Database Insights

A top-down playbook for high-performance MongoDB: measure with the profiler and explain(), model for access patterns, index by the ESR rule, keep the working set in the WiredTiger cache, pool connections, and scale reads with secondaries and sharding — with flow diagrams for each layer.

A repeatable, top-down method for tuning PostgreSQL: measure with pg_stat_statements, read plans with EXPLAIN (ANALYZE, BUFFERS), fix queries and indexes before parameters, then tune memory, I/O, WAL, connection pooling, and autovacuum — with a ready-to-adapt postgresql.conf baseline.

Configure MySQL binlog retention safely: binlog_expire_logs_seconds, manual purging rules, AWS RDS retention, and the disk-exhaustion failure mode you should monitor for.

Production MariaDB Galera Cluster: mariabackup-based SST, MaxScale Galera-aware routing, schema-change strategy with TOI vs RSU, and a troubleshooting playbook for the failures that actually take down production.

Complete guide to StarRocks monitoring with Prometheus and Grafana. Covers resource saturation, cluster health, and application availability alerts with PromQL expressions and runbooks.

Use Apache Airflow to orchestrate database ETL, backup jobs, and maintenance tasks — DAGs, sensors, and best practices

Define meaningful SLOs and SLAs for your database tier — latency, availability, durability, and error budgets

A practical runbook for database incidents — triage, diagnosis, escalation, and post-mortem for MySQL and PostgreSQL

Set up MySQL Orchestrator for automatic failover, topology discovery, and master election at scale

Fine-tune PostgreSQL autovacuum to eliminate dead tuples, prevent table bloat, and maintain query performance

Use MySQL Performance Schema to profile queries, monitor memory, and diagnose bottlenecks without guesswork

Decode PostgreSQL wait events to diagnose lock contention, I/O bottlenecks, and CPU pressure in production