After running continuous recording for a few weeks, storage became the first bottleneck. A single 1080p camera writes tens of GB per day — with a 30-day retention policy, a 1TB硬盘 is mostly consumed. Many community members reported the same issue, and during discussions, the ideas of timelapse and transcoding storage gained the most traction: most of the time the画面 is static, and compressing it with timelapse requires only 5% of the space for the same duration.

The concurrently released MiBeeNvr v0.6.0 brought major features like timelapse, video transcoding, and ONVIF enhancements. Unit tests alone are far from enough — the full workflow must be tested against real camera hardware. To provide reliable test machines for this release, three camera projects were updated on the same day, June 5th — both to supply testing environments for the NVR and to solve some typical embedded development engineering problems along the way.

Less than a week after v0.4.0, another 31 commits were pushed. v0.5.0 is a feature-dense release: full ONVIF protocol support (covering all five major services: Device/Media/PTZ/Imaging/Event), hardware transcoding (H.265 → H.264), and recorder reconnection optimizations. 127 files changed, +24,509 / -730 lines. See the full changelog at GitHub Release Notes. If you haven’t seen the previous versions, check out MiBeeNvr Introduction and v0.4.0 Technical Post. Full ONVIF Protocol Support v0.4.0 already had ONVIF device discovery and stream URL retrieval, but that was just the tip of the ONVIF iceberg. v0.5.0 completes the core services of ONVIF Profile S:

Coming from an operations background, later transitioning to development, the number of projects I maintain keeps growing. Various middleware, databases, monitoring components… each version upgrade is a manual labor: go to the official site to find the download link, compare version numbers, manually download to the internal network, then distribute to each machine. I used to write a bunch of Shell scripts to periodically pull the latest versions to the LAN — functional but not user-friendly: scripts scattered everywhere, adding new software required writing parsing logic by hand, and there was nothing to check when things went wrong.

Previously, MiBeeNvr’s MP4 files only had a video track — playback was silent. v0.4.0 fills this gap with audio recording. It also adds more practical camera health monitoring and auto-recovery. Recordings Now Have Sound Each camera can independently enable audio recording: yaml 1 2 3 4 5 6 cameras: - id: "front-door" name: "Front Door Camera" protocol: "rtsp" encoding: "h264" audio_enabled: true Supported audio formats:

After v0.3.1 shipped, I put in another 196 commits. v0.4.0 is a feature-dense release: audio recording pipeline, multi-layer health monitoring engine, HLS/LL-HLS playback stability optimization, and a major UI redesign. For the full changelog, see GitHub Release Notes. The previous post covered v0.3.x’s multi-protocol streaming and Xiaomi camera support (v0.3.0 Tech Post). If you haven’t read the first post, start with MiBeeNvr Introduction. Audio Recording: From Silent to Sound In the v0.3.x era, recorded MP4 files only had a video track. v0.4.0 introduces a complete audio capture and muxing pipeline, supporting AAC audio from RTSP cameras and G.711 audio from ONVIF/Xiaomi cameras.

A lot of work went into the releases after v0.2.0. v0.3.x brings several major updates: native Xiaomi camera support, recording archiving, multi-protocol streaming architecture (WebRTC/HTTP-FLV/RTMP/SRT/LL-HLS), and a wave of security hardening. The architectural evolution from external dependencies to built-in implementation, from single protocol to full protocol support, was much more曲折 than I expected. The previous post introduced v0.2.0’s 15 new features (v0.2.0 Update). If you haven’t read the first post, start with MiBeeNvr Introduction. v0.3.0 focuses on deep Xiaomi camera integration, and v0.3.1 builds on that with a complete multi-protocol streaming architecture. For the full changelog, see GitHub Release Notes.

The Origin: Compliance Check Hassles Anyone in operations knows there’s no escaping one hurdle for domestic servers: Cybersecurity Level Protection (GB/T 22239-2019, commonly known as “Level Protection 2.0”). Whether you’re Level 3 or Level 2, auditors come asking about these things: Is SSH root login disabled? Are password policies compliant? Is the firewall on? Is SELinux enforcing? Are there expired accounts? What’s the password validity period? Which ports are open? Are there high-risk services running? Are audit logs enabled? How long are they retained? There are plenty of compliance check tools on the market—search GitHub and you’ll find a bunch: Golin, EvaluationTools, Linux-Security-Compliance-Check, etc. But they all share one limitation: Run once, get a report, done. You check compliance today, and someone changes sshd_config tomorrow, turns off the firewall, installs a backdoor service—you’d never know.

Got Xiaomi cameras at home? Want to keep your recordings on your own storage instead of relying on the cloud? As someone with several Xiaomi cameras at home, I always had one frustration: every time I wanted to check the footage from my doorbell camera, I had to log into Xiaomi Cloud, wait for ages while it loaded, and it would often just spin. Plus, cloud storage charges by the day — it adds up over the month. And if you swap cameras, all your old recordings are gone. Pretty frustrating.

From Static to Real-Time The previous article introduced security-collector-exporter v0.1.0 — turning Linux security configuration states into Prometheus metrics. But v0.1.0 is essentially “snapshot-based”: periodically reading /etc, /proc, capturing the static configuration at a single point in time. There’s an area of security operations that snapshots can’t cover: real-time security events. Someone running a reverse shell, a process escalating privileges, an abnormal network connection, someone loading a kernel module — these events happen and pass; you’d never see them at your next scrape.