This comprehensive guide covers HikariCP internals, core parameter tuning, connection leak detection, handling MySQL wait_timeout disconnections, preventing cascade failures, production-ready configuration examples, monitoring with Micrometer, and comparison with Druid for Spring Boot applications.
This article presents a practical checklist of 20 Linux kernel parameters—grouped by network, memory, process, and filesystem settings—explaining their default values, typical failure symptoms, step‑by‑step tuning commands, verification methods, and rollback procedures to ensure production systems such as web servers, databases, caches, and containers run without kernel‑level bottlenecks.
This guide walks through the complete workflow for analyzing, configuring, and validating Nginx in high‑traffic environments, covering architecture basics, core parameters, system limits, practical configuration examples, stress‑testing methods, monitoring, risk mitigation, rollback procedures, and production‑grade best practices.
This article walks through the complete load‑testing and performance‑tuning workflow for a Spring Cloud microservice application, covering environment preparation, JMeter script creation, benchmark execution, bottleneck analysis, JVM, database pool, and Sentinel optimizations, and presents before‑and‑after results with a detailed checklist.
This article walks through a real‑world performance bottleneck on a high‑traffic e‑commerce platform, explains step‑by‑step deep tuning of Nginx Ingress Controller, compares it with Envoy Gateway, and provides concrete configurations, benchmark results, monitoring rules, and best‑practice recommendations for Kubernetes Ingress optimization.
The article outlines JVM tuning fundamentals, categorizing common issues, presenting six optimization principles, detailing key JVM parameters, and introducing the jps command‑line tool to help developers diagnose and improve Java application performance while maintaining stability.
This guide walks you through a fast, five‑minute checklist for tuning Linux kernel parameters via sysctl.conf to boost network throughput, reduce connection latency, and improve stability for high‑traffic web, API, database, and container workloads.
This comprehensive guide walks you through the Linux IO stack, explains key metrics from iostat and iotop, demonstrates advanced tracing with blktrace and bpftrace, shows how to benchmark with fio, and provides practical tuning steps to resolve high‑IO latency and system hangs.
This guide explains how to maximize Nginx's concurrent handling capacity by configuring worker_processes, worker_connections, event settings, system limits, and I/O optimizations, providing concrete code snippets and kernel parameters for achieving tens of thousands of simultaneous connections.
Learn how to maximize Nginx throughput by correctly configuring worker_processes, worker_connections, enabling epoll, and using accept_mutex, with practical examples, formulae, and system‑level tweaks to avoid common pitfalls like CPU oversubscription and 'too many open files' errors.
This article explains why MySQL replication lag hurts performance, then details a three‑layer parallel replication strategy—including logical‑clock parallelism, binlog group‑commit tuning, and slave‑side optimizations—provides full my.cnf configurations, performance test results, monitoring commands, utility scripts, common pitfalls, and a summary of the achieved improvements.
This guide explains how to tune Nginx for maximum performance by leveraging multi‑core CPUs, increasing concurrent connections, enabling zero‑copy file transfer, and optimizing keep‑alive settings, with concrete configuration examples and practical recommendations.
This comprehensive guide walks you through the exact scenarios, prerequisites, a 20‑item checklist, and step‑by‑step implementations for tuning CPU scheduling, memory swappiness, huge pages, disk I/O schedulers, network queues, TCP parameters, IRQ affinity, cgroup limits, and monitoring, providing scripts, alert rules, benchmarks, security hardening, troubleshooting tables, rollback playbooks, and best‑practice recommendations for high‑performance Linux servers.
This comprehensive guide walks you through enterprise‑grade Nginx tuning, covering worker process settings, event model tweaks, memory and buffer adjustments, compression, SSL/TLS hardening, load‑balancing, caching strategies, monitoring, system‑level kernel tweaks, and practical troubleshooting steps to dramatically increase request throughput.
This article walks through practical Nginx performance tuning—optimizing worker processes, expanding connection limits, enabling caching and gzip, adjusting kernel parameters, and providing a one‑click diagnostic script—backed by real benchmark data that shows up to five‑fold improvements in concurrency and response times.
This article explains how operations engineers can dramatically improve Linux network performance by understanding key metrics and applying practical tuning methods—such as adjusting TCP windows, enabling TCP Fast Open, switching to BBR, optimizing kernel parameters, using high‑performance NICs, zero‑copy transfers, load balancing, and monitoring tools—to increase bandwidth and reduce latency for high‑concurrency and real‑time applications.
This article explains how send and receive socket buffers work, why they are crucial for TCP flow and congestion control, how to tune kernel parameters and application settings, and what common pitfalls and testing methods help keep network services stable and efficient.
This article details 360's comprehensive approach to improving Apache Kafka cluster stability through proactive operations, capacity assessment, parameter tuning, monitoring, version upgrades, and traffic control, offering concrete guidelines and best‑practice recommendations for large‑scale message‑queue deployments.
This article introduces several MySQL performance‑diagnostic utilities—including mysqltuner.pl, tuning‑primer.sh, pt‑variable‑advisor, and pt‑query‑digest—explains how to download and run them, interprets their reports, and also contains promotional material for unrelated AI services.
This article explains how to monitor, interpret, and optimize Java Garbage Collection by using JDK flags, IDE configurations, and the gceasy.io visualizer, providing step‑by‑step guidance, sample logs, and performance metrics for effective JVM tuning.
This article explains how to enable detailed GC logging in the JVM, interpret both Young and Full GC log entries, configure heap parameters, and use the online visualizer gceasy.io to analyze performance metrics such as throughput, pause latency, and memory usage for effective JVM tuning.
This comprehensive guide outlines five common MySQL performance problems, a step‑by‑step investigation methodology, detailed Java middleware and database analyses, practical tuning tactics such as index optimization and sharding, and a governance framework for sustainable performance management.
This article walks through a Spark job’s garbage‑collection tuning workflow, presents step‑by‑step experiments with different JVM options and collectors, compares performance under tight and normal memory conditions, and offers practical recommendations for choosing the optimal GC strategy in big‑data workloads.
This guide explains why regular MySQL health checks are crucial and introduces four open‑source performance tools—mysqltuner.pl, tuning-primer.sh, pt‑variable‑advisor, and pt‑query‑digest—detailing how to download, run, and interpret their reports to optimize configuration, detect bottlenecks, and improve security.
This article explains how to design a gRPC connection pool, covering scaling rules, idle‑connection timeout and keep‑alive, pool‑full handling, core gRPC features, and practical tuning parameters to achieve high performance in high‑concurrency backend services.
This article details practical Elasticsearch tuning steps—adjusting index buffers, thread pools, refresh intervals, and translog settings—to raise average write speed from 3,000 to 8,000 documents per second and maintain stability under load.
This article examines a real‑world MySQL master‑slave replication delay case, analyzes the root causes using slave status, InnoDB metrics, OS‑level I/O and error logs, and provides concrete configuration and operational recommendations to reduce lag.
This article introduces four popular MySQL performance‑tuning utilities—mysqltuner.pl, tuning-primer.sh, pt-variable-advisor, and pt-query-digest—explaining how to download, run, and interpret their reports to identify configuration issues, memory bottlenecks, and slow‑query problems.
This guide explains how to boost Nginx Ingress Controller throughput in high‑concurrency Kubernetes environments by adjusting kernel parameters, fine‑tuning Nginx settings, and applying optimal ConfigMap configurations for keep‑alive, timeouts, worker connections, retries, and Brotli compression.
This guide introduces four powerful MySQL performance‑tuning utilities—MySQLTuner.pl, tuning‑primer.sh, pt‑variable‑advisor, and pt‑query‑digest—detailing their installation, command‑line usage, and how to interpret the generated reports to optimize database configuration and query efficiency.
This article details 58.com’s big‑data team’s migration of HBase clusters from CMS/G1 to the low‑latency Z Garbage Collector, explains ZGC’s design and key techniques, presents performance test results versus CMS, discusses tuning parameters, and shares practical lessons from production deployment.
This article presents a systematic benchmark of MySQL 5.7.22 and MySQL 8.0.15 using sysbench to measure TPS and QPS across read‑write, read‑only, and write‑only modes under two persistence configurations, analyzes the results, and provides a Bash script for reproducing the tests.
The article explains why a small database connection pool combined with a large queue of waiting threads yields better performance, illustrates this with Oracle and PostgreSQL benchmark data, and provides a practical formula for calculating the optimal pool size based on CPU cores and effective disks.
This guide consolidates practical Elasticsearch tuning techniques—from configuration file settings and system‑level adjustments to usage‑level optimizations—covering memory locking, discovery, fault detection, queue sizing, JVM heap, file descriptors, translog handling, bulk indexing, shard management, and best practices to achieve a stable, high‑performance cluster.
This article explains how to monitor and tune Linux network packet reception using tools such as ethtool, ifconfig, and procfs, covering RingBuffer inspection, hardware and soft interrupt analysis, multi‑queue configuration, interrupt coalescing, and GRO settings to improve throughput and reduce packet loss.
The article explains why a small database connection pool often yields better performance than a large one, illustrates the point with Oracle and PostgreSQL benchmark data, and provides a simple formula to calculate the optimal pool size based on CPU cores and effective disks.
This article explains how HBase uses WAL and MemStore to create HFiles, describes the two compaction types (Minor and Major), and provides detailed recommendations for tuning key compaction-related configuration parameters to improve query performance and reduce HDFS impact.
This article explains the most important Kafka producer configuration parameters—such as acks, max.request.size, retries, compression.type, buffer.memory, batch.size, linger.ms, request.timeout.ms, and max.in.fight.requests.per.connection—provides practical tuning advice, and presents a recommended setup to achieve high throughput without message loss.
This guide explains how to improve web service performance by tuning Linux system parameters and Nginx configuration, covering file descriptor limits, TCP connection queues, temporary port ranges, worker processes, keepalive settings, and access‑log buffering, with concrete sysctl and Nginx directives.
This guide explains how to optimize Nginx by configuring worker processes, CPU affinity, file descriptor limits, event models, HTTP settings, keep‑alive timeouts, FastCGI parameters, gzip compression, expires caching, anti‑hotlinking, kernel tweaks and system connection limits for high‑traffic Linux servers.
This article summarizes essential JVM tuning flags—including AutoBoxCacheMax, AlwaysPreTouch, CMSInitiatingOccupancyFraction, MaxTenuringThreshold, ExplicitGCInvokesConcurrent, and memory settings—explaining their effects on object caching, memory allocation, garbage‑collection behavior, and overall Java application performance.
The article investigates why one of two identical Alibaba Cloud servers experiences frequent Full GC pauses, analyzes heap and GC logs, compares 3‑, 6‑, and 12‑hour metrics, and proposes JVM heap‑size and flag adjustments to eliminate the issue.
This guide details how to optimize Nginx for high‑traffic sites by configuring worker processes, CPU affinity, file descriptor limits, event handling, fastcgi, gzip compression, expires caching, anti‑leech rules, and kernel parameters, providing concrete code snippets and practical recommendations.
This article shares a detailed, experience‑driven guide on Elasticsearch tuning, covering data model fundamentals, storage cost reductions, cluster stability tricks, performance‑boosting settings, and custom kernel improvements, all illustrated with real‑world diagrams and Q&A insights.
This guide explains key Linux kernel and Nginx configuration adjustments—such as backlog queues, file descriptor limits, worker processes, keepalive settings, and logging options—to help administrators maximize web server performance while following safe, incremental tuning practices.
This guide explains how to fine‑tune Linux kernel parameters and NGINX directives—such as backlog queues, file descriptors, worker processes, keep‑alive settings, access‑log buffering, sendfile, and request limits—to achieve optimal web server performance for high‑traffic sites.
This guide details MySQL’s key configuration variables—including connection limits, file handling, cache controls, MyISAM and InnoDB settings—explaining their default values, recommended ranges, and how to adjust them for optimal performance, stability, and resource utilization.
This guide explains how to select optimal hardware, configure CPU affinity, adjust kernel parameters for short and long connections, enable SSL offload, and use HAProxy multi‑process mode to achieve the highest possible throughput and stability.
This guide explains how to optimize Nginx by configuring worker processes based on CPU cores, setting CPU affinity, adjusting file descriptor limits, fine‑tuning the event model, enabling sendfile and gzip, configuring FastCGI, applying expires headers, preventing hotlinking, and tuning Linux kernel parameters for maximum throughput and stability.
This article enumerates Oracle's most common wait events, explains the underlying reasons each event occurs, lists the associated parameters, provides sample queries for inspection, and offers practical guidance on diagnosing and mitigating performance issues caused by these waits.
This article examines the performance challenges of a 700‑node Redis Cluster used by Youku, analyzes bandwidth and latency impacts of cluster communication, and presents practical tuning methods—including adjusting cluster‑node‑timeout, reducing replicas, disabling AOF, limiting cluster‑nodes commands, and tuning the hz parameter—to improve throughput and stability in massive Redis deployments.
This article shares practical Elasticsearch experience covering index and query performance optimization, shard routing strategies, JVM tuning, daily maintenance, and answers to common production questions, providing actionable guidance for building high‑availability search clusters.
Learn how to accelerate MySQL sorting by increasing the max_length_for_sort_data parameter, removing unnecessary columns, and enlarging sort_buffer_size, ensuring the server uses the more efficient in‑memory sorting algorithm while avoiding costly data segmentation and temporary tables.
This article summarizes Brendan Gregg's LinuxCon NA 2014 talk, presenting the most reliable, time‑tested Linux performance utilities and illustrating the monitoring, benchmarking, and tuning tools for various subsystems with clear diagrams.
This guide presents practical Linux system tweaks and PHP configuration adjustments—including file descriptor limits, disabling atime, using tmpfs, and optimizing php.ini and PHP‑FPM settings—to dramatically improve high‑load PHP application responsiveness and stability.
