JDK 17 Performance Tuning Expert Needed

@tangramua

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@rohitpatidar001

Hi, I’m interested in helping with the JDK 17 performance tuning and middleware optimization work. I have 11+ years of professional Java development experience, including Java 17/21, Spring Boot, microservices, Kafka, database/API performance optimization, concurrency, production troubleshooting and enterprise application support. I can help with: * **JDK 17/JVM performance analysis** — GC behavior, heap/memory usage, allocation patterns and JVM configuration * **Thread and concurrency analysis** — thread contention, blocking, thread pools and synchronization issues * **Kafka performance** — producer/consumer configuration, batching, throughput, partitioning and consumer lag * **Middleware troubleshooting** across Kafka and related distributed components * CPU, memory, I/O and application-level bottleneck investigation on Linux/Ubuntu * Profiling and analysis using appropriate JVM/application diagnostic tools * Compatibility and configuration adjustments across existing Java/middleware environments * Production-safe performance changes with before/after measurements and documentation My approach would be measurement-driven: first establish a baseline, analyze JVM/GC/thread and middleware metrics, identify the actual bottleneck, apply targeted changes, and then validate the improvement through comparable load/performance tests.

@AITSoft

I can help turn this JDK 17 environment into a faster, calmer, more predictable system. I’ll investigate JVM internals and JDK 17 source behavior, then tune Garbage Collection, Memory Management, and Thread Performance using evidence from production-style workloads rather than guesswork. I’ll also trace compatibility boundaries across Apache Kafka, RabbitMQ, and Zookeeper, checking middleware interactions, queue pressure, latency spikes, and resource contention. Where the JVM symptoms point deeper, I’ll use Linux and kernel-level troubleshooting to isolate scheduling, I/O, memory, or networking issues. Java profiling, logs, metrics, thread dumps, GC analysis, and focused stress tests will help validate every improvement. You’ll receive clear findings, prioritized tuning recommendations, safe configuration changes, and before/after performance evidence, with rollback guidance where appropriate. Which workload is currently the biggest troublemaker: GC pauses, middleware latency, thread contention, or kernel-level resource pressure? Let’s make the JVM and its middleware teammates work together smoothly!

@kumarashish99

Hi, I’m a DevOps/Cloud engineer with strong experience in Linux, Java-based workloads, AWS, Docker, Kubernetes, and production performance troubleshooting. I can help investigate JVM performance issues around memory usage, garbage collection, thread behavior, and resource contention. I can analyze JDK 17 runtime behavior alongside Kafka, RabbitMQ, and Zookeeper to identify bottlenecks across the application, middleware, OS, and infrastructure layers. My approach would be evidence-driven using JVM metrics, GC logs, thread dumps, CPU/memory profiling, system metrics, and relevant kernel-level information before making tuning changes. I can also review compatibility issues between the JVM and existing middleware stack and provide practical configuration/code-level recommendations focused on measurable performance improvements. I’m available to review the current JVM metrics, logs, and workload characteristics and start troubleshooting immediately.

@devendrathakur12

Hi, I’m a Principal Software Engineer with 20+ years in backend performance and data-heavy systems. I have gone through your specific requirement for JVM and middleware tuning. I would use JDK 17 JFR and async-profiler before changing GC settings, because heap symptoms can hide thread or allocation hot spots. I will profile GC pauses and allocation pressure first, then trace thread contention through Kafka and RabbitMQ interactions. For kernel issues, I can correlate JVM behaviour with Linux scheduler and memory signals, so tuning is based on evidence. And I will document each change against the measured bottleneck, at least that is where I would start. Relevant backend architecture and code samples I can send privately. Which JDK 17 build and GC are running in production today? What Kafka, RabbitMQ and Zookeeper versions are involved, and where do you currently see the largest latency spikes? Do you have JFR recordings, GC logs or Linux profiling data from the affected workloads? Free for a quick call? Or answer those three and I will map out the first profiling pass. Dev Singh

@MuhammadUzair16

Hi, I am a software engineer with over 16 years of experience in Java systems, JVM internals, performance engineering, and production middleware. I have extensive experience diagnosing GC pauses, memory pressure, allocation issues, thread contention, latency spikes, and throughput bottlenecks in JDK 17 environments involving Kafka, RabbitMQ, and ZooKeeper. I can profile the current workload using JFR, GC logs, thread and heap analysis, and appropriate Linux/kernel-level tools, then tune the JVM and middleware configuration without compromising stability or compatibility. I can also investigate scheduler, I/O, networking, container limits, and native-memory behavior when the bottleneck sits below the JVM. My focus will be measurable improvements backed by before-and-after benchmarks and clear recommendations. Is the system running on bare metal, VMs, Kubernetes, or another container platform? Also, which GC is currently configured, and what are the main symptoms and performance targets? Please contact me to discuss details.

@hayteekeys

HI, KINDLY READ THROUGH MY PROPOSAL I will deliver targeted performance improvements for your JDK 17-based systems by tuning Garbage Collection, memory and thread behaviour, ensuring seamless compatibility with Kafka, RabbitMQ and Zookeeper, and resolving any kernel-level issues that affect reliability. MY APPROACH ✅ Deep analysis of JDK 17 GC, memory and thread performance ✅ Compatibility adaptation for Kafka, RabbitMQ and Zookeeper ✅ Kernel-level troubleshooting of underlying bottlenecks ✅ Optimisation of complex middleware interactions ✅ Clear, measurable before/after performance results DELIVERABLES - Tuned JVM configuration and performance report - Compatibility and integration recommendations - Kernel-level findings and fixes - Documentation of all changes and monitoring guidance QUESTIONS 1. Current JDK 17 version, GC algorithm in use and main performance symptoms? 2. Specific Kafka / RabbitMQ / Zookeeper versions and deployment topology? 3. Access method for production or staging environments and any existing monitoring data? Ready to start as soon as current JVM flags, performance metrics and middleware versions are shared.

@XRProConnect

Hi, Aashiq (Ash) here from Cape Town, South Africa. This project instantly caught my eye, so I had to reach out. I see you are looking for a specialist in JDK 17 performance tuning, particularly in areas like Garbage Collection and Memory Management. Your focus on ensuring seamless integration with middleware tech like Apache Kafka and RabbitMQ is clear. I've spent years helping businesses optimize their Java applications, focusing on performance and reliability. My experience includes extensive work with JDK 17, where I've successfully improved system performance and resolved complex middleware interactions. I would be happy to share samples of my successful projects upon request. Based on what you mentioned, here is how we would approach the project: - Conduct a thorough analysis of your current performance metrics - Implement targeted performance tuning strategies for JDK 17 - Ensure compatibility with existing systems through careful adaptation You can count on clear communication throughout the process, delivering a seamless, user-focused solution optimized for performance. Best Regards, Aashiq

@pinesucceed01

Hello, Drawing from my extensive knowledge of Java and 16 years of software development experience, I assure you that I am more than capable of handling the task at hand. My in-depth understanding of JDK 17 and its performance tuning, including experience in working with kernel-level debugging and troubleshooting, equips me with the necessary skills to optimize garbage collection, memory management, and thread performance. Additionally, I have a strong background in middleware technologies such as Apache Kafka, RabbitMQ, and Zookeeper which facilitates an understanding of complex middleware interactions that will contribute to improved performance. What sets me apart is not only my technical expertise but also my dedication to ensuring efficient and reliable performance improvements. I believe in tailoring solutions to meet specific client needs and providing high-quality scalable solutions. This approach aligns perfectly with your project requirements for compatibility adaptation and seamless integration - areas where my proficiencies will prove invaluable. My highest goal is always delivering guaranteed value to clients like you. Thanks!

@golamrabbi01

Hello, You’re dealing with a performance problem that likely requires looking beyond application-level tuning—JVM behavior, thread contention, memory/GC patterns, Linux/kernel behavior, and middleware interactions all need to be analyzed together. My background is in backend engineering, Linux, distributed systems, Docker/Kubernetes, cloud infrastructure, CI/CD, and performance-oriented troubleshooting. I’m comfortable working across application, JVM, infrastructure, and middleware layers. A few questions: - What JDK 17 distribution/version and JVM are you currently running? - Which Kafka, RabbitMQ, and ZooKeeper versions are involved? - Do you already have JVM GC logs, thread dumps, heap information, or system-level metrics from the affected environment? If you can share the current architecture and performance symptoms, I can first help identify where the bottleneck is before proposing tuning changes. Kind regards, Golamrabbi Azad

@farrukhdeveloper

I can help you diagnose and optimize JVM and middleware performance across the full application stack. I bring 18 years of software engineering and architecture experience, including Java/Spring, Kafka-based systems, Linux, Docker/Kubernetes, distributed systems, and production troubleshooting. My approach would cover JDK 17 GC tuning, heap and allocation analysis, thread contention, deadlocks, executor sizing, CPU saturation, and memory leaks using GC logs, JFR, heap dumps, thread dumps, and Native Memory Tracking. I can also analyze Kafka producer/consumer performance, partitioning, batching, lag, broker interaction, RabbitMQ queue/channel behavior, Zookeeper coordination issues, and Linux-level CPU, memory, disk I/O, networking, scheduler, and file-descriptor constraints. I prefer evidence-driven tuning rather than blindly changing JVM flags: establish a baseline, identify the actual bottleneck, apply targeted changes, and compare before/after results. I can also document the recommended configuration, risks, compatibility changes, and rollout plan for production.

@bojans9

Hello, I can help investigate and optimize Java/JDK 17 applications where the performance issues can be isolated through profiling, runtime metrics, logs, and controlled testing. I have 10+ years of software development experience across backend systems, APIs, Linux, Docker, cloud infrastructure, databases, and performance-focused troubleshooting. I can analyze JVM memory behavior, GC activity, thread usage, application bottlenecks, and middleware interactions, then document measurable findings and recommended changes. I can also investigate Linux/Ubuntu-level issues affecting application performance and validate compatibility after changes. My background is broader software/backend engineering rather than claiming deep specialization in JDK 17 internals, Kafka, RabbitMQ, or ZooKeeper, so I would first review the environment, metrics, logs, and reproduction case before proposing specific tuning changes. Rate: $25/hour

@amadorjay

Hi there, The hard part isn't just understanding JVM internals; it's ensuring that performance tuning aligns with your existing system architecture. Achieving optimal Garbage Collection and Memory Management requires precise adjustments, especially with JDK 17. Kernel-level troubleshooting is crucial, as underlying issues can significantly impact performance if not addressed. Can you provide more details on the specific integration challenges you're facing with your current middleware setup? Thank you.

@rishi9343

With a comprehensive understanding of both Java development and backend optimization, I am uniquely equipped to tackle your JDK 17 performance tuning project. My eight years of experience in database optimization have honed my skills in addressing complex middleware interactions and analyzing middleware technologies like Apache Kafka, RabbitMQ, and Zookeeper - all mainstays of your project. I have extensive knowledge of JVM internals that is vital for identifying and rectifying performance bottlenecks at their source. My proficiency with kernel-level debugging and troubleshooting will also prove crucial in ensuring the seamless integration of JDK 17 with your existing systems. You need someone who can adapt the compatibility of your systems and diagnose underlying issues impacting performance, and I have the qualifications to fulfill this. Choosing me for this project means not just gaining a skilled freelancer but a dedicated partner committed to providing efficient and reliable results. Let's make your JDK 17 reliant systems even more powerful together!

@diegovisiso

Hi, Diego Vinicius here from Brazil. I understand the need for a JDK 17 performance tuning expert with a deep understanding of JVM internals and middleware technologies like Apache Kafka, RabbitMQ, and Zookeeper. The main challenge lies in optimizing Garbage Collection, Memory Management, and Thread Performance while ensuring seamless integration with existing systems and troubleshooting kernel-level issues affecting performance. My approach involves a thorough analysis of JDK 17 source code, implementing targeted optimizations, and prioritizing reliability and efficiency in all aspects of performance tuning. Clarifying Questions: - How critical is the need for real-time performance improvements? - Are there any specific performance benchmarks or goals to achieve? - Can you provide more details on the existing middleware architecture? Let's discuss how we can enhance your system's performance effectively.

@serdarp4

Hi, Serdar here from The Colony⚡ The thing that separates real JVM performance work from flag-guessing is measuring before touching anything, and it's where I'd start. GC pauses, memory pressure and thread contention constantly masquerade as each other — a system that looks GC-bound is often actually blocking on lock contention or IO, and swapping GC flags at it just moves the symptom. So the first work is establishing the actual bottleneck with real evidence: GC logs analysed properly, allocation profiling, async-profiler flame graphs for CPU and lock contention, and JFR recordings under production-like load. Only then does tuning target the real cause. One honest note on "kernel-level": most issues that present as kernel-level in a JVM middleware stack turn out to be GC, syscall or IO behaviour that looks kernel-deep but is resolved in the JVM or the OS tuning layer. I'll go as deep as the evidence genuinely requires — with strace, perf and eBPF if it's truly there — rather than assume the kernel is the culprit before the data says so. I've done production JVM and Kafka/RabbitMQ performance tuning. Two things worth deciding early: 1. Which GC is running now, and what's the actual symptom? 2. Latency-critical or throughput-critical? Thanks, Serdar.

@indreshpnk

Hello, I understand you need a specialist to optimize JVM/JDK 17 performance across GC, memory, threads, and middleware such as Kafka, RabbitMQ, and Zookeeper. The goal is to identify bottlenecks and deliver measurable, reliable performance improvements. Here’s what I can provide: Analyze JVM behavior using GC logs, heap/thread diagnostics, profiling, and JDK 17 performance tuning techniques. Troubleshoot Kafka, RabbitMQ, and Zookeeper interactions, including latency, throughput, resource utilization, and configuration issues. Investigate Linux/Ubuntu system-level bottlenecks involving CPU, memory, I/O, networking, and kernel behavior. I bring over 4+ years of experience in Java, C++, Python, Linux, REST APIs, databases, Docker, AWS, and backend development, with a strong focus on reliable and scalable systems. I’ve worked on backend applications, APIs, cloud environments, and performance-focused troubleshooting. Just to clarify a few things: Can you share the current JVM metrics, GC logs, and JDK 17 configuration? Which component is currently showing the main bottleneck—JVM, Kafka, RabbitMQ, Zookeeper, or the underlying Linux system? Please come to the chat box to discuss more about your project. Best regards Indresh Kushwaha

@bohdan38

Hi, I’m Bohdan, an AI & Full-Stack Developer with 6+ years of experience, prepared to investigate JDK 17 performance across JVM internals, garbage collection, memory behavior, threads, and middleware interactions. You need a specialist who can identify the actual causes of latency, contention, resource pressure, or compatibility problems across Java services, Kafka, RabbitMQ, Zookeeper, and the underlying Linux environment. I can approach this through evidence-based profiling rather than guesswork, correlating JVM metrics, GC logs, thread dumps, heap behavior, broker telemetry, and kernel-level diagnostics. I will establish a baseline, isolate bottlenecks, review JDK 17 runtime and configuration choices, validate middleware settings, and recommend targeted changes with measurable before-and-after results. The work will include careful compatibility checks, reproducible testing, error analysis, clear documentation, and secure production-minded implementation practices. A focused diagnostic and optimization milestone can be delivered within one week, with prioritized findings and validated tuning recommendations. Could you share the current JDK 17 deployment details, JVM flags, GC logs, and the specific performance symptoms or workload peaks you have observed? Best regards, Bohdan

@elijahhmonreal

Hi there, I'm a Java Performance Engineer with 12+ years of deep expertise in JVM internals and JDK optimization. Your need for JDK 17 performance tuning across Garbage Collection, Memory Management, and Thread Performance aligns perfectly with my specialization. I've spent years optimizing complex systems involving Apache Kafka, RabbitMQ, and Zookeeper, I understand the middleware interactions that impact your performance bottlenecks. I'll conduct kernel-level analysis to identify underlying system constraints, then deliver targeted GC tuning, memory optimization, and thread pool configurations that integrate seamlessly with your existing infrastructure. My approach combines JDK 17 source code analysis with real-world profiling to ensure your systems achieve peak efficiency and reliability. Let me know if my profile looks interesting, and we can set up a time to talk. Best regards, Elijah M