CRaC is an OpenJDK project developed by Azul to solve the problem of “slow” startup times of the JVM in a microservice environment.
AsyncGetStackTrace: A better Stack Trace API for the JVM
An introduction into GetStackTrace, AsyncGetCallTrace, and the history and specification of AsyncGetStackTrace.
How Does Kafka Perform When You Need Low Latency?
Kafka benchmarks aim to discuss low latency characteristics of Kafka. Instead, they appear to be configured for throughput rather than low latency.
Writing a Profiler from Scratch: The Profiling Loop
How do profilers like async-profiler work? How to write your own? This is the second part, covering wall-clock profiling.
Why Your Choice of Java Virtual Machine (JVM) Matters More Than Ever
Learn why when you use hyper-optimized Java runtimes instead of vanilla OpenJDK you do less tuning and debugging!
How to Reduce Cloud Cost by 99% for EDA Kafka Applications
About 400x more instances can be run on the same hardware with Chronicle Queue for specific latency-sensitive EDA applications.
How to Leverage Method Chaining to Add Smart Message Routing
Learn how to use method chaining to add routing information to serialised data structures in a lightweight fashion!
Writing a Profiler from Scratch: Introduction
How do profilers like async-profiler work? How to write your own? This series tries to write a tiny sampling-based profiler from scratch!
Azul Provides the CRaC in AWS SnapStart Builds
Now, with a major Cloud platform providing built-in support for the CRaC API, it’s truly off to the races for CRaC.
Web resource caching: Server-side
Learn how the most challenging issue with server-side caching is the configuration, such as what to cache and for how long.
Web resource caching: Client-side
Learn about several alternatives to cache web resources: Expiry and Cache-Control, Last-Modified and ETag, and the Cache API and web workers.