Cohesity Converged Data Protection

The Cohesity Converged Data Protection presentation at Storage Field Day 8, delivered by Mark Thomas, focuses on the company’s advanced data protection architecture geared towards simplifying enterprise IT infrastructures. Thomas aims to explain the underlying technology of Cohesity’s solutions, particularly highlighting SnapTree—a data structure that supports efficient data management and protection workflows. The primary purpose of Cohesity’s architecture is to consolidate various operational data workloads onto a unified platform, which significantly streamlines data backup and recovery processes.

The conventional enterprise backup infrastructure, according to Thomas, is often burdened by a complex architecture that includes master servers, media servers, and multiple backup targets, which grow increasingly complicated as the enterprise scales its IT landscape. This complexity results in various inefficiencies such as multiple data silos, ineffective deduplication, and increased operational overhead. Cohesity’s solution replaces these intricate setups by offering a scalable platform that directly integrates with existing virtualized environments and applications, eliminating the need for separate media and master servers. Cohesity also features a distributed file system with SnapTree technology that allows for rapid and frequent data cloning without performance degradation.

The discussion also touched on how Cohesity supports additional workflows such as DevOps and instant VM recovery. Through its ability to create writable and modifiable clones instantly, use of integrated backup software, and a user-friendly interface, Cohesity provides robust solutions for both data protection and development environments. By indexing all backed-up data and enabling API integrations, Cohesity ensures ease of data management and swift recovery operations, making it a versatile tool for contemporary enterprise IT landscapes. The simplified architecture not only reduces the number of moving parts but also consolidates data management tasks onto a single platform, thus fostering a more efficient and less error-prone system.