If you have heard about distributed systems, you must also know about mainframe computers. Yes, mainframe computers dominated the era before the advent of distributed computing. Therefore, the historical nodes of the distributed system are tied with mainframe computers, among which the IBM mainframe was the most significant one.
Till the 1990s, mainframe computers were the most prominent means to process vast amounts of data. They were primarily responsible for the routine data processing tasks, and a central processing unit controlled all the other peripheral devices. The IBM mainframe took over the market share mainly because of its value. Before people could define the distributed system, this mechanism processed transactions at a massive scale.
The mainframe computers efficiently supported a large scale of concurrent users as well as application programs. Moreover, the IBM mainframe computers managed vast distributed databases seamlessly. It got popular because of its safety, reliability, optimum services, availability, and easy compatibility. However, the need for the distributed system arrived when some disadvantages of mainframe systems became hurdles. Let’s get into the details of why the need for distributed systems came into the picture.
The Need For Distributed System
As described above, mainframes provided multiple advantages. However, due to a few disadvantages, distributed computing had to save the avenue.
- Mainframe computers were expensive, which is why many medium-small enterprises could not afford them.
- They worked with specialized hardware and software due to which organizations working with these computers had to bear additional costs of investing in high infrastructure data centers.
- In addition to this, mainframe computers demanded professional skills for their maintenance and troubleshooting.
With the advent of PCs and laptops, people started switching to computers, and the number of businesses investing in computers increased rampantly. As a result, the number of concurrent online users also increased, and people started realizing the need to support these computing systems. As a reform, a fresh and improved distributed computing system paradigm arrived.
What is Distributed System?
A distributed computing system works by dividing user requirements into smaller parts. Then, the computing system allocates these tasks to multiple machines present in the network. A well-designed distributed system works as a single system and is not fragmented on disparate computers. Computer systems address their smaller parts present in the overall computing needs. The coordination between various computers in distributed computing is critical for network success.
Examples of distributed system
Google Web Server is an excellent example of a distributed system. Users see Google search result requests under a single search engine system.
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But interestingly, being a distributed computing system, it consists of several servers in the background. Google gives the data processing duty to a server in a suitable region.
This eliminates the chances of users viewing any notable latency. Along with Google Web Server, ATM networks and World Wide Web (WWW) are some other examples of distributed computing systems.
Advantages of Distributed Computer Systems
Compared to their centralized counterparts, distributed systems deliver multiple over-the-edge benefits.
Affordable hardware utilization- Computer components’ usage increases with the workload increases. Obviously, this delivers an improved price over-performance ratio.
Improved performance- Distributed systems utilize multiple nodes to offer better cumulative computing strength and storage volume.
Higher scalability- Distributed computing has the capability to scale horizontally. Thus, a person using it can rampantly improve the processing power and storage volume.
Task allocation- A decently built distributed computing system can easily and seamlessly distribute the tasks.
Incorporates redundancy- The distributed system works on multiple component computers. This feature makes the system handle redundancy and fault tolerance efficiently. Thus, such systems are better protected against potential hardware or software collapses.
How to build a Distributed Computer Solution?
Though it may look simple, developers must follow a few essential steps while developing a well-designed and efficient distributed computing system. Below given are the crucial steps to follow while building a distributed system.
1. Work With Diligence
Firstly, you have to address if you actually have the need to build a distributed computer system. For this, you have to take the help of a project manager, an IT architect, or a business analyst. This is the diligence and scrutiny that distributed computing demands. You should know that even after being so beneficial, distributed computing cannot solve all types of business problems, there are a few disadvantages attached to this system, and you must consider these disadvantages to maintain diligence in your distributed computing exercises.
The disadvantages of distributed computing are-
- Though it may benefit you with long-term cost-effectiveness, distributed computing still consumes significant design and development costs.
- There are several complexities attached to building a distributed computer system. The systems take a lot of effort, from conceptualizing to designing, building, and maintaining.
- Businesses have to deal with sensitive information while building a distributed system. It is challenging to secure proper handling of sensitive data
2. Have a bolstered development approach
If an organization initiates building a distributed system, it embarks on a new horizon. This change signals a drastic shift in the overall IT management of an organization. Planning such a system for an organization requires preparation through detailed feedback and inputs by the senior management. These inputs help mitigate potential project delivery risks after throughout the project journey. Preparation with the senior management has to be done in the following phases-
- Project requirements analysis
3. Collect and scrutinize the project demands
The project manager, IT architect, or the business analysts you get onboard with have to collect the business needs through all the business stakeholders. Ultimately, all of them will analyze and scrutinize the reviews from the stakeholders and create requirements documentation accordingly.
There might be several analyses for the requirements documentation. However, it is vital to set the requirements formally since as ambiguous requirements may threaten the entire software development work of the distributed computing system.
4. Assemble your project team
Now that you have conceptualized the idea and project requirements in a documented form, next up is hiring picking team members for your project. Since building a distributed computing system will be complex and demands field experts, it is recommended to have someone in-house than preferring someone working remotely. These are the following roles that you’ll need in your project-
- A cloud architect;
- An information security architect;
- A data modeler;
- A database administrator (DBA);
- UI designers;
- Web developers
- DevOps engineers.
5. Select the appropriate cloud infrastructure
Knowing that the process of building a distributed computer system is challenging, you will gradually start to help yourself as much as possible. Finding the most appropriate cloud services provider is one way to ease your daily efforts. This will enable you to become available for other important tasks apart from your core job. One of the most recommended cloud service providers is Amazon Web Services (AWS). It provides a robust infrastructure-as-a-service (IaaS) called Amazon Elastic Compute Cloud (EC2) along with impressive cloud capabilities. Key advantages of this cloud service include-
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- People can easily sign up, and console management makes the experience user-friendly.
- The pricing plans are flexible and easy to understand.
- It has global recognition and a powerful infrastructure that minimizes latency and provides high availability.
- You can efficiently scale up and choose from the broad range of services available.
6. Data modeling and selecting the suitable database
Next up is the step involving data modeling and selecting the most suitable database solutions for your planned distributed computer system. The data modeling phase includes the following options-
- Conceptual data models
- Logical data models (LDMs)
- Physical data models (PDMs)
As per your business needs, you will be able to select the right database for your distributed computing project.
7. Secure your distributed system application
Every now and then, we hear news about data breaches, identity theft, and the loss of sensitive data. Several businesses have to pay heavy penalties because of data breaches, and the clients have to contend with the fallouts of such incidences. Thus, it is vital to mitigate the primary application security risks. The risks involved are as follows:
- Ineffective authentication
- Loss of sensitive data
- XML external entities (XXE)
- Incorrect implementation of identity and access management
- Inadequate security configuration
- Cross-site scripting (XSS)
- Using outdated software with known vulnerabilities
8. Building APIs and Using them
Application programming interfaces (APIs) can be easily built and used during the development of distributed computing systems. The key advantages of using APIs are-
- Providing information and services becomes more manageable with APIs.
- APIs facilitate automation, integration, and improved efficiency.
There are two trendy ways to design APIs and use them: REST (Representational State Transfer) and GraphQL (Graph Query Language). Though you can consider either of the two options, understanding the differences will help you choose the right for your distributed system.
REST is an improved version of previous API protocols, such as SOAP, RPC, CORBA, etc. Unfortunately, these previous protocols were pretty rigid. Thus, developers could not implement the demanded flexibility in how clients and servers transmit.
The RESTful architecture employs HTTP and standard CRUD verbs, such as GET, PUT, POST, etc. Thus, it enables greater flexibility and can become the measure for designing and consuming APIs.
However, as far as RESTful architecture is concerned, everything is associated with the API endpoints. If a platform requires only a single field from an API endpoint, it still requires retrieving the entire endpoint. If the application demands more data than what you have in the endpoint, then multiple APIs have to be employed. As the consumption of APIs has increased, this inefficiency has significantly impacted.
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With REST APIs, you must streamline the API endpoints for the designs. Therefore, if you choose to modify the front-end, you will have to change the backend as well.
GraphQL can overcome these limitations as it operates with a query language. Developers can select the exact fields they want while utilizing GraphQL. Therefore, the issues of inefficiency do not arise. In addition, the flexibility of GraphQL also eliminates the close coupling between the front-end and backend.
Both REST and GraphQL are efficient with their unique features. So, as per your distributed computing requirements, you can choose the right one.
9. Organize the caching of your distributed system architecture
Organizing the caching well is vital for the efficient implementation of a distributed computer system. Ensure that your IT architect formulates an excellent caching strategy; for example, your application could take advantage of the browser cache of users.
10. Don’t avoid web development, testing, and proper deployment.
It is recommended that you use Node.js to develop the web app in your active distributed computer system. It is a prevalent open-source runtime software and is an excellent option for coding scalable and performant web apps.
Start planning your distributed system.
Devising a distributed computer system can be complex. You should build a system that is easy to maintain and has robust security maintenance. Hiring field experts or collaborating with reputed software development companies is the best way to build your own distributed computing system.
FAQs (Frequently asked questions)
Q.1 How can you make a distributed system more open?
Issue precise guidelines on components, standardize interfaces, and ensure that you can easily integrate all new interfaces.
Q.2 What makes distributed computing so hard?
Since computer hardware is not standardized, software should be able to bear this problem.
Q.3 What is an example of a distributed system?
A distributed system enables resource sharing that includes software by systems connected to the network. There are several examples of distributed systems/applications of distributed computing, such as Intranets, Internet, WWW, and email, along with Telecommunication networks, including both Telephone networks and Cellular networks.
Q.4 What are the types of distributed systems?
There are three types of distributed systems: Distributed Computing systems, Distributed Information systems and Distributed transaction processing.