Presentation: The Rust High Performance Talk You Did Not Expect
📰 InfoQ AI/ML
Learn how Rust's performance capabilities and compile-time safety can improve delivery velocity and reduce engineering overhead in high-performance caching services
Action Steps
- Migrate a high-performance caching service from Kotlin to Rust to compare performance
- Use the Rust borrow checker to identify and fix potential memory safety issues
- Apply Criterion and flamegraphs to optimize concurrent code and improve performance
- Configure Rust's compile-time safety features to shorten the developer feedback loop
- Test and profile Rust code to identify areas for optimization and improvement
Who Needs to Know This
Software engineers and developers on a team can benefit from understanding how Rust can improve performance and safety in their applications, while managers can appreciate the impact on delivery velocity and overhead
Key Insight
💡 Rust's compile-time safety and performance capabilities can significantly improve delivery velocity and reduce engineering overhead in high-performance applications
Share This
🚀 Improve delivery velocity and reduce overhead with Rust's high-performance capabilities and compile-time safety! 💻
Key Takeaways
Learn how Rust's performance capabilities and compile-time safety can improve delivery velocity and reduce engineering overhead in high-performance caching services
Full Article
Ruth Linehan explains how migrating high-performance caching services from Kotlin to Rust shattered internal preconceptions around delivery velocity and engineering overhead. She discusses the ergonomics of the Rust borrow checker, shares how compile-time safety shortens the developer feedback loop, and profiles how tools like Criterion and flamegraphs optimize concurrent code
DeepCamp AI