What is a Cloud Data Center?

Sridhar Panchapakesan

Dec 20, 2022 / 4 min read

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Every business requires a data center, regardless of size or industry. Traditionally, data centers were physical facilities that companies used to store integral information and applications for their business’s functions. While many individuals think of data centers as a single entity, they are composed of various technical equipment, from routers and security devices to application delivery controllers, compute servers, and storage systems. 

Cloud data centers differ significantly from traditional ones. Cloud makes everything available virtually and deployable through a code. In effect, Cloud or Virtual Data Centers can be provisioned and scaled with ease. For this reason and many more, we’ll be discussing why many organizations have invested in cloud-based data centers. In this piece, we’ll discuss what a cloud data center is and how it differs from traditional data centers.

Understanding Cloud Data Centers

A cloud data center is not located physically in an organization’s office, it’s kept on the cloud virtually. All the traditional on-premises data is located off-site. Rather than an organization managing its own infrastructure, it is leased by a third party, resulting in the cloud data center being accessed through the internet. 

Through this model, the service provider is responsible for installing, updating, maintaining, and meeting service-level agreements for the physical infrastructure under their direct control. Compute, storage, network, and other applications are made available on-demand through API and web interfaces via frameworks such as Infrastructure as a Service (IaaS), Software-defined networking (SDN), Platform as a service (PaaS), and various other frameworks.

When a new compute, storage, application, or technology is needed, cloud based frameworks will allow provisioning of these at the touch of a button or via code using APIs. The approach to provision infrastructure through APIs is known as infrastructure as code.

Comparing On-Premises and Cloud Data Centers

Cloud data centers differ from on-premises data centers in a variety of ways. Here we’ll be taking a look at each. 

  • In traditional data centers, resource scalability is limited by the amount of physical hardware available for deployment. Having your own infrastructure to maintain and administer takes significant financial and human input. In contrast, with cloud data centers, additional resources can be added as needed without the costs of purchasing equipment. You can buy more storage whenever you are ready or reduce it when development slows.
  • In on-premises data centers, flexibility is limited by appliances that may need to be acquired, provisioned, or updated. At the same time, businesses can choose exactly what software and hardware they want, allowing for changes to be made whenever the organization decides. In the cloud, organizations are limited to what the service provider offers and what works on their platform. 
  • On-premises traditional data centers have a higher cost than their cloud counterpart. Paying full price for infrastructure, including various server and networking hardware and personnel for maintenance, adds up. Replacing hardware as it gets outdated with staff makes it even more expensive. Hosting your data on a cloud data center results in more savings by eliminating various factors for maintenance, allowing for better resource optimization.
  • In the cloud, uptime availability is promised by service level agreements, which can provide better guarantees than an organization may be able to in-house. Users can access the cloud if there is a stable internet connection. In on-premises setup, natural disasters, blackouts, and other unexpected events may compromise uptime availability. 
  • In the cloud, everything is available as a code. This allows organizations to fully automate the entire lifecycle of infrastructure without ever touching any components of physical infrastructure. This essentially enables organizations to scale up and scale down resources on-demand, allowing for faster turnaround time while optimizing costs and use of resources.

As we’ve described, cloud data centers have a variety of advantages over their traditional counterparts. However, if an on-premises data center is required by a company for any reason, there is also a solution. Migrating to a cloud data center does not necessarily mean moving everything to the cloud. Many companies also utilize a hybrid approach, where a mix of traditional data center components is used with elements of a cloud data center through a shared responsibility model. Depending on the specifics of the approach, an organization can be responsible for maintaining and securing more or less of its infrastructure stack—fitting it exactly to its needs.

Synopsys, EDA, and the Cloud

Synopsys is the industry’s largest provider of electronic design automation (EDA) technology used in the design and verification of semiconductor devices, or chips. With Synopsys Cloud, we’re taking EDA to new heights, combining the availability of advanced compute and storage infrastructure with unlimited access to EDA software licenses on-demand so you can focus on what you do best – designing chips, faster. Delivering cloud-native EDA tools and pre-optimized hardware platforms, an extremely flexible business model, and a modern customer experience, Synopsys has reimagined the future of chip design on the cloud, without disrupting proven workflows.


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About The Author

Sridhar Panchapakesan is the Senior Director, Cloud Engagements at Synopsys, responsible for enabling customers to successfully adopt cloud solutions for their EDA workflows. He drives cloud-centric initiatives, marketing, and collaboration efforts with foundry partners, cloud vendors and strategic customers at Synopsys. He has 25+ years’ experience in the EDA industry and is especially skilled in managing and driving business-critical engagements at top-tier customers. He has a MBA degree from the Haas School of Business, UC Berkeley and a MSEE from the University of Houston.

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