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我正在研究针对网络不可靠（偏远站点、工业环境、车队等）的边缘/网关遥测模式，这种场景需要离线缓冲、磁盘空间限制以及在恢复连接后重放数据。向正在生产环境中运行此类系统的朋友们提问：你们目前使用什么方案？（MQTT 代理 + ??，Kafka/Redpanda/NATS，Redis Streams，自定义日志文件，嵌入式数据库等）在网络中断期间，你们在哪里进行缓冲：仅追加日志、SQLite/RocksDB、磁盘队列，还是其他方式？当磁盘空间接近满时，你们如何处理反压？（丢弃策略、压缩、采样、优先级）你们最害怕的故障是什么：数据损坏、重放风暴、重复数据、“卡住”的消费者偏移量、磁盘已满、时钟偏差？你们实际需要的保证是什么：零丢失 vs “尽力而为”（你们的界限在哪里）？网关上最重要的指标/告警是什么？（队列深度、重放速率、最旧事件时间、fsync 延迟、磁盘使用率等）我很想了解哪些方案有效，哪些会出问题，以及你们希望现有工具在哪些方面做得更好。

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I’m researching patterns for edge / gateway telemetry where the network is unreliable (remote sites, industrial, fleets, etc.) and you need offline buffering + bounded disk + replay once connectivity returns.Questions for folks running this in production:What do you use today? (MQTT broker + ??, Kafka/Redpanda/NATS, Redis Streams, custom log files, embedded DB, etc.)Where do you buffer during outages: append-only log, SQLite/RocksDB, queue-on-disk, something else?How do you handle backpressure when disk is near full? (drop policy, compression, sampling, prioritization)What’s your failure nightmare: corruption, replay storms, duplicates, “stuck” consumer offsets, disk-full, clock skew?What guarantees do you actually need: zero-loss vs “best effort” (and where do you draw that line)?What metrics/alerts matter most on gateways? (queue depth, replay rate, oldest event age, fsync latency, disk usage, etc.)I’d love to learn what works, what breaks, and what you wish existing tools did better.

Ask HN：你们如何在边缘端实现存储转发遥测？