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This article investigates the severe memory growth and latency spikes observed when synchronizing data across data centers in a Netty‑driven online computation service, analyzes the impact of JDK 17 ZGC and direct‑buffer allocation, and presents the debugging steps, source‑code insights, and configuration changes that ultimately resolved the issue.
Didi upgraded its self‑developed Elasticsearch from JDK 11/G1 to JDK 17, adopting ZGC for latency‑critical clusters and tuned G1 for throughput, which eliminated long GC pauses, reduced query latency by up to 96%, cut CPU usage, and dramatically improved stability across multiple production clusters.
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