Enterprise-grade financial ecosystem engineered with Java 17 & Spring Boot 3.

The Secure Banking Core System is a high-availability, modular monolith designed with a microservices-ready mindset. It leverages industry-standard tools for identity management, asynchronous messaging, and full-stack observability.

Core Development

Security & Identity Management

Data Persistence & Caching

Resilience & Messaging

Full-Stack Observability (LGTM Stack)

Infrastructure & Quality

Testing & Validation

• Core Backend: Java 17 (Amazon Corretto) & Spring Boot 3.4.2 utilizing Clean Architecture.
• Identity & Access (IAM): Robust security via Keycloak (OAuth2/OpenID Connect).
• Persistence & Caching: PostgreSQL 15 (ACID) and Redis for high-speed caching.
• Async Messaging: Event-driven tasks supported via RabbitMQ.
• Observability Stack: Prometheus, Grafana, Jaeger (Tracing), and Loki (Logging).
• Code Quality: Continuous inspection with SonarQube (Zero Technical Debt).
• Orchestration: Containerized with Docker Compose and Kubernetes.

The system is engineered as a Modular Monolith, striking the perfect balance between transactional integrity and future scalability.

• Strategic Modularity: Clear domain separation (Auth, Account, Transaction) ensures a smooth microservices transition.
• ACID & Consistency: We guarantee 100% atomic transaction management, paramount for financial safety.
• SOLID Foundations: Business rules are strictly decoupled from infrastructure for long-term maintainability.

This ecosystem is fully containerized, ensuring environment parity from development to production.

Managed via docker-compose, integrating 10+ services including databases, IAM providers, and monitoring tools.

The project includes complete manifest files for Kubernetes deployment, featuring optimized pod resource management.

Engineering Insight: The K8s configuration supports horizontal scaling and resource limits, ensuring the banking core remains resilient under high load.

We've implemented a comprehensive telemetry suite to monitor every heartbeat of the microservices ecosystem.

JVM & Request Monitoring: Utilizing Prometheus to scrape high-cardinality metrics, we visualize JVM health, memory allocation, and API latency through custom Grafana dashboards. This provides proactive insights into system stability.

Context Propagation: By integrating Jaeger, we perform end-to-end distributed tracing. This allows us to track the lifecycle of a single request across multiple services and databases, making it easy to identify latency bottlenecks in complex transaction flows.

We maintain a strict "Zero Technical Debt" policy. The project's evolution is documented through continuous static analysis to ensure high maintainability and security.

Refactoring Journey:

• Initial Report (Debt: 4h): Identification of complex lambda expressions and redundant code smells.
• Final Report (Debt: 0m): High-quality code achieved through rigorous refactoring and unit test optimizations.

We use Liquibase for version-controlled database schema changes. This ensures that every environment (Dev, Test, Prod) is perfectly synchronized with the Java entities without manual SQL execution.

Before implementation, complex SQL queries--such as high-activity sender monitoring and anti-fraud filters--are rigorously tested for performance and logic accuracy.

Transactional emails and background tasks are managed via RabbitMQ. This asynchronous approach decouples core banking logic from notification services, improving system responsiveness.

Beyond simple "UP/DOWN" status, we monitor the health of every integrated component (Postgres, Redis, RabbitMQ) through custom Actuator endpoints.

We use Loki to aggregate logs from all microservice containers. Its metadata-indexing approach allows us to correlate logs with Prometheus metrics instantly without the heavy overhead of a full ELK stack.

While Grafana provides the visuals, Prometheus handles the raw time-series data, scraping /actuator/prometheus endpoints to capture every system event and JVM metric.

The project is tested on a local 1-node cluster using Docker Desktop Kubernetes (v1.34.1) with Kubeadm, ensuring that all manifests (Secrets, PVCs, Deployments) are cloud-ready.

The system evolved from a custom JWT implementation to Keycloak. This transition ensures enterprise-grade Identity and Access Management (IAM), providing robust Role-Based Access Control (RBAC) and SSO capabilities.

Loki was strategically chosen over ELK for its resource efficiency. It indexes only metadata, leading to significantly lower storage costs and a lightweight footprint suitable for high-scale microservices.

The architecture is designed to evolve alongside business needs:

• Microservices: Extracting modules into independent services using Spring Cloud (Eureka, API Gateway) as load increases.
• Frontend: Modern SPA Dashboard using React.js & Tailwind CSS.
• Messaging: Transitioning from RabbitMQ to Apache Kafka for high-throughput streaming.
• CI/CD: Multi-stage deployment pipelines using GitHub Actions.

For granular details on Database Schema, Design Patterns, and Unit Testing (100+ Tests):

Technical Backend Documentation (BACKEND-README.md)

Follow these steps to orchestrate the entire ecosystem on your local machine:

[!NOTE] Ensure that the values in your .env file match the configurations in docker-compose.yml.

Local Infrastructure Orchestration: This view demonstrates the successful deployment of the entire development ecosystem via docker-compose. It confirms that all 10+ integrated services--including Keycloak, SonarQube, Grafana, and the core databases--are in a "Healthy" state. This ensures environment parity and proves that the system's resource allocation is optimized for a local developer machine.

Cluster Readiness & Pod Lifecycle: These logs verify that the Spring Boot application has successfully initialized within a Kubernetes Pod using the prod profile. It documents the successful connection to the managed database and the execution of schema validations. This proves that the containerized application is fully compatible with K8s orchestration, including proper handling of startup probes and environment-specific configurations.

Service Discovery & Networking: This listing showcases the active Kubernetes services within the banking namespace. It validates the networking strategy, where critical infrastructure like Postgres, Redis, and RabbitMQ are kept secure via ClusterIP, while the Banking API and Grafana are exposed via NodePort. This confirms the project's readiness for high-availability production environments.

Once the system is orchestrated, you can access the various banking services and monitoring tools via the following URLs:

Batuhan Baysal - Software Developer