Every cloud application, from a CRM dashboard to a large language model, is supported by some physical infrastructure in one way or another. However, this is exactly the aspect that cloud computing typically tries to hide: behind the user interface, there’s always some sort of a data center, or sometimes multiple ones, supporting compute, storage, and networking for that application. Choosing the right type of data center and understanding its relation to cloud computing is what will distinguish a scalable cloud strategy from an unpredictable and hard-to-budget one. With that said, here’s the guide, written by the experts at Wizard Infoways, covering the types, technology, and choosing the right model of data center for cloud computing.
What Is a Data Center in Cloud Computing?
A data center in cloud computing refers to the physical facility, servers, storage arrays, and networking equipment a cloud provider uses to deliver cloud computing services to customers. When you launch a VM or call some API, you’re actually allocating some capacity in one of those facilities. What distinguishes it from any other kind of data center is a software layer above that allows multiple customers to use the same physical infrastructure without interfering with each other’s compute workloads.
Types of Data Centers in Cloud Computing
There are different kinds of data centers in cloud computing that you might want to explore:
- Hyperscale data centers. Huge facilities managed by the major cloud providers, optimized for scalability and standardization.
- Colocation data centers. Shared facilities where a provider provides power, cooling, and physical security, while customers bring or rent their own compute infrastructure.
- Enterprise (on-premises) data centers. Owned and managed by a customer, still quite popular for applications with special compliance, latency, or data residency requirements.
- Edge data centers. Small facilities located close to end-users or devices in order to reduce latency for real-time applications.
- Managed or hosted data centers. Infrastructure operated by the provider on behalf of the customer, a sort of hybrid approach between fully-outsourced cloud and fully-owned infrastructure.
Cloud-Based Data Center vs. Traditional Data Center
A cloud-based data center refers to the infrastructure based on virtualization, which is elastic and charged based on usage. On the other hand, a traditional data center is the capacity that the company owns and controls. It comes down to a trade-off between the ownership of physical infrastructure. Cloud-based infrastructure takes care of physical infrastructure management and allows scaling fast, but can be more expensive than owned infrastructure in case of high, steady utilization. Traditional data centers offer full control and predictable cost but require investment and knowledge to operate.
Public Cloud Data Centers
Public cloud data centers refer to the facilities behind AWS, Azure, and Google Cloud that provide shared infrastructure to multiple customers in the form of a pay-as-you-go service. It’s the quickest way to start using cloud infrastructure without any physical infrastructure in place. It works perfectly well for variable workloads, for new product development, for those who want to avoid investment into capital expenditure. However, cloud-based infrastructure doesn’t give any control over the exact location of your data and might be problematic for organizations with strict compliance or data residency requirements.
Hybrid Cloud Data Center
Hybrid cloud data center is a combination of private infrastructure, whether it’s on-premises or colocated, and public cloud infrastructure. This is the model that most midsize and enterprise organizations eventually come to since it allows keeping sensitive or latency-sensitive workloads on controlled infrastructure while everything else is scaling on the cloud infrastructure. Making such hybrid model work properly depends largely on the proper network architecture between those environments and proper policies regarding workload placement.
Data Center Technology in Cloud Computing
Today data center technology in cloud computing has moved far beyond simple server racks. Such technologies as virtualization and containerization allow running multiple workloads on shared hardware effectively. Software-defined networking and software-defined storage allow configuring infrastructure via coding rather than manually rewiring. Automation and orchestration platforms help with provisioning and scaling of the cloud infrastructure with minimal human intervention. And finally, AI-driven capacity planning and cooling optimization are being used in the process of managing the power consumption and thermal load in case of increasing rack density, especially when more and more data centers are optimized for running AI workloads.
Choosing the Right Model for Your Business
The optimal choice largely depends on your specific workload rather than on general best practices. Steady, predictable workloads with strict compliance requirements make sense on either owned or colocated infrastructure, while variable or growing fast workloads would rather go to public cloud. Most of the organizations, however, end up somewhere in between, and the mistake that we’ve seen in the work of Wizard Infoways with midsize and enterprise companies the most is in not having a clear workload-by-workload reason for each system to run on particular infrastructure. That’s the gap that data center and cloud computing strategy supposed to fill.
How Wizard Infoways Can Help
Wizard Infoways helps companies develop and implement data center and cloud computing strategies that fit their workloads rather than general templates. That includes analyzing existing infrastructure, defining the right blend of public cloud, hybrid or on-premises capacity, and helping with migration and vendor selection. If you’re trying to figure out the best approach to data center and cloud computing, feel free to contact Wizard Infoways.
