I have extensive experience with several server-side languages, including Node.js, Python, and Java. Each has its strengths, but I prefer Node.js for its non-blocking I/O model and the vast npm ecosystem, which accelerates development. Python is my go-to for its readability and the powerful Django and Flask frameworks, while Java's robustness makes it ideal for large-scale systems. My choice depends on the project requirements, team expertise, and performance considerations.

Security is paramount in back-end development. I implement several measures, including input validation to prevent injection attacks, using HTTPS for data in transit, and encrypting sensitive data at rest. I also keep dependencies updated to avoid vulnerabilities and use authentication and authorization mechanisms like OAuth and JWT. Regular security audits and adhering to best practices like the principle of least privilege further enhance the security of the services I develop.

Once, I faced a performance bottleneck in a database-heavy application. The queries were slow, affecting user experience. I analyzed the queries using EXPLAIN to identify inefficiencies, indexed the right columns, and optimized the queries. For complex operations, I introduced caching with Redis, significantly reducing the load on the database. This approach improved response times by over 70%, demonstrating the importance of profiling and targeted optimizations in back-end development.

In distributed systems, I ensure data consistency by implementing strategies like two-phase commits or using eventual consistency models where appropriate. I leverage distributed transactions when strong consistency is required, and for systems where high availability is critical, I opt for eventual consistency, ensuring conflicts are resolved through application logic or conflict-free replicated data types (CRDTs). Monitoring and reconciliation processes are also key to maintaining consistency across distributed databases.

I adopt a multi-layered testing strategy for back-end code, starting with unit tests for individual components, integration tests to verify interactions between components, and end-to-end tests for the entire system. I use mocking and stubbing to isolate tests and ensure they're reliable and fast. Continuous integration pipelines run these tests automatically, and I prioritize test coverage for critical paths. This comprehensive approach ensures robustness and facilitates refactoring with confidence.