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This article explains how to improve a high‑traffic Java service by reusing a singleton HttpClient, enabling keep‑alive, configuring a pooling connection manager, and adding an idle‑connection monitor, which reduces average request latency from 250 ms to about 80 ms.
This article details a step‑by‑step optimization of Apache HttpClient—including connection pooling, keep‑alive, singleton client usage, timeout tuning, and response handling—to reduce average request latency from 250 ms to about 80 ms in a high‑throughput Java service.
This article details how to dramatically improve the performance of a million‑level QPS Java service by reusing a singleton HttpClient, enabling keep‑alive connection pooling, and handling responses efficiently, cutting average request time from 250 ms to about 80 ms.
This article explains how to dramatically improve the performance of a high‑traffic Java service by reusing a singleton HttpClient, enabling connection pooling and keep‑alive, tuning timeout and retry settings, and adding an idle‑connection monitor to reduce average request latency from 250 ms to about 80 ms.
This article explains how to dramatically reduce HttpClient request latency from 250 ms to about 80 ms in a high‑traffic service by using a singleton client, connection pooling, keep‑alive strategies, proper timeout settings, and efficient response handling, complete with code examples.
The article investigates frequent HttpClient connection‑pool exhaustion caused by excessive CLOSE_WAIT sockets in a high‑traffic Java service, explains the underlying TCP and HttpClient mechanisms, presents diagnostic commands and code snippets, and offers concrete configuration and architectural recommendations to prevent similar issues.
The article documents a systematic investigation of why an Apache HttpClient‑based utility class fails to reuse connections, reproduces the problem with a test server and client, analyzes Tomcat's default maxKeepAliveRequests limit of 100, and provides recommendations for configuration.