful for increasing data availability in a hybrid environment, if you can afford the cost and added management burden they bring.


Hybrid cloud architectures should maximize performance, cost-effectiveness, security, and reliability. Don’t let data management challenges undercut these advantages.

About the Author(s)

Christopher Tozzi

Technology Analyst, Fixate.IO

Christopher Tozzi is a technology analyst with subject matter expertise in cloud computing, application development, open source software, virtualization, containers and more. He also lectures at a major university in the Albany, New York, area. His book, “For Fun and Profit: A History of the Free and Open Source Software Revolution,” was published by MIT Press.

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