This article examines Druid 1.1.5 connection‑pool settings—maxWait, connectionProperties, keepAlive, maxActive—illustrates real‑world cases of misconfiguration, provides recommended values, and shares a step‑by‑step investigation of a DB slow‑query incident to help engineers prevent performance and stability issues.
This article analyzes a production Java service that repeatedly hit org.apache.http.conn.ConnectionPoolTimeoutException due to exhausted HttpClient connection pools, explains how CLOSE_WAIT sockets are created when responses are not closed, and provides step‑by‑step code fixes and Tomcat configuration tweaks to eliminate the problem.
This article explains the concept, design considerations, and step‑by‑step implementation of a lightweight database connection pool in Java, covering its core components, thread‑safe management, configuration handling, and a test demonstration of its functionality.
This article explains how to correctly configure JedisPool and its underlying GenericObjectPoolConfig, provides Maven dependency details, demonstrates pool initialization and usage patterns, and offers practical recommendations for maxTotal, maxIdle, minIdle, idle monitoring, and warm‑up to ensure stable and efficient Redis operations in Java applications.
This article explains why creating a database connection for each request is inefficient, introduces the concept and configuration of connection pools, provides a custom Java DataSource implementation, and demonstrates the use of popular open‑source pools such as DBCP, C3P0, and Tomcat JNDI with complete code examples.
The team rescued a crashing Redis cache handling 100K‑120K QPS by shrinking Nginx Lua timeouts, trimming connection pools, adding four Redis nodes behind Twemproxy, and splitting keys to raise cardinality, which eliminated connection spikes, balanced shard load, and restored stable performance.
This guide explains Druid’s key features—including a high‑performance connection pool, SQL monitoring, password encryption, and customizable JDBC filters—and provides step‑by‑step instructions for configuring the pool, creating a custom DruidPasswordCallback, generating RSA keys, encrypting passwords, and integrating the setup into Spring.
The article examines how various JDBC connection pools such as Tomcat‑JDBC, Druid, c3p0, HikariCP, and BoneCP handle connection validation parameters like testOnBorrow, validationInterval, and idle checks, and provides recommendations for critical applications.
This article explains how Tomcat JDBC connection pool settings such as testOnBorrow, testOnReturn, testWhileIdle, and testOnConnect work, discusses related parameters like maxActive and removeAbandoned, and presents performance testing to guide reliable and efficient database connection management.
This guide outlines practical MySQL optimization strategies—including table schema design, index creation, SQL tuning, connection‑pool configuration, and historical data archiving—to help developers maintain fast, scalable databases as data volume grows.
A developer recounts how a Redis connection pool overflow across dozens of clusters was traced to a single misbehaving service, diagnosed with netstat and ps commands, and resolved by adjusting configuration and stopping the offending process, illustrating practical troubleshooting of connection limits.
This article presents practical MySQL optimization techniques covering table schema design, character set choices, primary key strategies, field definitions, index creation, SQL query tuning, pagination tricks, join handling, connection‑pool parameter tuning, and historical data archiving for large‑scale databases.
Heroku shares five practical Redis recommendations—including using connection pools, naming clients, selecting key eviction policies, avoiding the KEYS command, and configuring connection timeouts—to improve performance, manage resources, and simplify troubleshooting in production environments.
This article explains why cache and database can become inconsistent in distributed systems, why the "invalidate‑cache‑then‑write‑DB" rule is preferred, and presents practical serialization techniques—modifying DB and service connection pools—to guarantee per‑key sequential execution while maintaining availability and load balance.
This article explains how to create an asynchronous MySQL proxy server using the Swoole extension, detailing connection pooling, idle/busy management, request queuing, and providing a complete PHP implementation that reduces MySQL load and network overhead for PHP applications.
