"A clustered file system (CFS) is a file system which is shared by being simultaneously mounted on multiple servers."
Methods for storing and accessing data in a distributed system environment.
Distributed Systems Architecture: This refers to the physical and logical design of systems that allow multiple machines to work together to achieve a common goal, such as storing and accessing large amounts of data.
Consistency Models: A consistency model defines the guarantees made by a distributed system about how data is stored and accessed across multiple nodes. This includes discussions around eventual consistency, strong consistency, and other models.
Replication: Replication refers to the process of keeping multiple copies of data across multiple nodes to ensure availability, reliability, and data locality.
Partitioning and Sharding: These refer to techniques for dividing large amounts of data into smaller, more manageable chunks and distributing them across multiple nodes in a system.
Distributed File Systems: These systems allow for large-scale file storage, access, and sharing, with examples including Hadoop Distributed File System (HDFS), Google File System (GFS), and Amazon S3.
Distributed Databases: These systems allow for data to be stored and accessed across multiple nodes, and include technologies such as Apache Cassandra, MongoDB, and Microsoft SQL Server on Linux.
Distributed Caching: Caching involves storing frequently used data in memory to improve performance. Distributed caching allows for this data to be stored and retrieved across multiple nodes in a system.
Message Queues and Event Streaming: These technologies enable asynchronous communication between different parts of a distributed system, allowing for fault tolerance and scalability.
Consensus Algorithms: These algorithms seek to achieve agreement among different nodes in a distributed system, such as in leader election or in ensuring a replicated system has consistent data.
Load Balancing: Load balancing involves distributing requests or computational workloads across different nodes in a system to ensure optimal performance.
Distributed Transaction Processing: A distributed transaction involves multiple, interdependent steps that need to be executed across different nodes in a system. These transactions require complex coordination between nodes, and various technologies exist to handle them.
Fault Tolerance and High Availability: These concepts refer to a system's ability to tolerate node failures and continue functioning, as well as providing constant availability for users.
Security and Authorization: Security challenges in distributed systems include ensuring data privacy and confidentiality, verifying user identity, and protecting against various types of attacks, such as denial-of-service or man-in-the-middle attacks.
Monitoring and Management: Distributed systems are complex and often require advanced monitoring and management tools to ensure that they are working correctly and efficiently.
Distributed File System (DFS): Distributed File System (DFS) is a method for organizing and accessing files across multiple computers in a network, allowing for efficient and scalable file storage and retrieval.
Content Delivery Network (CDN): Content Delivery Network (CDN) is a distributed system that enables efficient and reliable delivery of web content, such as static files and media, by caching content closer to end-users and reducing latency.
Distributed Database System: Distributed Database System is a network of databases spread across multiple computers that work together to store and retrieve data in a coordinated manner.
Peer-to-Peer (P2P) Networks: Peer-to-Peer (P2P) Networks refer to decentralized systems where computers or devices communicate and share resources directly with one another rather than relying on a central server.
Cloud Storage: Cloud Storage refers to the process of storing and accessing data remotely over the internet, allowing users to store and retrieve their files from anywhere and on any device.
Distributed Hash Tables (DHTs): Distributed Hash Tables (DHTs) are decentralized systems that allow efficient storage, retrieval, and retrieval of key-value pairs across a large network of nodes.
Data Grids: Data grids are a distributed storage system that allows for the management and access of large volumes of data across multiple nodes in a network.
Distributed Cache: Distributed Cache refers to a mechanism that stores frequently accessed data in memory across multiple nodes in a distributed system to improve data access and response times.
Distributed Object-Based Storage (DOB): Distributed Object-Based Storage (DOB) is a storage approach that organizes data as objects accessible through an identifier and distributes them across multiple nodes for improved scalability and fault tolerance.
Distributed Virtual File System (DVFS): Distributed Virtual File System (DVFS) refers to a system that provides a unified and transparent view of distributed files across multiple physical machines.
"There are several approaches to clustering, most of which do not employ a clustered file system (only direct attached storage for each node)."
"Clustered file systems can provide features like location-independent addressing and redundancy which improve reliability or reduce the complexity of the other parts of the cluster."
"Parallel file systems are a type of clustered file system that spread data across multiple storage nodes, usually for redundancy or performance."
"A clustered file system is shared by being simultaneously mounted on multiple servers."
"There are several approaches to clustering, most of which do not employ a clustered file system."
"Clustered file systems can provide features like location-independent addressing and redundancy which improve reliability."
"Clustered file systems can provide features like location-independent addressing and redundancy which reduce the complexity of the other parts of the cluster."
"Parallel file systems spread data across multiple storage nodes for redundancy or performance."
"Parallel file systems spread data across multiple storage nodes for redundancy or performance."
"Clustered file systems can provide features like location-independent addressing."
"Clustered file systems can provide features like redundancy which improve reliability or reduce the complexity of the other parts of the cluster."
"Parallel file systems are a type of clustered file system that spread data across multiple storage nodes, usually for redundancy or performance."
"A clustered file system is shared by being simultaneously mounted on multiple servers."
"Most approaches to clustering do not employ a clustered file system, only direct attached storage for each node."
"A clustered file system is shared by being simultaneously mounted on multiple servers."
"Parallel file systems are a type of clustered file system."
"Parallel file systems spread data across multiple storage nodes, usually for redundancy or performance."
"Clustered file systems can provide features like redundancy which improve reliability."
"Clustered file systems can provide features like redundancy which reduce the complexity of the other parts of the cluster."