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Microservices Modernization of a Legacy Real-Time Payment Gateway Application

Description

This project is about modernizing an old payment application. The existing payment system runs as one large application on a physical server. The project will break this large application into smaller independent microservices, package each service into a Docker container, and run the microservices on Kubernetes. This makes the payment system easier to manage, scale, monitor, and recover when one service has a problem.

Aim

To change the old monolithic payment application into a modern microservices-based application running on Cloud using Docker and Cloud EKS. The system will process payment requests through separate services and allow each service to be scaled and managed independently.

Objectives

01 Assess the existing payment application and identify its dependencies and performance problems.
02 Create the required Cloud infrastructure using Infrastructure as Code.
03 Break the large payment application into smaller microservices.
04 Package each microservice using Docker.
05 Deploy and manage the microservices using Kubernetes.
06 Use an event and message system to process payment activities asynchronously.
07 Secure communication between APIs and services.
08 Monitor the application and identify performance problems.

Application Workflow

01

Payment Request Initiation

Process

Customers or merchant applications initiate a payment request by providing the required transaction and payment details.

Tools
Nginx API Gateway PostgreSQL
Implementation

The payment request enters through Nginx and is forwarded to the API Gateway. The gateway routes the request to the appropriate payment microservice, while transaction details are stored in PostgreSQL.

02

Authentication and Payment Validation

Process

The payment request is authenticated and validated before processing.

Tools
API Gateway Authentication Service PostgreSQL
Implementation

The Authentication Service verifies the customer or merchant credentials. The Payment Service validates transaction details, account information, and payment limits using data stored in PostgreSQL.

03

Real-Time Payment Processing

Process

The validated payment is processed through the appropriate banking or payment network.

Tools
Payment Service REST APIs Message Broker
Implementation

The Payment Service sends the transaction to the external bank or payment provider through REST APIs. A Message Broker can be used to exchange transaction events between payment microservices without tightly coupling the services.

04

Transaction Confirmation

Process

The payment result is received and the transaction status is updated.

Tools
Transaction Service PostgreSQL REST APIs
Implementation

The Transaction Service receives the payment response, updates the transaction status in PostgreSQL, and returns the payment result to the customer application.

05

Notification and Monitoring

Process

Customers and merchants receive the payment status, while the system monitors transaction and service health.

Tools
REST APIs Prometheus Grafana
Implementation

The Notification Service sends payment confirmation or failure notifications through the required communication channel. Prometheus collects microservice and infrastructure metrics, while Grafana displays service health, transaction performance, and resource usage.

Current Infrastructure

Existing on-premises infrastructure and technologies used before migration.

Existing On-Premises Environment

Payment Application Monolithic Application

All payment functions such as card validation, fraud checking, payment processing, and notifications run inside one large application.

Database PostgreSQL 14

Stores customer details, merchant information, user accounts, and payment transaction records.

Operating System Ubuntu Server 24.04 LTS

The application and database run directly on a physical Linux server.

Process Management Systemd

Starts and manages the payment application and database services.

Storage Linux ext4 File System

Stores application files, PostgreSQL data, and transaction logs on the local server disk.

Security and Access Linux PAM

Manages administrator and server user access.

System Logging Journald

Collects application and system logs for troubleshooting.

Network and Firewall TCP/IP + UFW

Handles network connections and controls which traffic can reach the payment application.

Deployment Location On-Premises Linux Server

The complete payment application and database run on one physical server, with limited scaling and failover capability.

Target Infrastructure

Cloud-hosted infrastructure and technologies used after migration and modernization.

Cloud-Hosted Modernized Environment

Database Engine PostgreSQL 14

Stores customer, merchant, account, and payment transaction data. The database is hosted in the Cloud environment.

Cloud Platform Cloud Web Services (Cloud)

Provides the Cloud environment for running the modernized payment gateway application.

Cloud Networking Cloud VPC

Provides a private and secure network for the application, database, and Kubernetes infrastructure.

Cloud Compute Cloud EC2

Provides virtual servers that host the Kubernetes worker nodes and application workloads.

Operating System Ubuntu Server 24.04 LTS

Runs on the EC2 instances hosting the containerized application environment.

Containerization Docker

Packages the payment application components into independent containers.

Container Orchestration Kubernetes

Deploys, manages, and scales the payment microservices across multiple containers and servers.

API Gateway Kong

Acts as the external API gateway, routing and securing incoming payment requests.

Event and Message Processing Apache Kafka

Handles real-time payment events and asynchronous communication between microservices.

Service Communication Istio

Manages secure communication, traffic control, and service-to-service connectivity between microservices.

Security and Access Linux PAM + Kubernetes RBAC

PAM manages Linux server access, while Kubernetes RBAC controls access to cluster resources.

System Logging Journald

Collects operating-system and service logs from the Linux servers.

Infrastructure as Code OpenTofu

Creates and manages Cloud resources such as VPC, EC2, networking, and security infrastructure using code.

Configuration Automation Ansible

Configures EC2 servers and installs required system and Kubernetes dependencies.

Application Observability OpenTelemetry

Collects application telemetry and distributed tracing information from the payment microservices.

Distributed Tracing Jaeger

Tracks requests across multiple payment microservices and helps identify latency and service failures.

Infrastructure Monitoring Prometheus

Collects infrastructure and application performance metrics such as CPU, memory, network, and service metrics.

Monitoring Dashboard Grafana

Displays Prometheus metrics and monitoring information through dashboards.

Storage Cloud EBS

Provides persistent block storage for EC2 instances and required application and database data.

Implementation Process

01
Assess the Existing Payment Application
  • Analyze the existing monolithic Python application and identify payment functions such as authentication, payment processing, fraud checking, and notifications.
  • Review the PostgreSQL 14 database, application dependencies, configuration, and existing system services.
  • Identify the components that will be separated into independent microservices.
  • Document current server resources, network configuration, and application dependencies.
02
Build the Cloud and Kubernetes Environment
  • Use OpenTofu to create the Cloud VPC, EC2 instances, networking, and security infrastructure.
  • Use Ansible to configure Ubuntu Server 24.04 LTS and install the required dependencies.
  • Install Docker and Kubernetes on the EC2 infrastructure.
  • Configure the Kubernetes cluster to run multiple application workloads.
  • Configure Kubernetes RBAC and Linux PAM for controlled access.
03
Modernize the Application into Microservices
  • Separate the monolithic application into services such as Authentication Service, Payment Service, Transaction Service, Fraud Detection Service, and Notification Service.
  • Package each service using Docker containers.
  • Deploy the containers using Kubernetes.
  • Configure Kong as the API Gateway for incoming payment requests.
  • Configure Istio for secure communication between microservices.
  • Configure Apache Kafka for real-time events and asynchronous communication.
04
Migrate the Database and Configure Observability
  • Migrate the existing PostgreSQL 14 data to the Cloud environment.
  • Configure the microservices to access the required payment and transaction data.
  • Configure OpenTelemetry to collect application telemetry.
  • Use Jaeger to trace requests across the payment microservices.
  • Configure Prometheus to collect infrastructure and application metrics.
  • Configure Grafana dashboards to monitor system performance and service health.
05
Test and Deploy the Modernized Payment Gateway
  • Test authentication, payment processing, fraud checking, transaction processing, and notifications.
  • Test communication between microservices using Istio and Apache Kafka.
  • Verify API routing through Kong.
  • Test Kubernetes service recovery and scaling.
  • Verify PostgreSQL 14 transaction data after migration.
  • Monitor the environment using Prometheus, Grafana, OpenTelemetry, and Jaeger.
  • After successful validation, redirect production payment traffic to the modernized Cloud environment.

Proposed Solution

The proposed solution modernizes the old payment application by breaking it into smaller microservices. Docker is used to package the services, and Kubernetes is used to run and manage them. Apache Kafka handles communication between services, while Kong and Istio provide API and service security. OpenTelemetry and Jaeger are used to trace payment requests, while Prometheus and Grafana monitor application and infrastructure performance. This makes the payment system more scalable, secure, reliable, and easier to maintain.

Benefits

Better Security : Kong protects external APIs, while Istio secures communication between internal services.
Independent Scaling : If the payment service receives more traffic, only that service can be scaled.
Better Reliability : Kubernetes can automatically restart failed containers.
Faster Processing : Kafka allows services to process events independently instead of everything waiting in one application.
Easy Troubleshooting : OpenTelemetry and Jaeger help identify where a payment request is slowing down.
Better Monitoring : Prometheus and Grafana show system health and performance.
Less Manual Work : OpenTofu and Ansible automate infrastructure and configuration.

Challenges

Data Consistency : Keeping payment data correct when it is handled by multiple microservices.
Service Communication : Managing communication between many containers and services.
Kafka Management : Ensuring payment events are processed correctly without losing messages.
Monitoring Data : Managing the large amount of logs, metrics, and traces generated by the microservices.
Migration Testing : Testing all payment functions carefully before moving production traffic to the new system.
System Complexity : Kubernetes, Istio, Kafka, Kong, and multiple microservices make the new environment more complex to manage.
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