LarsArtmann/website-holger-hahn

AI Summary: Implement a comprehensive testing strategy for a Go web application, including BDD tests using Ginkgo, achieving 80%+ test coverage across unit, integration, and end-to-end tests, covering database operations, HTMX interactions, and email services. This involves setting up the Ginkgo framework, writing tests for various aspects of the application, and integrating automated testing into a CI/CD pipeline.

AI Summary: Implement comprehensive security hardening measures for Holger M. Hahn's professional website, addressing vulnerabilities identified in a security assessment. This includes fixing file permission issues, adding input validation and sanitization, implementing rate limiting and CSRF protection, configuring security headers (HSTS, CSP, X-Frame-Options), setting up HTTPS enforcement, preventing SQL injection, and improving session management. The goal is to ensure the website meets security best practices and complies with regulations relevant to the financial services industry.

AI Summary: Merge two Go applications (`main.go` and `cmd/server/main.go`) into a single unified application. This involves consolidating their routing, dependency injection (`samber/do` recommended), and removing duplicate code related to containers. The goal is to create a single entry point and consistent architecture, reducing technical debt and improving maintainability.

AI Summary: Implement a complete CI/CD pipeline using GitHub Actions, Dockerize the Go application, set up a staging environment, and establish a robust production deployment strategy with rollback capabilities, including infrastructure as code and environment configuration management. This involves integrating with existing testing and observability efforts and ensuring secure deployment practices.

AI Summary: Implement event sourcing for Holger M. Hahn's professional website, adding an event store, event streams, projections, and replay capabilities to enhance auditability, debugging, and business intelligence. This involves significant architectural changes, impacting several existing components and potentially requiring a simpler alternative if the complexity outweighs the benefits for a portfolio website.

AI Summary: Implement comprehensive observability and monitoring for a Go web application, including structured logging (using uniflow or charmbracelet), distributed tracing (OpenTelemetry), metrics collection (business and system), health checks, performance monitoring, and alerting. This is crucial for production deployment and operational excellence, especially given the financial context of the application.

AI Summary: Implement Domain-Driven Design (DDD) principles in an existing Go web application. This involves defining bounded contexts, creating aggregates and value objects, implementing domain events, and separating domain logic from infrastructure concerns. The goal is to improve the application's architecture to support future implementation of CQRS and Event Sourcing.