Flusso Release 0.0.2
🚀 Release Summary
Version 0.0.2
of Flusso introduces a range of optimizations, improved error handling, and configuration updates, along with streamlined deployment through Helm and Docker. This release enhances performance, reduces warnings, and facilitates deployment via automated CI/CD configurations.
✨ New Features and Enhancements
-
Build Optimization:
- Enabled Link-Time Optimization (LTO) to reduce binary size and improve performance in
Release
builds, as suggested by zamazan4ik. This configuration change improves efficiency and provides a smaller binary size. - Established groundwork for future support of Profile-Guided Optimization (PGO) and post-compilation optimization using LLVM BOLT for additional performance gains.
- Enabled Link-Time Optimization (LTO) to reduce binary size and improve performance in
-
Docker Image Versioning and Management:
- Implemented incremental Docker image versioning (e.g.,
0.0.2
,0.0.36
) for each release, removing the need for thelatest
tag. - Enhanced deployment integration with
Helm
, allowing image version specification with the--set image.tag
option.
- Implemented incremental Docker image versioning (e.g.,
-
Expanded Documentation:
- Added detailed documentation for modules, including Kubernetes ingress event handling, load balancing, and HTTP proxy server components, offering greater clarity for each aspect of the project.
🛠️ Bug Fixes
-
Compilation Warning Resolution:
- Resolved multiple warnings related to
unused imports
,dead code
, andunused Result
. - Adjusted type compatibility between
reqwest
andactix-web
for HTTP headers and status codes.
- Resolved multiple warnings related to
-
Enhanced Error Handling:
- Improved error handling in async operations, particularly in background tasks (
tokio::spawn
) and event listeners (EventListener
), ensuring more stable execution.
- Improved error handling in async operations, particularly in background tasks (
🙏 Acknowledgments
Special thanks to @zamazan4ik for recommending the use of Link-Time Optimization (LTO) in Cargo.toml
and suggesting Profile-Guided Optimization (PGO) as a future enhancement. These insights have helped improve Flusso's performance and guided us toward achieving a more efficient build configuration.