analysis and identification with monitoring tools You can use postman to see the response time. - reduce excessive join tables, max 3 joins - use index table - You can denormalize the table - use redis atau caching toola for cache your data - use load balance - you can use combine write and read database (syncronize)

Use monitoring tools to continuously monitor key metrics like query response times, resource utilization (CPU, memory, disk I/O), and connection pool sizes. Optimize SQL performance through parameterization and indexing of frequently accessed columns. Enhance hardware to improve overall database throughput (e.g., faster CPUs, increased RAM, high-performance storage).

To minimize downtime during database bottlenecks: Analyze Bottlenecks: Use monitoring tools to identify slow queries, locks, or resource contention. Scale Resources: Temporarily increase CPU, memory, or IOPS capacity if possible. Optimize Queries: Tune slow queries, add missing indexes, and enforce proper query patterns. Implement Caching: Use in-memory caching (e.g., Redis) for frequently accessed data. Enable Load Balancing: Distribute workloads across replicas or database clusters. Use Maintenance Windows: Schedule fixes during low-traffic periods. Leverage Connection Pooling: Optimize application connections to avoid overload. Monitor Continuously: Adjust dynamically based on real-time metrics.

To keep my system running smoothly, optimize queries for faster execution, scale horizontally with more servers, and implement caching to reduce frequent database hits. Enhance performance with indexing, load balancing, and read/write splitting across replicas. Shard my database to spread the load, use connection pooling for efficiency, and replicate for fault tolerance. Time-based scaling ensures the right resources during peak periods, while regular maintenance keeps the database at its best. By combining these strategies, can minimize downtime and ensure seamless performance even under high traffic.

To minimize downtime, always monitor incoming queries and apply query optimization, caching and indexing which also really helps improve database performance. downtime queries is a big problem for users, so solve it.