Distributed computing

 Distributed computing

Distributed computing is a field of computer science that studies distributed systems, defined as computer systems whose inter-communicating components are located on different networked computers.

The components of a distributed system communicate and coordinate their actions by passing messages to one another in order to achieve a common goal. Three challenges of distributed systems are: maintaining concurrency of components, overcoming the lack of a global clock, and managing the independent failure of components. When a component of one system fails, the entire system does not fail. Examples of distributed systems vary from SOA-based systems to microservices to massively multiplayer online games to peer-to-peer applications. Distributed systems cost more than monolithic architectures, primarily due to increased needs for additional hardware, servers, gateways, firewalls, new subnets, proxies, and so on. Distributed systems can also suffer from fallacies of distributed computing. Conversely, a well-designed distributed system is more scalable, more durable, more changeable, and more fine-tuned than a monolithic application deployed on a single machine. According to Marc Brooker: "a system is scalable in the range where marginal cost of additional workload is nearly constant." Serverless technologies fit this definition but the total cost of ownership, and not just the infra cost must be considered.

A computer program that runs within a distributed system is called a distributed program, and distributed programming is the process of writing such programs. There are many types of implementations for the message-passing mechanism, including pure HTTP, RPC-like connectors, and message queues.

Distributed computing also refers to the use of distributed systems to solve computational problems. In distributed computing, a problem is divided into many tasks, each of which is solved by one or more computers, which communicate with each other via message passing.

What are the advantages of distributed computing?

Distributed systems bring many advantages over single system computing. The following are some of them.

Scalability

Distributed systems can grow with your workload and requirements. You can add new nodes, that is, more computing devices, to the distributed computing network when they are needed.

Availability

Your distributed computing system will not crash if one of the computers goes down. The design shows fault tolerance because it can continue to operate even if individual computers fail.

Consistency

Computers in a distributed system share information and duplicate data between them, but the system automatically manages data consistency across all the different computers. Thus, you get the benefit of fault tolerance without compromising data consistency.

Transparency

Distributed computing systems provide logical separation between the user and the physical devices. You can interact with the system as if it is a single computer without worrying about the setup and configuration of individual machines. You can have different hardware, middleware, software, and operating systems that work together to make your system function smoothly.

Efficiency

Distributed systems offer faster performance with optimum resource use of the underlying hardware. As a result, you can manage any workload without worrying about system failure due to volume spikes or underuse of expensive hardware.