System Design Interview Basics: Distributed System Fundamentals
First thing first to build large-scale applications
Prologue
System design interviews are a technical interview method used to evaluate a candidate’s ability to design and scale complex systems. During these interviews, candidates are asked to design and discuss the architecture of a hypothetical system while considering factors such as scalability, performance, reliability, and fault tolerance. One type of system architecture that candidates may be asked to design is a distributed system.
Distributed systems involve multiple independent components that communicate and coordinate with each other to perform a common task. These types of systems are often used in large-scale applications where high availability and scalability are crucial. To effectively design and implement distributed systems that can handle high levels of traffic and provide reliable and consistent performance, it’s important to have a solid understanding of fundamental concepts such as distributed computing, concurrency, consistency, fault tolerance, and replication.
Let’s Get The Details
Today’s digital age, distributed systems have become an essential aspect of software engineering. These systems are designed to distribute data and processes across multiple nodes within a network, allowing for greater scalability and fault tolerance. However, building and maintaining distributed systems can be a challenging task that requires a solid understanding of the underlying principles and architectures.
In this article, we will dive into the basics of distributed systems and explore some of the fundamental concepts that form the foundation of these systems. We’ll look at topics like data durability and consistency, replication, partitioning, consensus, and distributed transactions.
Data Durability and Consistency
One of the main challenges of distributed systems is ensuring data durability and consistency. In a distributed system, data can be stored on multiple nodes, which means that it’s crucial to have mechanisms in place that ensure the integrity of the data. Durability refers to the ability of a system to recover data after a failure, while consistency refers to the accuracy and correctness of data across different nodes.
For example, let’s say you’re building a social media application that allows users to create and share posts. If one node goes down, you don’t want to lose all the data that was stored on that node. Therefore, you need a mechanism to ensure that the data is replicated across multiple nodes to ensure durability. Additionally, if two users create a post at the same time, you need to ensure that the data is consistent across all nodes.
Replication
Replication is the process of copying data from one node to another. In a distributed system, replication is essential for ensuring data durability and consistency. When data is replicated across multiple nodes, if one node goes down, the data can be recovered from another node. Additionally, replication can help improve read throughput by allowing multiple nodes to serve read requests simultaneously.
Partitioning
Also known as sharding, is the process of dividing data across different nodes within a system. By partitioning data, you can distribute the workload across multiple nodes, which can help improve scalability and reduce the reliance on pure replication. For example, if you’re building an e-commerce application, you can partition your data based on the geographic location of your customers. This way, each node can serve requests for a specific geographic region, improving response times and reducing the load on any one node.
Consensus
Consensus is the process of ensuring that all nodes in a distributed system agree on a particular state. In a distributed system, nodes can be located in different geographic locations, and data packets can take varying amounts of time to travel between nodes. This can lead to inconsistencies and errors in the system. Consensus ensures that all nodes agree on the current state of the system, which prevents faulty processes from running and ensures consistency and replication of data and processes across the system.
Distributed Transactions
Once consensus has been achieved, distributed transactions are used to ensure that transactions from applications are committed across databases with fault checks by each resource involved. In a distributed system, two-way and three-way communication is used to read, write, and commit transactions across participant nodes. This ensures that transactions are atomic, meaning they are either fully completed or not completed at all.
Understanding the fundamentals of distributed systems is crucial for building scalable, fault-tolerant applications. By understanding concepts like data durability and consistency, replication, partitioning, consensus, and distributed transactions, you can design systems that can handle the demands of modern applications. Remember, building a distributed system is a complex task that requires careful consideration and planning, but with the right foundation, you can create systems that can stand the test of time. I give you the video above to understands more ^^.