Tiered Compilation in JVM: Understanding C1 vs C2 Compilers for Performance Optimization
Learn how tiered compilation in JVM combines C1 and C2 compilers to balance startup performance and runtime optimization for Java applications
Tutorials under 'JIT Compiler'
Understanding Class Data Sharing (CDS) and AppCDS for Faster JVM Startup and Lower Memory Usage
Learn how Class Data Sharing (CDS) and AppCDS optimize JVM startup, reduce memory footprint, and improve performance in Java applications with real-world use cases
GraalVM JIT Compiler: Next-Generation JVM Performance and Optimization
Explore GraalVM’s JIT compiler for next-generation JVM performance, advanced optimizations, polyglot support, and real-world tuning strategies for Java apps.
JVM Intrinsics and Escape Analysis Explained in Depth for Performance Optimization
Dive deep into JVM intrinsics and escape analysis, how HotSpot JIT optimizes code, reduces GC pressure, and improves Java performance in real-world apps.
JVM Safepoints Explained: Why the JVM Halts Threads and How It Impacts Performance
Understand JVM safepoints, why the JVM halts threads, their role in garbage collection, JIT compilation, and how to optimize safepoint behavior in production systems
Biased Locking, Lightweight Locking, and JVM Synchronization Internals Explained
Learn JVM synchronization internals including biased locking, lightweight locking, and object monitors. Discover performance impacts and best practices in Java apps
GC Tuning Case Study: Optimizing JVM for Low-Latency Trading Systems
Explore a real-world GC tuning case study in low-latency trading systems. Learn how ZGC, Shenandoah, and JVM flags help achieve predictable sub-10ms pauses
Deoptimization in JVM: Understanding When Optimizations Are Rolled Back
Learn JVM deoptimization, why HotSpot rolls back JIT optimizations, how it ensures correctness, and its performance impact in Java applications
Inline Caching in the JVM: Faster Method Dispatch and JIT Optimization
Discover how JVM inline caching accelerates method dispatch, reduces dynamic lookup overhead, and boosts Java application performance with JIT optimizations
JVM Profiling Internals: Stack Sampling and Instrumentation for Performance Optimization
Explore JVM profiling internals with stack sampling and instrumentation. Learn how to detect performance bottlenecks and optimize Java applications in production
Choosing the Right Garbage Collector for Your Application: G1, ZGC, Shenandoah, and Beyond
Learn how to choose the right JVM garbage collector (G1, ZGC, Shenandoah, Parallel) for your application. Compare throughput vs latency tuning with real-world cases
GC Tuning Case Study: Optimizing JVM for High-Throughput Web Applications
Learn GC tuning strategies for high-throughput web applications. Explore G1, Parallel, and ZGC optimization with JVM flags, case studies, and best practices
JVM Internals in Cloud-Native Environments: Optimizing for Docker and Kubernetes
Learn JVM internals in cloud-native environments. Explore GC tuning, memory management, and best practices for Docker and Kubernetes deployments
JVM Memory and Garbage Collection in Microservices Architectures
Learn how JVM memory and GC tuning affect microservices. Explore best practices for heap sizing, GC choice, and performance optimization in cloud-native systems
JVM Performance Tuning Checklist for Enterprise Applications
A complete JVM performance tuning checklist for enterprise apps. Covers GC, heap, JIT, monitoring, flags, and best practices for scalable production systems.
Diagnosing and Fixing OutOfMemoryError in Production
Learn how to diagnose and fix OutOfMemoryError in production Java apps. Covers causes, detection, GC tuning, memory leaks, and best practices for stability
Common Myths About JVM and GC: What Developers Get Wrong
Debunk common myths about JVM and Garbage Collection. Learn the truth about heap, GC tuning, JIT, safepoints, and performance in modern Java versions
Alternatives to the JVM Garbage Collector: Off-Heap Stores and Native Memory
Explore alternatives to JVM Garbage Collection using off-heap stores and native memory for better performance, reduced GC pauses, and optimized workloads