Businesses increasingly rely on cloud computing solutions to streamline operations and drive innovation. Naturally, this technology comes with risk—service disruption can mean lost revenue, diminished customer trust, and reputational damage. Being thoughtful and intentional about the data centers you use as a business can help mitigate these risks.
While it’s essential to choose the right data center location for your business operations, there are various scenarios where using multiple data centers can help you more effectively grow and scale your business while making your business more resilient against risk.
This article will discuss reasons for deploying across multiple data centers rather than relying on a single data center.
Many laws and regulations govern how data is collected, shared, and stored. An essential aspect of some of these regulations is that they often prohibit storing certain data outside national boundaries. For instance, consider an application accessed by customers living in Cleveland, Ohio, and Toronto, Canada. In this situation, it might be necessary to host the application in two data center locations—Canada and The United States, even if the Toronto data center is closer to both locations. Using data centers in different geographies may be an important part of a company’s overall regulatory compliance strategy.
Despite the best efforts of cloud service providers, data center failures can occur. Recovering quickly is essential to ensure customer retention and avoid data loss. Data loss can occur for various reasons, including hardware failures, outages, natural disasters, and failure of environmental controls resulting in fire. Businesses must protect themselves, and their customers, from these situations.
While it’s important for businesses to back-up data, restoring data from backups can be time-consuming and inadequate in some situations. To help mitigate the consequences of a data center failure, you can deploy your application across several data centers. The application hosted in one data center can serve the incoming traffic, and the application hosted in another data center (somewhere relatively close to the primary data center) can serve as a backup node. If the first data center goes offline for any reason, you can reroute the incoming traffic to the application deployed in the second data center, thereby preventing or minimizing data loss.
Deploying across multiple data centers can improve your application’s overall performance by optimizing various parts of the workload, especially when you have a global customer base.
If your application generates and serves up unstructured data (static assets) like media and text files, you can use object storage to store the data and CDN to serve and distribute the data. The combination of object storage and CDN can speed up unstructured data distribution and improve content availability, especially for applications with a global reach. For instance, if you anticipate high user activity (i.e., users uploading/downloading unstructured data) in a secondary region, you can spin up an object storage instance in a data center closer to that region.
Spinning up an object storage instance allows you to speed up the data movement between the CDN endpoint and object storage location and potentially prevent performance bottlenecks. When users upload static assets to the CDN endpoint, the CDN endpoint can quickly write the data to the object storage. Similarly, the static assets stored in the object storage can be promptly synced to the CDN location, reducing the wait time and speeding up the download process.
By scaling your object storage across multiple data centers, you can improve the overall performance of your application and provide exceptional customer experiences.
Suppose you have a centralized application (e.g., a gaming application) with distributed edge nodes that writes to a central master database. In this scenario, you can speed up the read operations by scaling read-only database instances horizontally across multiple data centers, reducing the read latency significantly and making the overall application faster.
The write latency would still be the same, as your application would be writing the data into the central database. In other words, if your application performs more reads than write operations, you can scale up read operations by deploying your distributed edge nodes across multiple data centers, thereby speeding up your application.
On the other hand, if your application requirements dictate that the write latency is as low as possible (e.g., fintech applications), you can deploy your entire application (the main application along with database instances) across multiple data centers such that the application can serve customers regionally while keeping the write latency low. This way, you can optimize the read/write operations at a database level by hosting your database instances across multiple data centers.
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