Booking.com's high-level system architecture

Greetings, everyone! Taking a closer look at Booking.com, one of the world's largest travel and hospitality platforms, we will examine its possible high-level architecture.

Serving millions of users worldwide, Booking. com has a dynamic system architecture to meet ever-changing customer expectations and integrate technological innovations. They are starting with Booking. com’s system requirements, the purpose of this paper is to discuss how the platform was designed, and how its main components function.

Like other leading companies in the industry, Booking. com needs complex and scalable architectures to continuously improve user experience, increase efficiency, and maintain a competitive advantage in the market. This paper will try to understand the technological processes behind such a platform and propose a basic high-level architecture. 

Whether you are a software developer, a systems engineer, or just a tech-savvy person, we hope that this article will give you a better understanding of Booking. com’s technological structure. This immense traffic indicates the need for a high-capacity, resilient server infrastructure capable of efficiently handling large volumes of data and user interactions, especially during peak usage periods.

To manage this effectively, the system architecture must be robust and scalable, ensuring that it can handle the concurrent requests and data processing needs of this large and active user base. The possible high-level architecture diagram you see above is a visual summary of Booking. com’s service architecture.

A critical decision in the high-level architecture of Booking. com is the selection of an architectural pattern that can effectively accommodate the platform's varied and dynamic load across different services.

Given the diversity in service loads, such as the higher frequency of users browsing for hotels compared to the number of users making reservations, it is clear that a one-size-fits-all approach to scaling does not suit Booking.com's needs. In the architecture of Booking.com, the selection of a relational database is strategic, driven by the platform’s operational pattern where the volume of hotel searches substantially exceeds the number of actual reservations made. 

The efficiency of relational databases in read operations aligns seamlessly with the high number of searches that the platform accommodates. The use of MySQL is discussed in many articles on Booking. com’s technical blogs.

The platform utilizes content delivery network (CDN) technology to provide users with fast access to hotel images. This centralized structure effectively manages traffic on the system and provides a secure user experience by controlling access based on users’ authorizations. Booking. com believes that review systems are critical to the user experience and quality of service, which is why it places a great deal of importance on the platform’s review systems.

Besides these main microservices, Booking. com’s architecture may also include additional services that analyze user behavior and feed a constantly evolving machine-learning pipeline using booking data. Elastic Search: ElasticSearch is known for its ability to index and query large data sets quickly and efficiently, enabling the Search Service to quickly filter and present a wide and diverse range of accommodation options to users.

We delve into the sophisticated architecture that enables Booking. com to manage its complex network of services efficiently. It is responsible for the high-level management of traffic routing, policy enforcement, and service discovery. Booking. com uses an ADN (Application Delivery Network) based on HAProxy to efficiently manage user requests.

HAProxy acts as a high-performance load balancer and proxy server, automatically routing user requests to the most appropriate server. HAProxy dynamically manages the traffic flow on the network and thus processes user requests taking into account various factors such as geographical location, server health, and load.

Requests made by users are routed by HAProxy to the most appropriate data center. In conclusion, we have examined Booking. com’s high-level architecture and its core microservices, its global application delivery network, and how its components work together.

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