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Raft Algorithm: Simple and Reliable Consensus in Distributed SystemsDistributed systems are the foundation of modern software architecture. But the simultaneous operation of multiple servers presents complex challenges, such as ensuring data consistency and system fault tolerance. At the heart of these challenges lies the problem of 'consensus': the ability of a group of servers to agree on a single value or action despite disruptions such as network outages or server failures.

The CAP theorem stands as one of the most influential principles in distributed systems design, articulating fundamental constraints that engineers must navigate when building resilient, scalable applications. First conjectured by Eric Brewer in 2000 and later proven mathematically by Seth Gilbert and Nancy Lynch in 2002, the theorem establishes that distributed data systems can provide at most two of the following three guarantees simultaneously; Consistency, Availability, and Partition tolerance.

Distributed systems are systems where multiple independent processes or nodes cooperate for a common purpose. They are widely used in many areas from microservice architectures to cloud infrastructures in the modern technology world.

Distributed systems are one of the most critical technological building blocks of our day. In databases, blockchain networks, multi-layered enterprise software architectures, cloud computing infrastructures and many other areas, we use systems based on the principle of different physical or virtual nodes working together. However, many problems such as communication failures, hardware failures, malicious attacks or software errors can occur in these systems. These problems directly affect the overall operation and reliability of the distributed system.

In distributed systems, reaching consensus among multiple nodes is a difficult problem. The PAXOS algorithm is a well-accepted protocol in the academic world that was developed to provide reliable consensus in distributed systems. Introduced by Leslie Lamport in the 1990s, this algorithm is especially used in systems where fault tolerance is critical.

Go (Golang) is a modern programming language designed by Google in 2007 and published as open source in 2009, focusing on developing high-performance and scalable software. Thanks to its simple and understandable syntax, it can be easily learned by both experienced and novice developers. At the same time, since it is a lightweight and fast-compiling language, C-like performance can be achieved.

Distributed systems have become increasingly popular today. Microservices architectures, replications between data centers, geographically distributed databases, applications with multiple access points, and similar scenarios make ensuring data consistency quite complex. Conflicts can arise when data is simultaneously located, updated, or read from multiple locations. This is where the concept of CRDT (Conflict-free Replicated Data Types) comes into play.

In the world of computers, while some technologies are forgotten over time, others take root and form the basis for many other innovations. The UNIX operating system falls into this category. Developed by Dennis M. Ritchie and Ken Thompson in the early 1970s, UNIX is a revolutionary software that forms the basis of many modern operating systems today.

In the field of networking and information technologies, a common framework is needed so that different systems can work in harmony with each other. In this context, the OSI (Open Systems Interconnection) Model is a basic conceptual model used to understand how various networks and communication protocols work and how they interact with each other.

MoSCoW is a methodology used to determine priorities in software projects and other project management processes. This method helps clarify which elements take priority by classifying the project's requirements and features.