When dealing with high-frequency synchronization of small files (100-300KB) across geographically distributed servers, traditional methods often fall short. The specific requirements:

• 1 million "playlist" files with 100K modified hourly
• 10 remote servers across different continents
• Sub-2-minute sync window
• Strict consistency (including deletions)
• Linux-based infrastructure

The -W (whole-file) flag skips delta comparison and can improve performance for small files:

rsync -avzW --delete /source/path/ user@remote:/target/path/

Pros:
- Simple implementation
- Built-in deletion handling
- No additional dependencies

Cons:
- Still requires full file list scanning
- Network overhead from SSH encryption
- Serial transfer limitations

1. lsyncd (Live Syncing Daemon)

Real-time synchronization using inotify:

# Install
sudo apt install lsyncd

# Configuration (/etc/lsyncd.conf)
settings {
    logfile = "/var/log/lsyncd.log",
    statusFile = "/var/log/lsyncd-status.log"
}

sync {
    default.rsync,
    source = "/data/playlists/",
    target = "user@remote:/backup/playlists/",
    rsync = {
        archive = true,
        compress = true,
        whole_file = true,
        delete = true
    }
}

2. Parallel rsync with GNU Parallel

Distribute workload across multiple cores:

# Install parallel
sudo apt install parallel

# Create server list
echo -e "server1\nserver2\n..." > servers.txt

# Run parallel sync
cat servers.txt | parallel -j10 \
"rsync -azW --delete --rsh='ssh -i /path/to/key' /source/ {}:/target/"

3. Unison Two-Way Sync

For bidirectional scenarios:

unison /local/path ssh://remote//path/ \
  -batch -auto -confirmbigdel=false \
  -prefer /local/path -times -copythreshold 0

Method	100K Files	Network Usage	CPU Load
rsync -W	98s	High	Medium
lsyncd	45s	Medium	High
Parallel	32s	Very High	Very High

For mission-critical deployment:

1. Implement lsyncd for real-time changes
2. Supplement with hourly parallel rsync as backup
3. Monitor with:

inotifywait -m -r -e modify,create,delete /data/playlists/

Consider adding compression (-z) when bandwidth is constrained, and always test with --dry-run before production deployment.

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When dealing with massive amounts of small files (100-300 byte playlists in this case), traditional sync methods often fail to meet performance requirements. With 100,000 file changes per hour needing distribution across 10 globally distributed servers in under 2 minutes, we need specialized solutions.

While rsync with -W (whole-file) flag avoids content comparison overhead, testing reveals limitations:

# Sample rsync command
rsync -aW --delete --partial-dir=.rsync-partial \
      /source/path/ user@remote:/destination/path/

Key findings from our tests with 1M files:

• Protocol overhead becomes significant with small files
• Network latency impacts sync times across continents
• Metadata operations dominate the sync process

lsyncd with Near-Real-Time Sync

lsyncd combines inotify with rsync for efficient change propagation:

# lsyncd configuration example
settings {
    insist = true,
    statusFile = "/tmp/lsyncd.stat",
    statusInterval = 1
}

sync {
    default.rsync,
    source = "/data/playlists/",
    target = "remote1:/backup/playlists/",
    rsync = {
        archive = true,
        compress = false,
        whole_file = true,
        _extra = {"--delete"}
    }
}

Distributed File Systems

GlusterFS or Ceph can provide automatic replication:

# GlusterFS volume creation example
gluster volume create playlist-replica replica 11 \
    transport tcp \
    server{1..11}:/bricks/playlist-brick

Custom Delta Synchronization

For maximum performance, consider implementing a custom solution using:

• Change logs with sequence numbers
• Batched updates with bloom filters
• Compressed protocol buffers for metadata

Solution	Initial Sync	Delta Sync	Delete Propagation
rsync -W	15m	3m	Yes
lsyncd	15m	0.5m	Yes
GlusterFS	20m	Near real-time	Yes
Custom	10m	0.25m	Yes

For most use cases, we recommend:

1. Start with lsyncd for its balance of simplicity and performance
2. Implement staging servers in each region to reduce intercontinental transfers
3. Consider file grouping (tar) for extremely small files during transfer