It is forecasted that in 2021, there will be over 7 million data centers in the world. As the digital society brings more advancement, more data is being generated as well. A year after the COVID-19 pandemic has impacted the world, around 1,327 exabytes of data will be stored in data centers. This is an 8-fold increase compared to 2015.
With the bulk of overall data that would occupy data centers around the world, the demand for keeping these facilities secure, well-connected, scalable, and efficient is higher than before. Connectivity is one of the most important components in a data center, alongside offering so much more than just storage.
Now, modern data centers serve as connectivity hubs, providing colocation customers with incredible possibilities when it comes to building their networks. Behind all of these, it is important to understand how distance and capacity matter for data center connectivity.
Where should data centers be located? How should data center capacity be planned? These are some of the questions that should be answered by providers as well as enterprises to ensure the operations of sustainable and highly competent data centers.
Connectivity: Why distance matters
A traditional data center can be built anywhere with sufficient power and connectivity. But, to make this work, location is crucial as it affects the quality of service that the facility will provide. Connectivity is then closely associated with proximity.
In terms of establishing stable connectivity, one of the effective ways to provide consistent and reliable bandwidth at an enterprise-grade data center is to build lots of connections to different network providers.
Aiming to be carrier-neutral, in a data center environment, a cross connect is a physical direct connection between two different termination locations — from a colocation rack to an ISP, telecom carrier, or cloud provider. The facilities of these providers assemble at major peering points (internet exchanges). Following this, when data centers are located in close geographic proximity to IXPs, low-latency and multiply-redundant bandwidth are delivered.
However, regardless of how much bandwidth a data center has access to, data still requires some time to travel. In reality, round-trip distances are doubled as both the request and the response have to cover the geographical distance.
Taking this into consideration, the physical location of the data center is important. However, within cities, there are not that much space left to be allocated for these facilities. In fact, the worldwide data center space has recorded almost 2 billion square feet. To resolve the lack of land availability as well as massive costs, edge data centers are now increasing. Being closer to the source of data is deemed to be more reliable and durable in the long run.
In order to cope with the ongoing digital transformation and the enormous data and bandwidth requirements it entails, more businesses across all industries are shifting servers to data centers outside of their organizations (colocation) or into the cloud.
Whether around a metro area, across countries, or even all over the world, data centers must have the connectivity to enable the performance of transporting more capacity. At any distance, flexibility, resiliency, and ability to provide performance-optimized solutions should be considered in any data center.
Storage: Why capacity matters
To be able to handle data, the storage capacity must be enough to avoid encountering bottlenecks and potentially slowing down the onboarding and processing of new applications. There’s no argument that the need for data storage expansion is upon us as the future becomes more digitally advanced and automation progresses.
Roughly producing about 2.5 quintillion bytes of data daily, we’re not in danger of running out of data storage space just yet. But to keep the storage streamlined, capacity planning must be done. Too much capacity can cause unnecessary capital expenditures and might lead to idle and unused servers. Yet, without enough computing, network, and storage capacity, applications can also encounter bottlenecks and potentially stop working or take too long to be processed.
Revolutionizing data storage is needed to ensure reliability and cost-effectiveness. Solid-state drives (SSDs) aka flash storage, have made tremendous advancements in delivering better speed and capacity. The new era of SSD is faster at retrieving data with no physical moving parts to slow it down.
Narrowing the gap between on-site and cloud workloads, utilizing flash storage aims to narrow the gap between storage performance of cloud-based compute instances. Thus, cloud service providers offer premium tiers for storage-intensive applications such as databases.
Cloud storage services also provide elasticity, which means that you can scale capacity as your data volumes increase or cut down capacity if necessary. By storing data in a cloud, you will be paying for storage technology and capacity as a service, rather than investing in the capital costs of building and maintaining in-house storage networks.
Capacity is important for storage as it determines how much data a data center or memory can handle. With almost everything opting to be on the edge, having the right amount of capacity to manage both unstructured and structured data is vital for speed and responsiveness.
In detail, there are three main types of cloud storage: block, file, and object. In this storage model, data is organized into blocks or large volumes. Cloud storage providers use blocks to split large amounts of data among multiple storage nodes and separate hard drives. On the other hand, file storage is commonly used for development platforms, home directories, and repositories for video, audio, and other files.
Moreover, objects store data in the format it arrives in and makes it possible to customize the data for easier access and analysis. Instead of being organized in files or folders, objects are kept in repositories that enable unlimited scalability virtually.
Virtualization is key
Cloud storage servers are software-defined servers. This approach is what enables cloud storage providers to offer pay-as-you-go cloud storage and charge only for the storage capacity being consumed. In this way, connectivity is kept at bay as long as virtualization takes place.
By virtualizing servers and abstracting away the underlying hardware, you are preparing yourself to jump into the cloud. As the public cloud matures and the technology around it advances, the thought of moving data out of traditional data centers and into a cloud hosting facility would become the trend.
When you bring virtual resources into the data center, it can have an extensive effect on the network infrastructure. Most of the impact will be on the physical aspect and the enterprise capacity to accommodate the new virtual machines (VMs). VMs make better use of shared data center resources and give complete control of server functions through a software overlay.
More importantly, virtualization and cloud resources combined meet the changing demands for scaling up networks. Particularly in a post-pandemic era where connectivity to the cloud becomes more essential, the goal of business continuity must be achieved 24/7. By virtualizing data centers, distance and capacity needs are addressed. Having said that, storage virtualization and availability would lead to less interference, security risks, and reduced infrastructure costs.