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Java Tech Enthusiast

Apr 9, 2025 · Databases

MySQL vs PostgreSQL Performance Benchmark: Latency, Throughput, and Saturation

The benchmark comparing MySQL 9.0 and PostgreSQL 17.0 shows PostgreSQL consistently achieving lower insertion latency, roughly double the throughput (≈19 k QPS vs 10 k QPS), using less CPU, memory and disk I/O, while both hit an 80‑connection pool limit and PostgreSQL maintains stable read latency as MySQL’s performance degrades beyond ~5.5 k QPS.

MySQLPerformance BenchmarkPostgreSQL

0 likes · 7 min read

MySQL vs PostgreSQL Performance Benchmark: Latency, Throughput, and Saturation

Test Development Learning Exchange

Nov 5, 2024 · Fundamentals

Performance Testing Metrics: A Comprehensive Guide

Performance testing involves monitoring various metrics to assess system behavior under different conditions, including response time, throughput, CPU usage, memory utilization, and error rates.

CPU utilizationDatabase OptimizationMemory usage

0 likes · 8 min read

Performance Testing Metrics: A Comprehensive Guide

DataFunSummit

Apr 10, 2024 · Artificial Intelligence

Large Language Model Inference Overview and Performance Optimizations

This article presents a comprehensive overview of large language model inference, describing the prefill and decoding stages, key performance metrics such as throughput, latency and QPS, and detailing a series of system-level optimizations—including pipeline parallelism, dynamic batching, KV‑cache quantization, and hardware considerations—to significantly improve inference efficiency on modern GPUs.

GPUInferencelatency

0 likes · 23 min read

Large Language Model Inference Overview and Performance Optimizations

DataFunTalk

Feb 19, 2024 · Artificial Intelligence

Large Language Model Inference Overview and Performance Optimizations

This article presents a comprehensive overview of large language model inference, detailing the prefill and decoding stages, key performance metrics such as throughput, latency and QPS, and a series of system-level optimizations—including pipeline parallelism, dynamic batching, specialized attention kernels, virtual memory allocation, KV‑cache quantization, and mixed‑precision strategies—to improve GPU utilization and overall inference efficiency.

GPUInferenceLLM

0 likes · 24 min read

Selected Java Interview Questions

Feb 1, 2024 · Operations

AngusTester Single-Node Throughput Test Achieving Over 600,000 TPS

This article documents a performance benchmark of AngusTester on a single node, demonstrating over 600,000 transactions per second against an Nginx HTTP server, and details the test purpose, environment, configuration, execution steps, and result analysis.

AngusTesterPerformance Testingbenchmark

0 likes · 6 min read

AngusTester Single-Node Throughput Test Achieving Over 600,000 TPS

Top Architect

Dec 25, 2023 · Backend Development

Performance Tuning of a Spring Boot Backend: Identifying and Resolving Throughput Bottlenecks

The article details a step‑by‑step investigation of a Spring Boot service that failed to meet a 500 requests/second target, analyzes slow SQL, thread‑pool misconfiguration, excessive logging, and high CPU usage, and presents concrete optimizations that roughly doubled throughput.

JavaSpring Bootbackend

0 likes · 17 min read

Performance Tuning of a Spring Boot Backend: Identifying and Resolving Throughput Bottlenecks

Code Ape Tech Column

Nov 8, 2023 · Backend Development

Performance Tuning of a Spring Backend Service to Reach 500 Requests per Second

The article details a step‑by‑step performance investigation and optimization of a Spring‑based ToB system, covering slow SQL, thread‑pool tuning, JVM memory adjustments, excessive logging, and bean‑creation overhead, ultimately improving throughput from 50 req/s to nearly the required 500 req/s.

JVMRedisSQL

0 likes · 13 min read

Performance Tuning of a Spring Backend Service to Reach 500 Requests per Second

Architecture Digest

Oct 31, 2023 · Backend Development

Performance Troubleshooting and Optimization of a ToB System: From Low Throughput to Improved CPU Utilization

This article documents a step‑by‑step investigation of a Java Spring backend that initially achieved only 50 requests per second under load, detailing how slow SQL, excessive logging, thread‑pool misconfiguration, bean‑creation overhead and CPU‑bound operations were identified and mitigated to roughly double the throughput while reducing response latency.

JavaSpringbackend

0 likes · 14 min read

Performance Troubleshooting and Optimization of a ToB System: From Low Throughput to Improved CPU Utilization

Selected Java Interview Questions

Oct 27, 2023 · Backend Development

Diagnosing and Optimizing Throughput and CPU Usage in a Java Spring Backend Service

The article details a step‑by‑step investigation of a Java Spring backend that initially achieved only 50 req/s under load, identifies bottlenecks such as slow SQL, excessive logging, thread‑pool misconfiguration and costly Spring bean creation, and demonstrates how targeted optimizations roughly doubled throughput while reducing response times.

CPUJavaPerformance

0 likes · 14 min read

Diagnosing and Optimizing Throughput and CPU Usage in a Java Spring Backend Service

Continuous Delivery 2.0

Apr 12, 2023 · Operations

Improving Stability and Throughput in Large‑Scale Software Delivery through Continuous Delivery Practices

The article explains how organizations can boost software delivery stability and throughput by adopting continuous delivery, establishing consistent metrics, reducing manual testing, automating configuration and deployment, and applying incremental, value‑stream‑focused improvements to both technical and cultural processes.

AutomationContinuous DeliveryDevOps

0 likes · 9 min read

Improving Stability and Throughput in Large‑Scale Software Delivery through Continuous Delivery Practices

Laravel Tech Community

Feb 28, 2023 · Operations

Understanding QPS, TPS, Concurrency, Throughput, and Related Performance Metrics

This article explains the definitions and differences of QPS and TPS, describes concurrency and throughput concepts, introduces related metrics such as PV, UV, DAU, MAU, and outlines key considerations for system performance testing and capacity planning.

ConcurrencyPerformance MetricsQPS

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Understanding QPS, TPS, Concurrency, Throughput, and Related Performance Metrics

Code Ape Tech Column

Nov 9, 2022 · Operations

System Performance Optimization: Definitions, Testing, Bottleneck Identification, and Common Strategies

This article explains system performance concepts such as throughput and latency, describes how to design and run performance tests, outlines methods for locating bottlenecks at the OS, code, network, and database levels, and presents practical optimization techniques ranging from algorithmic improvements to I/O and TCP tuning.

Database OptimizationNetwork TuningPerformance

0 likes · 35 min read

System Performance Optimization: Definitions, Testing, Bottleneck Identification, and Common Strategies

Top Architect

Oct 6, 2022 · Operations

Understanding QPS, TPS, RT, Concurrency, Throughput and Optimal Thread Count

The article explains the core performance metrics QPS, TPS, response time (RT), concurrency, and throughput, provides formulas to relate them, demonstrates practical calculations for capacity planning, and discusses how to determine the optimal number of threads for a backend system.

ConcurrencyPerformanceQPS

0 likes · 7 min read

Understanding QPS, TPS, RT, Concurrency, Throughput and Optimal Thread Count

Selected Java Interview Questions

Aug 30, 2022 · Backend Development

Understanding QPS, TPS, RT, Concurrency, and Throughput in Backend Systems

This article explains the key performance metrics of backend systems—including QPS, TPS, response time, concurrency, and throughput—provides their definitions, relationships, practical calculation examples, and guidance on optimal thread counts for achieving balanced performance.

ConcurrencyQPSTPS

0 likes · 7 min read

Understanding QPS, TPS, RT, Concurrency, and Throughput in Backend Systems

OPPO Kernel Craftsman

Jul 1, 2022 · Operations

Linux Kernel Performance Profiling: A Comprehensive Guide to On-CPU and Off-CPU Analysis

This comprehensive guide explains Linux kernel performance profiling—both on‑CPU and off‑CPU—by stressing the need to target the critical 3 % of code, covering throughput, latency and power metrics, scalability laws, flame‑graph visualizations, perf and eBPF tools, lock‑contention analysis, and further reading recommendations.

Flame GraphLinux kernelPerformance Profiling

0 likes · 27 min read

Linux Kernel Performance Profiling: A Comprehensive Guide to On-CPU and Off-CPU Analysis

Top Architect

Oct 30, 2021 · Backend Development

RabbitMQ vs Kafka: Architectural Comparison and Throughput Considerations

This article compares RabbitMQ and Kafka by explaining their architectures, queue consumption and production mechanisms, highlighting the master‑mirror design of RabbitMQ versus Kafka's partitioned approach, and summarizing their throughput characteristics to help engineers choose the appropriate messaging middleware for their needs.

Kafkaarchitecturebackend development

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RabbitMQ vs Kafka: Architectural Comparison and Throughput Considerations

Top Architect

Oct 2, 2021 · Backend Development

RabbitMQ vs Kafka: Architectural Comparison and Selection Guidance

This article compares the architectures of RabbitMQ and Kafka, explaining their queue models, master‑mirror and partition mechanisms, performance trade‑offs, and provides guidance on choosing between them based on throughput requirements and system design considerations.

Kafkaarchitecturebackend

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RabbitMQ vs Kafka: Architectural Comparison and Selection Guidance

Fulu Network R&D Team

Jul 6, 2021 · Operations

Understanding Throughput, Concurrency, and Lock Contention in System Design

Throughput measures the rate at which an application processes tasks, distinct from concurrency, and can be improved by reducing task latency, increasing parallelism, and optimizing lock usage through finer granularity, lower cost, and techniques like buffering, merging, and batch processing to mitigate contention and enhance scalability.

ConcurrencyLocksParallelism

0 likes · 11 min read

Understanding Throughput, Concurrency, and Lock Contention in System Design

FunTester

Aug 23, 2020 · Operations

Analyzing Throughput Errors in JMeter Load Testing

JMeter’s reported throughput can be misleading because it includes local processing time, especially when response validation such as regex extraction adds overhead, leading to significant underestimation of actual server load; the article demonstrates this with experiments and suggests micro‑benchmark corrections to obtain accurate results.

JMeterMicrobenchmarkPerformance Testing

0 likes · 5 min read

Analyzing Throughput Errors in JMeter Load Testing

Top Architect

Jul 11, 2020 · Operations

7 Key Performance Metrics for Application Monitoring and Their Recommended Tools

The article outlines seven essential performance metrics—response time and throughput, average load, error rate, GC pause time, business indicators, uptime, and log size—explaining their significance for application health and recommending popular monitoring tools for each metric.

Garbage CollectionLog ManagementUptime

0 likes · 6 min read

7 Key Performance Metrics for Application Monitoring and Their Recommended Tools