In general, distributed files systems are IT solutions that allow multiple users to access and share data in what appears to be a single seamless storage pool. The back-end enabling systems can follow one of a few architectural patterns, in popular order they are client-server, which tends to be the most common, cluster-based architectures are most useful in large data centers, and decentralized files systems also exist.
These architectures comprise multiple back-end systems connected together via a network, with middleware orchestrating file storage, and employing many techniques to ensure the “distributed” system’s performance meets the needs of users. In this way, the distributed system has a capacity of service, and the load on that service is the total demand by all the active users. When load approaches or exceeds that capacity, system performance will degrade, and will show signs of lag, or service outages.
The chief benefit rests on the fact that sharing data is fundamental to distributed systems, and therefore forms the basis for many distributed applications. Specifically, distributed files systems are proven ways to securely and reliably accommodate the data sharing between multiple processes over long periods. This makes them ideal as a foundational layer for distributed systems and applications.
Distributed systems form the modern concept of “the cloud” and support the idea that the cloud is essentially limitless in storage capacity. These systems can expand behind the scenes and match any growth in demand. They can manage massive volumes of information, safeguard its integrity, and ensure its availability to users 99.9995% of the time. And in that small sliver of downtime, there are contingencies upon contingencies in place. For cloud data centers, this is their business, and so are able to benefit from economies of scale more readily than enterprises or smaller businesses that deploy their own distributed systems.
Enterprises and small businesses may deploy their own distributed file systems to facilitate business operations, regionally, even globally. For instance, distributed systems may support private clouds, parallel computing, even real-time control systems. Municipalities deploy real-time traffic control and monitoring systems to better manage commuter times, all made possible by DFS supported applications. Sophisticated parallel computing models are deployed across many participating computing systems in collaborations that help compute large data sets, as in astronomical calculations where one computer simply won’t do the work.