Why Your Business Should Separate Cloud Compute and Cloud Storage

In 2024, almost every business already understands the power of data-driven services and operations. From improving customer experiences to streamlining business intelligence, a data-first approach is revolutionary when it comes to honing a company’s offering to the world. With that in mind, organizations around the world are constantly looking for new ways to drive their management and mastery of data even further.

A popular strategy that has gained steam over the past few years is separating cloud compute and cloud storage. The world is no stranger to cloud technologies, with the cloud computing market crossing $500 billion in total value in 2023. The vast majority of companies have seen the added scalability, improved flexibility, and boosted data management capacities that cloud offers and have already made the switch.

However, a combined approach to cloud computing and cloud storage can radically narrow down the flexibility that a business has when utilizing cloud tech. In this article, we’ll turn to these two spheres of cloud deployments, examining why an increasing number of data teams and technicians are pushing to separate compute and storage.

Let’s dive right in.

Optimize Cost Throughout the Course of a Project

An important consideration that many data teams use as a primary factor to motivate higher-ups to allow them to make the change to a split cloud strategy is that separating these components can help to more effectively manage the cost of using cloud resources. When compute and storage and connected, businesses may find it difficult to determine exactly where they’re using the most resources.

Especially as nearly all cloud providers work on a subscription basis via tiered pans, a company could be paying for a high resource allocation of storage or compute while not actually using it all. 

To avoid unnecessary exposure, businesses can instead split compute and storage. By treating these two components in isolation, data teams can fine-tune their usage to determine the precise volume of resources that are needed at any one given time for each service. Instead of treating them as one pool of resources, you can craft a highly detailed plan of which resources you use and when.

This approach gives any data project a higher degree of scalability as you can begin to reduce any overhead costs by more precisely approaching each component. 

Avoid Performance Issues

A typical issue that companies run inot when they havave a connected storage and compute approach to cloud is that the performance of one may dramatically impact the other. For example, if your data team is performing a heavy load of queries and processing lots of information, the compute function may be consuming a great deal of your allotted resources.

When connected, if one service consumes the pool of resource, the other is left with fewer to run its normal function on. With this considered, a business could severly impact the function of either storate or compute when dealing with a higher than normal workload on another. 

Especially for businesses that typically deal with spikes in their workload in either component, splitting storage and compute can be a powerful remedy to this issue and provide a more consistent performance experience across all deployments. As a company begins to scale, underlying problems like these will only become more dramatic, making this an issue to tackle as early on as possible if an organization wants to avoid performance issues in their products.

Provide Flexibility to Your DevOps Tech Stack

Another strong reason to separate cloud compute and cloud storage is that it allows a business to build more effective technological foundations. When working with combined compute and storage, you must compromise on the technologies that you use as they must be compatible with this approach. On the contrary, a cloud data warehouse that can split these functions has a much higher degree of flexibility, providing your business with complete technological freedom when constructing data architecture. 

When comparing Snowflake vs BigQuery, two leading cloud data warehouses, both present the ability to effectively separate storage and compute. However, the extent to which they isolate compute and data varies, meaning that a company has to carefully plan for the future before committing to a service. 

Yet, once an organization has successfully divided compute and storage, they are then able to begin adopting technologies that directly benefit each one of these spheres. Your business can add platforms or software that is specifically built to facilitate better storage or compute, not needing to settle for a less flexible technology that does both to a lesser extent.

Constructing an effective tech stack becomes a more natural process when you don’t have limitations imposed upon your teams due to a singular cloud entity.

Streamline Governance

Cloud computing and cloud storage must equally follow regulatory standards and ensure that compliance with security measures is upheld across every aspect of their operations. Yet, despite both existing in the realm of the cloud, these two functions don’t have exactly the same regulations to follow. On the contrary, there are unique concerns that apply to each area. Especially in industries that deal with private or sensitive data, the clear-cut compliance initiatives are even more drastic.

Separating cloud compute and cloud storage allows a business to more effectively follow compliance for each of these components. As DevOps practices aim to prioritize security across the entire development cycle, a more precise approach aligns with this methodology and helps businesses manage sensitive data with more care.

By tackling the necessary security measures for each of these segments in isolation, your business can create a precise strategy to manage all of the potential governance issues you could run into. Instead of compromising, you can fulfill all requirements in a purposeful manner.

Final Thoughts

Separating cloud storage and cloud compute is a highly effective strategy that will allow all of your teams to get more from your cloud environments. Although there will be an initial cost involved when scaling these two services independently of one another, this strategy more than makes up for this commitment by providing flexibility, scalability, and optimized consumption of compute and storage resources.

Businesses that treat cloud compute and cloud storage separately are able to more precisely build the technological and infrastructural base to support all deployments their teams may require. Especially as data becomes even more important in the world of business development and strategy, this tendency to divide compute and storage will only become even more pronounced.