When the network and internet were not that popular, we used big data centers to manage processes. Now that we have all the necessary resources, the client-server model is multiplying in popularity, and distributed computing has now become a reality.
No question that distributed systems are the future of back-end architecture. They’re scalable, reliable, and available, making them the perfect solution for applications that need to handle high loads.
Instead of going in-depth into the details, this article will introduce you to the modern computing solutions we all know as distributed systems in a nutshell. By the end of this post we explore its importance for developers and available career opportunities in designing distributed systems for backend. So let’s get started,
What is a distributed system for the backend?
A distributed system is simply a collection of interconnected machines that work together to provide a solution or service. In which components located on networked computers communicate and coordinate by passing messages. A distributed system for a back-end typically involves multiple servers that work together to provide the necessary functionality for an application.
There are many benefits to using a distributed system for your back-end:
They are scalable
A distributed system can easily scale to handle high loads or traffic volumes by adding more servers and nodes to the network, without sacrificing performance or reliability.
By distributing the workload across multiple servers, a distributed system can continue to function even if one or more servers fail.
Improve application performance
A distributed system can enhance performance by distributing the workload across multiple servers, reducing the load on any one server.
Offer great flexibility
A distributed system can be designed to accommodate different types of workloads, and be easily reconfigured as requirements change.
Heterogeneous distributed computing
A distributed system may contain many different kinds of hardware and software that work together cooperatively to solve problems.
Viewed as cheaper
After a certain threshold, distributed systems can be significantly more efficient than vertical scaling of centralized systems.
Shared but secured
Security in distributed systems, where more than one machine must incorporate middleware, remains a challenge. However, a defined security architecture can be used to ensure that the design of applications and systems meets the required security objectives.
The Need for Distributed Systems on the Backend
Backend operations are critical for any business, and they can be made even more efficient by using a distributed system. By using a distributed system, backend operations can be scaled up to handle multiple tasks simultaneously, without worrying about the consequences or affecting the performance of other parts of the business. This allows backend operations to run much more quickly, which is crucial for businesses that rely on high-traffic websites or applications.
This approach can help to reduce security risks and improve overall reliability. A distributed system enables you to take advantage of redundancy and fail-over mechanisms in case one machine goes down. Due to its asynchronous nature, it also avoids bottlenecks and achieves higher levels of automation without sacrificing performance or quality assurance (QA).
Furthermore, because data is stored on multiple machines rather than centrally, there’s less chance that data will become corrupted or lost in case of an incident.
Why should every developer know about distributed systems?
Distributed systems can be complicated for beginners, and it takes time to fully grasp the concepts. But developers should understand concurrency in computing systems. No one wants a programmer who can’t think about concurrency all over their code or an algorithm.
An entry-level programmer may not have to be an expert in distributed systems to contribute to modern software, but senior developers of the development team will typically deal with distributed systems issues.
Modern applications are heavily dependent upon networked services, both in the front end and back end, most applications that are built today:
- run in the cloud
- interact with mobile users
- Designed as multi-platform applications or microservices
- Data is stored in non-SQL databases or other scale-out persistence services, or it is reliant on third-party network services.
For any of these to work well, distributed systems programming techniques will be needed. As long as networks remain unreliable and have high latencies (an eternity), distributed systems programming techniques will be relevant.
Why are distributed systems considered complex?
The reason distributed systems are inherently complex is simple: it takes time!
There is a lot a developer should know before understanding the intricate concepts of distributed systems. It may include a deep understanding of network communication, fault tolerance, data storage, computing, load balancing, design patterns, monitoring, debugging, and security to build reliable and efficient distributed systems.
Developers list the following as potential reasons for its complexity;
- Asynchronous communication
- Partial failures
How to design a distributed system, and what a career in distributed systems looks like
When developing a distributed system for a backend, the system architecture, including communication protocols, data storage, and fault tolerance mechanisms, must be carefully designed.
It’s also crucial to thoroughly test the system to ensure it can handle the expected workload and recover from failures.
You can use this 8-point guide to design a robust and reliable distributed system for the backend:
- Define the system requirements
Before you start designing the system, you need to define the system requirements, such as the number of users, data size, peak traffic, response time, and availability. These requirements will guide your design decisions.
- Choose the right architecture
There are various distributed system architectures, such as client-server, peer-to-peer, and microservices. Choose an architecture that fits your system requirements.
- Select the right technology stack
Choose the right technology stack that supports the chosen architecture and the required features. Consider the programming language, database, messaging system, and other tools.
- Partition data and services
Partition your data and services across multiple nodes to ensure scalability and availability. Use techniques like sharing, replication, and load balancing to distribute the load evenly across the nodes.
- Implement fault tolerance
Ensure that the system can handle failures gracefully by implementing fault tolerance mechanisms like redundancy, replication, and automatic failover.
- Ensure data consistency
Implement consistency mechanisms like distributed transactions, two-phase commits, or optimistic concurrency control to ensure data consistency across multiple nodes.
- Secure the system
Ensure that the system is secure by implementing authentication, authorization, encryption, and other security mechanisms.
- Test and monitor the system
Test the system thoroughly to ensure that it meets the requirements and is robust and reliable. Use monitoring tools to monitor the system’s performance and detect issues early.
Lastly, it’s important to remember that not all users will be familiar with deploying and using a distributed system; therefore, it’s essential to include clear instructions on how everything works, along with examples from real-world cases where this technology was successfully used.
By following these guidelines, you’ll be able to build an efficient back end with maximum scalability for your business!
There are several popular technologies for building distributed systems for back-ends, including:
- Apache Kafka is a distributed streaming platform that can manage large volumes of data and provide real-time processing.
- Apache Spark is a distributed computing system that enables parallel processing on large datasets.
- Kubernetes is an open-source container orchestration system that can manage and deploy containerized applications across a cluster of servers.
- RabbitMQ is an open-source message broker that can handle large volumes of messages between different components in a distributed system.
- Apache Cassandra is a distributed NoSQL database that can handle large volumes of data across multiple servers.
Career Prospects in Distributed Systems Engineering
As the world becomes increasingly connected, so does the need for engineers who can design, develop, and automate distributed systems. There is also a significant demand for individuals with multiple programming language competencies to build these systems.
Due to the increased demand for engineers who can design efficient and secure distributed networks, career opportunities in distributed systems engineering are expanding rapidly, and a bright future lies ahead.
Long story short,
Hopefully, with the tips given in this blog post, you will be able to understand how distributed stacks work, evaluate different types of architectures, and design the best possible system.
If you want to learn more about distributed system architecture and the career prospects in distributed systems engineering?
This series of blogs will continue, so stay tuned until then and keep learning.
Or if you are preparing for a tech interview, you can check out our technical interview checklist, the most frequently asked back-end developer interview questions, and salary negotiation tips to get interview-ready.