What is Distributed Computing?

With the increased investment of different industries in the IT sector, the IT field is growing rapidly. As a result, strategists and analysts of the IT sector are constantly researching cost-effective and transparent IT resources to maximize performance. Concepts such as Distributed computing plays a key role which ensures fault tolerance and enables resource accessibility. Here we collected data regarding “What is distributed computing” and put it together to offer a detailed understanding of distributed computing.

What is Distributed Computing?

Distributed computing is the method of making multiple computers work together to solve a common problem. It makes a computer network appear as a powerful single computer that provides large-scale resources to deal with complex challenges.

For example, distributed computing can encrypt large volumes of data; solve physics and chemical equations with many variables; and render high-quality, three-dimensional video animation. Distributed systems, distributed programming, and distributed algorithms are some other terms that all refer to distributed computing.

How does it work?

Distributed computing connects hardware and software resources to accomplish many things, including:

• Collaboration to achieve a single goal through optional resource sharing
• Manage access rights per user authority level;
• Enable resources, to be open for further development
• Achieve concurrency so multiple machines can work on a single process
• Ensure that all computing resources are scalable and can operate faster when working with multiple machines
• Detect errors in connected components so that the network stays fault-tolerant.

Advanced distributed systems include automated processes and APIs to help them perform better.

From the customization perspective, distributed clouds provide businesses with the ability to connect their on-premises systems to the cloud computing stack so that they can transform their entire IT infrastructure without discarding old setups. They can extend existing infrastructure through comparatively fewer modifications.

The cloud service provider controls the application upgrades, security, reliability, adherence to standards, governance, and disaster recovery mechanism for the distributed infrastructure.

Benefits of Distributed Computing

• Performance. Distributed computing can help improve performance by having each computer in a cluster handle different parts of a task simultaneously.
• Scalability. Distributed computing clusters are scalable by adding new hardware when needed.
• Resilience and redundancy. Multiple computers can provide the same services. This way, if one machine isn’t available, others can fill in for the service. Likewise, if two machines that perform the same service are in different data centers and one data center goes down, an organization can still operate.
• Cost-effectiveness. Distributed computing can use low-cost, off-the-shelf hardware.
• Efficiency. Complex requests can be broken down into smaller pieces and distributed among different systems. This way, the request is simplified and worked on as a form of parallel computing, reducing the time needed to compute requests.
• Distributed applications. Unlike traditional applications that run on a single system, distributed applications run on multiple systems simultaneously.

Distributed Computing use cases

Distributed computing use cases can include one of the following:

• Data sovereignty: A multi-national organization needs to comply with local data laws, which means that data cannot always be stored in a single, hyperscale data center.
• Application requirements: Some applications need low latency, some require high processing computing, and some do not have strict requirements and can use any scalable cloud. This diversity is difficult to be met in a single cloud or data center.
• Security: Certain industry sectors and companies have stringent security policies which inhibit their use of the public cloud. These enterprises are looking for a mix of edge computing and private cloud to meet their needs.
• SaaS applications: SaaS providers or ISVs do not always allow their customers to determine where their applications are hosted; the SaaS provider will choose a cloud platform that works best for its application.

Conclusion

Distributed computing helps improve the performance of large-scale projects by combining the power of multiple machines. It’s much more scalable and allows users to add computers according to growing workload demands. Although distributed computing has its own disadvantages, it offers unmatched scalability, better overall performance, and more reliability, which makes it a better solution for businesses dealing with high workloads and big data.