When managing database backups, key pain points on entry-level servers are memory spikes (Out of Memory crashes) and running out of disk space due to temporary dump files.
To validate the efficiency of LunarDump (a zero-disk streaming backup solution), I conducted a benchmark & memory profiling using Memray across a multi-cloud setup based in Jakarta.
🖥️ Test Environment Setup:
- Server A (Database): Tencent Cloud (Jakarta) — Ubuntu 24.04, 2 vCPU, 2 GB RAM, 40 GB SSD
- Server B (LunarDump Engine): Cloudeka (Jakarta) — Ubuntu 24.04, 1 vCPU, 1 GB RAM, 20 GB SSD
- Destina tion Storage: Google Cloud Storage (GCS) Bucket
📊 Benchmark Highlights:
- Total Data Processed: ~8 GB (MySQL Database Stream)
- Execution Duration: 1 Hour 1 Minute (Continuous Cross-Cloud Streaming)
- Peak Memory Usage (Heap): 119.1 MB (~1.4% of total dataset size)
- Resident Set Size (RSS): Stable at ~180 MB
- Local Disk Footprint: 0 Bytes (Data streamed from Server A, encrypted with AES-256-GCM in Server B’s RAM, and uploaded directly to GCS on-the-fly)
- Server B CPU Load: Averaged 4% – 8%
💡 Key Takeaways:
Through Flamegraph visualizations and Resident Set Size Over Time analysis, LunarDump demonstrated Zero Memory Leak. The flat memory footprint confirms that garbage collection and chunk-based buffer recycling function flawlessly—keeping resource consumption predictable even on a low-spec 1 vCPU/ 1 GB RAM node.
Github : lunardump
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