[QC] Bizfly Cloud's Kubernetes, Cloud, DB and S3 models for Microservices

Instead of a single large application, a microservice architecture breaks it down into smaller, independent services that work together to complete specific tasks. Each service focuses on a single job, like order processing or inventory management, and communicates with each other through specific interfaces. When deploying microservices according to the traditional model, businesses often have to manage and deploy each individual service on multiple servers. Each time updating a new version requires many manual operations such as running scripts, restarting services or reconfiguring the system, making the deployment process prone to errors and difficult to rollback (back to the old version) when problems arise. Besides, the difference between the actual development, testing and operating environments can lead to a situation where the application works normally in the testing phase but generates errors when put into use. As the number of services and users increases, system expansion, load balancing, or troubleshooting also become more complicated due to the lack of centralized coordination and automatic recovery mechanisms. In addition, monitoring distributed systems and responding to traffic spikes often requires a lot of operational resources, increasing costs and risk of service disruption.

In microservices architecture, the database is a potential bottleneck. Continuous queries from multiple services, especially with real-time data, location or transaction history, can cause the system to respond slowly if not designed to scale properly. In the traditional model, the database often has to handle both reading and writing on the same system, easily creating a "bottleneck" when traffic increases. In the traditional model, data such as photos, videos, documents, logs or historical data are often saved directly on the application server. As data grows rapidly, businesses must continuously expand storage capacity, increasing infrastructure costs but not improving system performance. At the same time, backing up and synchronizing data between multiple servers becomes complicated and poses a potential risk of data loss. The problem in the Transport - Logistics & Delivery industry is that the technology system must continuously process large amounts of real-time data such as orders, delivery status, driver's GPS location and shipping history. Bizfly Cloud deploys the K8s Database Object Storage S3 model on the Cloud. At the application operations layer, K8s manages all microservices such as order management, driver dispatching, location tracking and notification systems that are packaged and operated in a unified way. When combined with CI/CD, Kubernetes becomes more than just a deployment tool and becomes a platform that standardizes the entire system operation lifecycle. An important point is that the system is organized on the principle that all configurations and changes are managed centrally and synchronously. This eliminates the situation where each environment (dev, test, production) runs differently - which is a common cause of errors when bringing the system to production in real logistics systems. Besides, the entire deployment process is standardized from testing to actual operation. Instead of having to do each release manually or in multiple steps, the system ensures the same process is applied consistently in all environments.

More importantly, Kubernetes supports a mechanism to securely update the system. When upgrading or deploying a new version, the system is not changed entirely at once but is updated in small parts. If something goes wrong, the system can quickly roll back to the previous stable version without the need for complicated manual intervention. This helps significantly reduce downtime - an extremely important factor in logistics, where any disruption directly affects orders and customer experience. At the database layer, Bizfly Cloud Database plays a central role in processing real-time data such as order status, driver location and shipping history. The system can flexibly scale according to the number of queries, separate read and write streams to reduce load, and ensure automatic backup and recovery. Thanks to that, problems such as slow queries when customers track orders, database congestion during peak hours or overload when processing GPS data are significantly reduced, ensuring data is always accurate and available. In addition, Bizfly Cloud Simple Storage acts as a specialized storage layer for all unstructured data such as delivery confirmation photos, customer signatures, videos, system logs and driver journey data. In the old model, this data was often saved directly on the server, leading to the hard drive quickly filling up, making it difficult to expand, difficult to synchronize, and reducing system performance when traffic increased. When moving to S3, all data is separated from the main processing system, making the application lighter, more stable, and easier to scale during peak periods. To receive free consultation and POC solution model, readers please visit: https://bizflycloud.vn/