GC Tuning | BestHub

Cognitive Technology Team

Feb 16, 2025 · Operations

Resolving High Memory Utilization after Upgrading to JDK 11 with G1GC: Causes, Analysis, and Tuning Guide

After upgrading to JDK 11 and switching to G1GC, the author observed memory usage exceeding 90% due to G1 Old GC not reclaiming space, and provides a detailed analysis of the issue, including heap inspection, GC mechanisms, and practical tuning solutions such as adjusting heap size and G1GC parameters.

G1GCGC TuningJDK11

0 likes · 33 min read

Resolving High Memory Utilization after Upgrading to JDK 11 with G1GC: Causes, Analysis, and Tuning Guide

HelloTech

May 10, 2024 · Backend Development

Root Cause Analysis and Optimization of G1GC Pauses Caused by StringTable Growth in Java Services

The investigation revealed that G1GC pauses were caused by uncontrolled growth of the JVM StringTable, triggered by Jackson’s InternCache interning countless random JSON field names, and was mitigated by enlarging the young generation, disabling field‑name interning, tuning G1 parameters, and monitoring StringTable size.

G1GCGC TuningJSON interning

0 likes · 37 min read

Root Cause Analysis and Optimization of G1GC Pauses Caused by StringTable Growth in Java Services

Code Ape Tech Column

Dec 31, 2023 · Backend Development

How to Set JVM Parameters for a Platform Handling 1 Million Daily Logins on an 8 GB Server

This article explains how to estimate capacity, choose appropriate garbage collectors, and configure JVM memory settings—including heap size, young generation, thread stack, and GC options—for a service that processes one million login requests per day on a node with 8 GB of RAM, providing step‑by‑step guidance and example command lines.

GC TuningJVMJava

0 likes · 25 min read

How to Set JVM Parameters for a Platform Handling 1 Million Daily Logins on an 8 GB Server

Ctrip Technology

Jun 1, 2023 · Backend Development

Optimizing Microservice Timeout Issues: Analysis and Practical Solutions

This article examines common timeout problems in microservice architectures, identifies root causes such as connection and socket timeouts, and presents ten practical optimization techniques—including setting appropriate timeouts, rate limiting, cache improvements, thread‑pool tuning, GC and JIT adjustments, NIO async programming, host migration, and network checks—to enhance system stability and performance.

CachingGC Tuningbackend performance

0 likes · 21 min read

Optimizing Microservice Timeout Issues: Analysis and Practical Solutions

Architect's Guide

Aug 24, 2022 · Backend Development

Optimizing Long‑Connection Services with Netty: From Millions of Connections to High QPS

This article summarizes the challenges and optimization techniques for building a high‑performance long‑connection service with Netty, covering non‑blocking I/O, Linux kernel tuning, client‑side testing, VM‑based scaling, data‑structure tweaks, CPU and GC bottlenecks, and the final results of achieving hundreds of thousands of connections and tens of thousands of QPS on a single server.

GC TuningJava NIOLinux Tuning

0 likes · 14 min read

Optimizing Long‑Connection Services with Netty: From Millions of Connections to High QPS

Code Ape Tech Column

Mar 2, 2022 · Backend Development

JVM GC Tuning Case Study: Reducing YGC Frequency and Boosting Service Performance

The author describes a high‑QPS Java web service, analyzes its GC behavior using jstat and gceasy, applies JVM parameter adjustments such as enlarging the young generation, tweaking MaxTenuringThreshold and disabling biased locking, and achieves roughly a 15% overall performance gain with improved GC throughput.

GC TuningJVMJava

0 likes · 8 min read

JVM GC Tuning Case Study: Reducing YGC Frequency and Boosting Service Performance

JD Retail Technology

Dec 2, 2021 · Backend Development

Optimizing JD.com Flash Sale Product Pool: Architecture Upgrade and Performance Tuning

This article details how JD.com’s flash‑sale system tackled rapid product‑pool growth by analyzing JVM memory issues, redesigning the architecture with double‑buffered updates, local LRU caching, system splitting, and Bloom‑filter integration, resulting in significant performance and stability improvements for large‑scale promotions.

CachingGC TuningJVM

0 likes · 15 min read

Optimizing JD.com Flash Sale Product Pool: Architecture Upgrade and Performance Tuning

Big Data Technology Architecture

Nov 28, 2021 · Big Data

Investigation and Resolution of HiveServer2 JDBC Connection Failures and GC‑Induced Hang

The article analyzes why HiveServer2 experiences JDBC connection failures and task execution stalls under high concurrency, reproduces the issues using GC monitoring and large join queries, and presents memory‑ and GC‑tuning solutions including server migration and JVM parameter adjustments to improve stability.

Big DataGC TuningHadoop

0 likes · 7 min read

Investigation and Resolution of HiveServer2 JDBC Connection Failures and GC‑Induced Hang

High Availability Architecture

Jul 6, 2021 · Backend Development

Tuning a Go Service to Reach 200k QPS: GC Adjustment and UDP Optimizations

The article describes how a Go‑based high‑throughput service was tuned from 80k to over 200k QPS by enlarging the GC heap, reusing UDP connections with sync.Pool, reducing system‑call overhead, and applying several lightweight logging and discovery optimizations.

GC TuningGoPerformance

0 likes · 8 min read

Tuning a Go Service to Reach 200k QPS: GC Adjustment and UDP Optimizations

Youzan Coder

Jan 13, 2021 · Big Data

Flink Real-time Task Resource Optimization Practice at Youzan

At Youzan, Flink real‑time tasks running on Kubernetes are optimized by daily GC‑log memory analysis and Kafka‑throughput monitoring, which compute recommended heap sizes and parallelism adjustments to eliminate over‑provisioned CPU and memory, automate alerts, and pave the way for fully automated resource tuning.

Big DataFlinkGC Tuning

0 likes · 16 min read

Flink Real-time Task Resource Optimization Practice at Youzan

Big Data Technology Architecture

Jul 3, 2020 · Big Data

Overview of Elasticsearch Architecture and Optimization Strategies

This article explains Elasticsearch's architecture, including its reliance on Apache Lucene, shard and replica design, routing optimization, JVM garbage‑collection tuning, memory‑locking, and index‑merge control, offering practical guidance for building and operating high‑performance search clusters.

Big DataElasticsearchGC Tuning

0 likes · 11 min read

Overview of Elasticsearch Architecture and Optimization Strategies

58 Tech

Mar 20, 2019 · Operations

JVM GC Tuning for Java Service Migration to a Private Cloud: A Multi‑Round Optimization Case Study

During the migration of a billion‑record Java service from physical servers to a private‑cloud Docker environment, a series of JVM GC tuning steps—including adaptive young generation sizing, larger young generation, reduced concurrent GC threads, and phantom‑reference cleanup—significantly reduced stop‑the‑world pauses and restored service performance.

DockerGC TuningJVM

0 likes · 10 min read

JVM GC Tuning for Java Service Migration to a Private Cloud: A Multi‑Round Optimization Case Study