Flussonic Release Notes Full ^new^ Site

The following table provides a detailed technical breakdown of the notable changes for key releases.

Verify that active hardware transcoder pipelines are operating with low CPU/GPU usage percentages.

Flussonic Media Server Document Version: 24.12 (summary of major changes from v20 to v24) Date: April 12, 2026 flussonic release notes full

Optimized the interleaved RTSP-over-TCP driver to handle unstable, low-cost IP security cameras without dropping sessions. 3. Hardware Transcoding and Codec Advancements

updates its video streaming software monthly to improve performance, stability, and protocol support. This document tracks the major features, optimizations, and breaking changes across recent Flussonic versions, helping video engineers, IPTV operators, and OTT platforms manage their upgrade paths. 🛠️ Flussonic v24 (2024 Major Releases) The following table provides a detailed technical breakdown

: Support for H.265 (HEVC) in browsers via fragmented MP4, reducing bandwidth requirements without sacrificing quality. 2. Flussonic Watcher: Surveillance and Analytics

curl http://localhost:8080/docs/en/changelog/ 🛠️ Flussonic v24 (2024 Major Releases) : Support

(flussonic.com/login) → Downloads → select version → "View Changelog".

for monitoring conditional access systems and optimized Docker images with layered builds for faster deployment. Version 26.01 (January 2026) : Major platform overhaul integrating NMOS/ST-2110 (uncompressed video over IP), low-latency LL-HLS playback , and vehicle analytics (color/model identification). 2025: Stability & Metrics Version 25.11 (November 2025) : A breakthrough in observability, adding over 40 real-time metrics per stream and support for NTSC frame rates in the transcoder. Version 25.08 (August 2025) : Focused on ad-insertion (SCTE-35)

But software is never finished. A flurry of minor releases followed Archive, each a micro-story. Some entries were stubbornly practical: "Fix: corrected timestamp skew when ingesting RTMP from certain phone models." Others were invitations: "Preview: experimental ML-based quality estimation—tell us if it helps your ops."