How Shiji Group created a global guest profile store on AWS

Shiji Group provides global software solutions for the hospitality industry. The Shiji Enterprise Platform enables customers to manage large hotel property portfolios using software as a service (SaaS). Among functionalities such as reservations, housekeeping, finance, and integrations with external systems, the guest profile is a key aspect of the system. Besides personal information (such as name and address) and billing details, the guest profile can include room preferences and entertainment options.

A property portfolio can span multiple hotels across the globe, and each hotel location can offer better customer service by consolidating data. Once the guest gives their cross-border data processing consent (CBDPC), profile information can be shared between properties. This provides a centralized and seamless experience for the hotel guest no matter which hotel in the portfolio was chosen.

In the following blog post, you will explore the architecture of the guest profile store that replicates the profile across multiple geographic areas. We will review the single Region design first and its infrastructure components and architectural patterns. We will then show the evolution to a multi-Region architecture.

Single Region architecture with CQRS

The ability to find relevant guest profile data fast is essential in the day-to-day hospitality business. Therefore, the following architecture uses the command query responsibility segregation (CQRS) pattern to provide high scalability and rich full-text search capabilities without sacrificing performance. With CQRS, write requests (commands) are targeting a different service than read requests (queries). This allows systems to store an item (such as a profile) in a search-optimized format for serving reads, while providing a simple schema for writes.

The microservices for the guest profile architecture are operated as containers on Amazon Elastic Kubernetes Service (Amazon EKS). The write model of the guest profile is stored in an Amazon Relational Database Service (Amazon RDS) PostgreSQL database. A separate read model uses Amazon OpenSearch Service. For interservice communication, Shiji runs a self-managed Apache Kafka cluster on Amazon Elastic Compute Cloud (Amazon EC2).

The following diagram provides a walk through the single Region architecture:

1. The front desk employee creates the Guest Profile upon first interaction with the hotel guest (name, address, billing, and room preferences).
2. The request is routed to the Kong API Management Solution that is running in an Amazon EKS Kubernetes cluster. It acts as the single entry-point to the system. It identifies the type of request by parsing the URL and forwarding write requests to the profile-write-model-service.
3. The service validates the request. It stores the data and ProfileCreated event in the PostgreSQL database, Amazon RDS.
4. A change data capture (CDC) mechanism publishes the ProfileCreated event to an Apache Kafka Local Profiles topic.
5. The profile-read-model-service subscribes to the Local Profiles topic and stores the profile in an optimized read format in Amazon OpenSearch. Whenever the hotel performs a guest profile search, results will now be provided via the profile-read-model-service.

Multi-Region networking setup

Shiji operates in multiple

Regions to provide low latency, regulatory requirements, and resilience across the globe. The previously presented single Region architecture can be replicated to multiple AWS Regions (eu-central-1 and ap-southeast-1, for example). Hotels with a given property portfolio that operate in the same Region can reuse the profile store of the Shiji Enterprise Platform. However, hotels that are being operated in a different AWS Region can be interconnected as well.

This is achieved by providing an AWS Transit Gateway in a separate networking account that connects the different Regions with a VPC attachment:

The account segregation provides an additional layer of flexibility to add further Regions in the future.

Multi-Region event replication

Upon first arrival, guests can choose to sign a cross-border-data processing consent (CBDPC). This permits the hotel to share the profile information globally. If accepted, the profile-write-model-service creates an additional ProfileCreated event that gets published to a GlobalProfilesEU Apache Kafka topic. This topic is accessible for subscribers in the target Region, which replicates relevant profiles into the local database as follows.

A replicator-service in the target Region (ap-souteast-1) is now able to subscribe to the GlobalProfileEU topic in (eu-central-1), via the established network connection from the previous section. It republishes the event to a local ReplicatedProfiles topic that the profile-write-model-service subscribes to and saves to the local database:

Putting it all together: The multi-Region guest profile store

The following diagram combines all the components from the previous sections. It provides an end-to-end look at the multi-Region guest profile architecture. Due to the event driven nature of the system, the architecture can be extended without changing the initial flow outlined in the single Region design.

1. If the hotel guest signed a cross-border data processing consent (CBDPC), the ProfileCreated event will also be published to a Global Profiles topic.
2. The replicator-service in the target Region (for example, ap-southeast-1) subscribes to the Global Profiles topic of the source Region (for example, eu-central-1). It then publishes the event to its local Replicated Profiles topic.
3. The profile-write-model-service in the target Region subscribes to the Replicated Profiles topic and records the item in the Amazon RDS PostgreSQL database with information about the source Region. This will initiate the local replication similar to the single Region design, and therefore creates a consistent experience between both Regions.

Conclusion and outlook

In this blog post, we showed how Shiji built a modern multi-Region microservice architecture on AWS. You have learned about patterns such as CQRS, which provide a scalable solution for both read and write traffic. We’ve also shown what is needed to interconnect two physically separated Regions. With cross-border data processing consent (CBDPC), you have seen how the ownership of guest data can be secured and utilized. The single Region architecture already provided a solid baseline for this solution architecture. The event-driven nature of the system permitted us to add additional functionality for the final multi-Region architecture.

The ability to manage a global guest profile within the main system as well as at the property itself is a huge advantage for enterprise hotel companies. It permits hotels to deliver a unified experience to their guests no matter where the guest is within the hotel or on their journey. Food preferences, spa, room, and more, can all be managed from a single guest profile. This centralized information hasn’t been possible within the hotel’s property management system (PMS) until recently.

Visit Shiji Enterprise Platform for more information.

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