This article provides a comprehensive guide to server performance optimization, covering the fundamentals of CPU, memory, and I/O analysis, practical methodologies, essential tools, and real‑world case studies to help operations engineers identify bottlenecks and improve system stability.
This article explains Oracle's system structure, the physical files used by RAC and ASM, their I/O patterns for OLTP and OLAP workloads, and provides detailed recommendations for ASM diskgroup design, redundancy, AU sizing, RAID choices, and SSD optimization for read and write intensive database operations.
This article examines how different server‑side languages model I/O, compares blocking and non‑blocking approaches, discusses scheduling overhead, presents sample code for PHP, Java, Node.js, and Go, and offers benchmark insights to help developers choose the right technology for high‑load web applications.
This article explains the end‑to‑end storage I/O path, analyzes how each node contributes to overall latency, compares IOPS and throughput, and provides practical guidance on configuring storage for Microsoft SQL Server workloads.
This article explains the key storage I/O characteristics—such as I/O size, read/write ratio, random versus sequential access, and workload patterns—across typical application types, providing reference values and guidance for storage simulation and performance testing using tools like Iometer.
This article explains the concepts of synchronous and asynchronous communication, blocking and non‑blocking thread behavior, and compares Java I/O models—including BIO, NIO, IO multiplexing, and AIO—highlighting their mechanisms, advantages, and typical use cases.
This article introduces the Linux sar command, explains its syntax and common options, and demonstrates how to sample and interpret CPU, memory, I/O, process queue, and swap metrics to identify system bottlenecks during performance testing.
The article compares Java's OIO, NIO, and AIO models, explaining how each handles threads, channels, and I/O requests, and clarifies the distinctions between synchronous, asynchronous, blocking, and non‑blocking communication, while discussing thread pooling, selector behavior, and performance implications for massive connections.
This article provides a comprehensive overview of the Linux sar command, explaining its syntax, common options, example use‑cases for CPU, memory, I/O and process monitoring, and how to interpret the output fields to identify system bottlenecks.
This article explains the differences between synchronous and asynchronous I/O, clarifies blocking versus non‑blocking calls, and describes various I/O models—including blocking, non‑blocking, multiplexed, event‑driven, and asynchronous—illustrated with diagrams to help readers understand how the kernel and user processes interact during I/O operations.
This article explains why the Linux I/O subsystem is the slowest part of the system, describes page‑level disk access, major and minor page faults, the file buffer cache, page types, write‑back mechanisms, monitoring tools, and practical tips for reducing I/O latency.
This guide explains how to enable MySQL’s Query Profiler, retrieve summary and detailed profiling data, and analyze CPU and I/O usage to pinpoint performance bottlenecks in your queries, including commands to list profiles, view specific query details, and interpret the results for optimization.
This article explains Guava’s terminology for streams, the ByteStreams and CharStreams utility methods, the deprecation of InputSupplier/OutputSupplier, and introduces the source and sink abstractions with their creation methods, common operations, and practical code examples for handling byte and character data in Java.
This article clarifies Unix I/O models by distinguishing synchronous and asynchronous operations, explaining blocking versus non‑blocking behavior, and summarizing the five classic I/O models with practical insights drawn from Richard Stevens' authoritative definitions.
