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This article outlines the fundamental concepts and key issues of distributed storage, provides an overview of four open‑source distributed file systems—HDFS, GlusterFS, OpenStack Swift, and Ceph—and compares their functionalities, accompanied by illustrative slide images.
This article provides an in‑depth comparison of Red Hat’s Ceph and GlusterFS open‑source storage solutions, detailing their underlying architectures—including RADOS, CephFS, RBD, and Gluster’s brick‑based design—while discussing performance, scalability, high‑availability, hardware requirements, and suitability for various cloud environments.
The article explains how to combine Distributed TensorFlow with Kubernetes—using GlusterFS storage, Deployments for parameter servers, Jobs for workers, service discovery, monitoring, and a Jinja2‑generated YAML template—to create isolated, scalable training clusters with Jupyter and TensorBoard access.
This article explains the fundamental architectures of Ceph and GlusterFS, describes their core components such as RADOS, librados, CephFS, RBD, and Gluster bricks, and compares their scalability, high‑availability, hardware requirements, decentralization, and performance characteristics for distributed storage deployments.
This article provides a comprehensive overview of GlusterFS, a scale‑out distributed file system, covering its modular architecture, elastic hash algorithm, high‑availability features, global namespace, supported protocols, cloud deployment considerations, and data flow from client to storage nodes.
The article examines various distributed storage design approaches—decentralized (GlusterFS), centralized (Hadoop), database‑based (GridFS and HBase), and metadata‑bypassing (FastDFS)—detailing their advantages, drawbacks, and practical considerations for cloud storage systems.