CFS provides storage services suitable for organizations with a large number of employees who need to access and share the same datasets. It allows the administrators of an organization to create file systems and set read/write permissions for internal clients.
CFS provides the scale, performance, high throughput of computing nodes, read-after-write consistency, and low-latency file operations required by high-performance computing and big data applications, making it particularly suitable for such scenarios as machine learning, AI training, and centralized server log processing and analysis.
For media workflows such as video editing, video production, broadcast processing, sound design, and rendering, shared storage is generally used to work with large files. The strong data consistency model of CFS, coupled with high throughput and shared file access, helps reduce the time it takes to complete such tasks.
As a highly persistent, high-throughput file system, CFS can be used for various content management systems. It stores and provides data for various applications such as websites, online distribution, and archiving.
CFS provides the foundation for the migration of traditional service architectures to the cloud for government, education, and healthcare sectors. Generally, a dedicated software program needs to share the same file storage system and only supports POSIX standard protocol operations.