Deep dives on PostgreSQL, MySQL, MongoDB and more — performance tuning, high availability, migrations and production war stories from our DBAs.
398 articles
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Complete guide to StarRocks monitoring with Prometheus and Grafana. Covers resource saturation, cluster health, and application availability alerts with PromQL expressions and runbooks.
Showing 12 of 398 articles
Monitor MySQL and PostgreSQL with Prometheus, Grafana, and PMM. Covers mysqld_exporter, postgres_exporter, alert rules, and production dashboard configuration.
Tune Redis from measured latency and memory behavior: bound command work, fix big and hot keys, choose eviction intentionally, and test persistence.
Secure your MySQL and PostgreSQL databases — TLS, at-rest encryption, role-based access, and audit logging
PgBouncer multiplexes thousands of application connections onto a small pool of real PostgreSQL server connections — reducing connection overhead without any application code changes.
Running a single PMM server is a single point of failure for your database monitoring. Here's how to set up PMM in an HA configuration with failover and shared storage.
mysqlpump adds parallel backup support to MySQL's logical dump toolset — enabling multi-threaded exports that can be 3-5x faster than mysqldump for large databases.
A deep dive into InnoDB locking — record locks, gap locks, next-key locks, how READ COMMITTED eliminates gap locks, diagnosing deadlocks with SHOW ENGINE INNODB STATUS and performance_schema, and prevention patterns.
MySQL InnoDB supports multiple compression strategies — from ROW_FORMAT=COMPRESSED to transparent page compression using punch holes. Choosing the right approach can cut storage by 40-70% for text-heavy workloads.
Deploy PgBouncer in transaction mode for high-concurrency PostgreSQL workloads — config, monitoring, and tuning
Essential MySQL diagnostic queries every DBA needs. Quickly identify slow queries, lock contention, replication lag, memory issues, and connection problems.
A practical guide to Redis use cases in production — cache-aside pattern, sliding window rate limiting, Pub/Sub vs Streams, BRPOP queues with delayed job scheduling, and session storage with persistence configuration.
Understand Kafka from a database perspective — partitions, offsets, consumer groups, and durability guarantees
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