Unraveling the Definition: What Does a Distributed Application Entail?

Distributed application, a term prominently used in the IT industry and software development, refers to a software system where components are located on different networked computers, each of which communicates and coordinates their actions by passing messages to one another. To understand the concept better, let’s dive into its definition, how it works, the benefits, best practices, use cases, and the most recommended books on the topic.

“Distributed application is like a symphony where many contributors perform different parts cohesively, coordinated to make a beautiful overall experience.” – Satya Nadella

What is a distributed application? Definition of Distributed Application

A distributed application, or distributed system, can be defined as a collection of autonomous computing elements that are linked together via a network, cooperating to achieve a common goal or complete a specific task. The components of the distributed application are physically or geographically separated, ensuring that they work in harmony by exchanging data through a set of shared protocols and rules.

ℹ️ Synonyms: Decentralized application, scattered application, spread application, networked application, collaborative application.

How it Works

Distributed applications work by breaking down a large task into smaller subtasks, which are then distributed among different computers or systems within the network. Each computer or system is assigned with a specific part of the task and starts processing it independently. Once the subtasks are completed, the results are combined and presented as the final output.

The use of middleware, which is a software that bridges the gap between the distributed application components and the underlying network, plays a crucial role in managing communication, data sharing, and coordination among the different components in the distributed application.

Benefits of using Distributed Application

• Scalability: Distributed applications are capable of handling increased traffic and load by adding more machines or resources to the network.
• Reliability: Since the system is distributed across multiple computers or machines, the failure of one component does not typically affect the entire application, ensuring high availability and fault tolerance.
• Resource optimization: Distributed applications make the most effective use of available resources by distributing tasks and processing loads among multiple machines or systems.
• Performance enhancement: The use of multiple machines for processing and completion of tasks can improve the system’s overall performance and reduce the time taken to complete the task.
• Data replication: In a distributed application, data is often replicated among the different components, ensuring data availability and reliability.
• Geographical distribution: A distributed application can span across different geographical locations, thereby providing better accessibility to its users.

Distributed Application Use Cases

Some common use cases for distributed applications include:

1. Online gaming: Massively multiplayer online games require several servers to be interconnected to handle millions of players simultaneously.
2. Internet search engines: Search engines like Google and Bing use distributed applications to store, index, and retrieve data efficiently for users.
3. Payment systems: Digital payment systems like PayPal and Stripe have distributed applications that manage and secure millions of transactions daily.
4. Cloud computing services: Distributed applications are at the core of cloud computing platforms like Amazon Web Services, Microsoft Azure, and Google Cloud, managing the global network infrastructure for clients.

Code Examples

// Example of a simple distributed application using Node.js and Express

// Server 1: Calculator Service
// File: calculatorService.js
const express = require('express');
const app = express();
const port = 3001;

app.post('/add', (req, res) => {
  const a = Number(req.query.a);
  const b = Number(req.query.b);
  const result = a + b;
  res.send({ result });
});

app.listen(port, () => {
  console.log(`Calculator service listening at http://localhost:${port}`);
});

// Server 2: Main Application
// File: mainApp.js
const express = require('express');
const app = express();
const port = 3000;
const axios = require('axios');

app.get('/calculate', async (req, res) => {
  const a = Number(req.query.a);
  const b = Number(req.query.b);

  try {
    const calculatorResponse = await axios.post(
      `http://localhost:3001/add?a=${a}&b=${b}`
    );
    const result = calculatorResponse.data.result;
    res.send({ result });
  } catch (error) {
    console.log(error);
    res.status(500).send({ error: 'Something went wrong!' });
  }
});

app.listen(port, () => {
  console.log(`Main app listening at http://localhost:${port}`);
});

Best Practices

While using a distributed application, it’s essential to follow certain best practices to ensure the smooth functioning of the system. These include proper planning and design of the application, ensuring that the components are modular and loosely coupled, employing data replication, and focusing on security and privacy. Monitoring and logging the performance and behavior of the application, implementing fault tolerance and failover mechanisms, and designing the application to be easily scalable as per the traffic and load are also crucial elements to consider.

Most Recommended Books about Distributed Application

To delve deeper into the world of distributed applications, here are some highly recommended books:

1. Designing Data-Intensive Applications by Martin Kleppmann – This book covers principles, algorithms, and practical approaches for distributed data processing systems.
2. Enterprise Integration Patterns by Gregor Hohpe and Bobby Woolf – It explores patterns and best practices for integrating distributed applications and services.
3. Building Microservices by Sam Newman – It introduces the concept of distributed applications built using microservices and covers design principles and architectural patterns.
4. Cloud Native Patterns by Cornelia Davis – This book provides guidance on designing and building distributed applications optimized for cloud environments.

Conclusion

Distributed applications have transformed the way software systems are designed and executed, providing numerous benefits such as scalability, reliability, performance improvement, and resource optimization. By understanding the intricacies of how distributed applications work, following best practices while designing and implementing them, and constantly improving your knowledge through relevant books, you can unlock the true potential of distributed applications for your projects and business needs.

Tags: application, architecture, computing, consensus, decentralized.