๐๐ฟ๐ผ๐บ ๐ฎ๐ฟ๐ฐ๐ต๐ถ๐๐ฒ๐ฐ๐๐๐ฟ๐ฒ ๐๐ผ ๐ฑ๐ฒ๐ฝ๐น๐ผ๐๐บ๐ฒ๐ป๐: ๐ฅ๐๐ป๐ป๐ถ๐ป๐ด ๐ผ๐๐ฟ ๐๐๐๐๐ฒ๐บ ๐ผ๐ป ๐๐๐ฏ๐ฒ๐ฟ๐ป๐ฒ๐๐ฒ๐
After designing the microservice architecture for our project ๐ฉ๐ฎ๐น๐ฒ๐ฟ๐ถ๐ , next step was taking it beyond local development and deploying it in cloud.
Read previous post on the Microservice Architecture of Valerix: Link
To do this, we containerized each service and deployed the system on Amazon Web Services (AWS) using ๐๐๐ฏ๐ฒ๐ฟ๐ป๐ฒ๐๐ฒ๐ (๐๐๐ฆ), allowing us to simulate a small production style environment for our distributed system.
GitHub Link: https://github.com/rawadhossain/Valerix
The deployed system followed this flow:
๐๐น๐ถ๐ฒ๐ป๐ โ ๐๐ป๐ด๐ฟ๐ฒ๐๐ (๐ก๐๐๐ก๐ซ) โ ๐๐ฟ๐ผ๐ป๐๐ฒ๐ป๐ฑ โ ๐๐ฃ๐ ๐๐ฎ๐๐ฒ๐๐ฎ๐ โ ๐๐ฎ๐ฐ๐ธ๐ฒ๐ป๐ฑ ๐ฆ๐ฒ๐ฟ๐๐ถ๐ฐ๐ฒ๐
Container Orchestrated View
Each component ran as independent containers orchestrated inside a ๐๐๐ฏ๐ฒ๐ฟ๐ป๐ฒ๐๐ฒ๐ ๐ฐ๐น๐๐๐๐ฒ๐ฟ on ๐๐ช๐ฆ ๐๐๐ฆ.
To deploy the system, we used:
ย โข ๐๐ผ๐ฐ๐ธ๐ฒ๐ฟ to containerize each service
ย โข ๐๐ช๐ฆ ๐๐๐ฅ to store and manage container images
ย โข ๐๐ช๐ฆ ๐๐๐ฆ to run the Kubernetes cluster
ย โข ๐ฒ๐ธ๐๐ฐ๐๐น to provision and configure the cluster
ย โข ๐ธ๐๐ฏ๐ฒ๐ฐ๐๐น to manage deployments, services, and cluster resources
ย โข ๐๐ช๐ฆ ๐๐๐ ๐ฟ๐ผ๐น๐ฒ๐ to securely allow cluster and registry access
Each microservice was deployed using ๐๐๐ฏ๐ฒ๐ฟ๐ป๐ฒ๐๐ฒ๐ ๐๐ฒ๐ฝ๐น๐ผ๐๐บ๐ฒ๐ป๐๐ ๐ฎ๐ป๐ฑ ๐ฆ๐ฒ๐ฟ๐๐ถ๐ฐ๐ฒ๐, allowing the system to scale and operate as independent components inside the cluster.
Core services included:
ย โข frontend-service
ย โข api-gateway
ย โข order-service
ย โข inventory-service
Traffic from users was routed through ๐ก๐๐๐ก๐ซ ๐๐ป๐ด๐ฟ๐ฒ๐๐ ๐๐ผ๐ป๐๐ฟ๐ผ๐น๐น๐ฒ๐ฟ, which directed requests to the appropriate services within the cluster.
The backend services were connected to their supporting infrastructure:
ย โข ๐ฅ๐ฎ๐ฏ๐ฏ๐ถ๐๐ ๐ค for asynchronous communication between services
ย โข ๐ฃ๐ผ๐๐๐ด๐ฟ๐ฒ๐ฆ๐ค๐ ๐ฑ๐ฎ๐๐ฎ๐ฏ๐ฎ๐๐ฒ๐ for Order and Inventory data
ย โข ๐ฃ๐ฟ๐ผ๐บ๐ฒ๐๐ต๐ฒ๐๐ & ๐๐ฟ๐ฎ๐ณ๐ฎ๐ป๐ฎ for monitoring and observability
All infrastructure components were defined using Kubernetes manifests, making the system easy to deploy, manage, and reproduce inside the cluster.
Moving from ๐๐ผ๐ฐ๐ธ๐ฒ๐ฟ ๐๐ผ๐บ๐ฝ๐ผ๐๐ฒ ๐น๐ผ๐ฐ๐ฎ๐น๐น๐ to a fully ๐ผ๐ฟ๐ฐ๐ต๐ฒ๐๐๐ฟ๐ฎ๐๐ฒ๐ฑ ๐๐๐ฏ๐ฒ๐ฟ๐ป๐ฒ๐๐ฒ๐ ๐ฒ๐ป๐๐ถ๐ฟ๐ผ๐ป๐บ๐ฒ๐ป๐ on ๐๐ช๐ฆ was a great experience. Seeing the system run end to end on AWS with services communicating, routing, and running inside the cluster was one of the most rewarding parts of the project.
