A distributed system is a group of independent computers or nodes that work together to achieve a common purpose. These nodes connect by sending messages across a network, and their combined resources contribute to the system’s overall functionality. The basic goal of distributed systems is to outperform centralized systems in terms of performance, scalability, and dependability.
Distributed systems are widely employed in a wide range of applications and scenarios, including:
- Web Applications: To manage user requests, spread workloads, and assure responsiveness, large-scale web applications frequently use distributed systems.
- Cloud computing platforms are based on distributed networks and provide customers with scalable and on-demand resources.
- Big Data Processing: As seen in frameworks such as Apache Hadoop and Apache Spark, distributed systems play an important role in processing and analyzing massive volumes of data in parallel.
- material Delivery Networks (CDNs): CDNs distribute material across various servers across the world to reduce latency and increase web content delivery speed.
- Blockchain Technology: Blockchain technology, which underpins cryptocurrencies, uses a distributed ledger to record and verify transactions across a network of nodes.
As previously stated, these systems are meant to manage jobs across numerous machines, resulting in benefits such as better performance, scalability, and fault tolerance. Among the properties of distributed systems are:
- Resource Sharing: Any hardware, software, or data can be used anywhere in the system. The resource manager manages access, offers naming schemes, and manages concurrency. A resource sharing model (e.g., client/server or object-based) that describes how resources are delivered, consumed, and how providers and users interact with one another.
- Concurrency: In distributed systems, numerous tasks or processes can run at the same time. By distributing the workload across different machines, this enables parallel processing and enhances overall system performance.
- Scalability: Distributed systems are inherently scalable, which means that by adding more users or additional machines to the network, they can handle a growing amount of burden. This scalability enables effective resource utilization while also accommodating rising demand.
- Fault Tolerance: Distributed systems must sustain availability even when hardware/software/network dependability is low.
Distributed systems are built to be resilient to failures. If one component or machine fails, the system should be able to continue operating without shutting down completely. Fault tolerance is enhanced via redundancy, replication, and fault detection systems. - Transparency: Distributed systems strive to give transparency to users and applications by concealing the underlying network’s complexity. Location transparency (users are uninformed of the actual location of resources), replication transparency (users are unaware of the presence of multiple copies of data), and other forms of transparency exist. More about transparencies!
- Heterogeneity: Distributed systems are frequently made up of disparate hardware, software, and network components. They can combine a variety of technologies, platforms, OS, networks, and programming languages, allowing them to adapt to a variety of contexts.
- Security considerations such as authentication, authorization, and data encryption must be addressed in distributed systems. It is vital to ensure the confidentiality and integrity of data transported across the network, especially in systems dealing with sensitive information.
- Openness: Distributed systems are intended to be open and extensible. They should enable for easy integration of new technologies and support compatibility across different hardware and software components. Differences in data representation of interface types on different processors (from various suppliers) must be handled.