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JProfiler Visual Studio Code Integration -- The Kotlin Multiplatform Killer Use Case
An airhacks.fm conversation with Ingo Kegel (@IngoKegel) about:
jprofiler Visual Studio Code integration using Kotlin Multiplatform,
migrating Java code to Kotlin common code for cross-platform compatibility,
transpiling to JavaScript for Node.js runtime,
JClassLib bytecode viewer and manipulation library,
Visual Studio Code's Language Server Protocol (LSP),
profiling unit tests and performance regression testing,
Java Flight Recorder (JFR) for production monitoring with custom business events,
cost-driven development in cloud environments,
serverless architecture with AWS Lambda and S3,
performance optimization with parallelism in single-CPU environments,
integrating profiling data with LLMs for automated optimization,
MCP servers for AI agent integration,
Gradle and Maven build system integration,
cooperative window switching between JProfiler and VS Code,
memory profiling and thread analysis,
comparing streams vs for-loops performance,
brokk AI's Swing-based LLM development tool,
context-aware performance analysis,
automated code optimization with AI agents,
business event correlation with low-level JVM metrics,
cost estimation based on cloud API calls,
quarkus for fast startup times in serverless,
performance assertions in System Tests,
multi-monitor development workflow support
Ingo Kegel on twitter: @IngoKegel
View all episodes
By Adam Bien
5
55 ratings
An airhacks.fm conversation with Ingo Kegel (@IngoKegel) about:
jprofiler Visual Studio Code integration using Kotlin Multiplatform,
migrating Java code to Kotlin common code for cross-platform compatibility,
transpiling to JavaScript for Node.js runtime,
JClassLib bytecode viewer and manipulation library,
Visual Studio Code's Language Server Protocol (LSP),
profiling unit tests and performance regression testing,
Java Flight Recorder (JFR) for production monitoring with custom business events,
cost-driven development in cloud environments,
serverless architecture with AWS Lambda and S3,
performance optimization with parallelism in single-CPU environments,
integrating profiling data with LLMs for automated optimization,
MCP servers for AI agent integration,
Gradle and Maven build system integration,
cooperative window switching between JProfiler and VS Code,
memory profiling and thread analysis,
comparing streams vs for-loops performance,
brokk AI's Swing-based LLM development tool,
context-aware performance analysis,
automated code optimization with AI agents,
business event correlation with low-level JVM metrics,
cost estimation based on cloud API calls,
quarkus for fast startup times in serverless,
performance assertions in System Tests,
multi-monitor development workflow support
Ingo Kegel on twitter: @IngoKegel
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