The Tool Desk
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What flush and fsync do in the streaming write path
They are separate operations in the vendor’s description. The streaming helper first flushes the staging file, moving buffered application writes toward the operating system. When the selected durability mode requires it, the helper then calls staging_file.sync_all().await before returning. The vendor cautions that “Flush is not automatically equivalent to stable physical persistence.” See the vendor’s explanation of strict and balanced durability.
The explicit sync is a request to push persistence further down the storage stack; it is not proof that every layer has honored it as expected. The result still depends on the operating system, filesystem, storage device, controller, and hardware behavior. As the vendor puts it, “fsync strengthens the contract, but ‘durable storage’ still ultimately depends on the operating system, filesystem, device, controller, and hardware behavior underneath.”
Where synchronization falls in a normal PUT
The vendor’s documented V1 write sequence places synchronization before the staging file is closed and the object is committed through later filesystem and metadata operations:
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- Create a staging file and stream the payload into it while computing SHA-256.
- Flush the staging file; in strict mode, call
sync_allbefore the streaming helper returns. - Close the staging file, recheck capacity and quota, create the final parent directory, and rename the staged file into its final placement.
- Write object metadata to RocksDB. If that metadata commit fails synchronously, the vendor says the physical file is removed.
This ordering means the explicit sync applies while the payload is still represented by the staging file—not after the final rename and metadata write. The sequence is the vendor’s description of its current implementation, not evidence from independent crash tests covering every possible interruption point. The vendor’s account of the V1 commit pipeline also stresses that “It does not magically turn filesystem + RocksDB into one atomic transaction.”
Strict and balanced compared
| Question | Strict, as described | Balanced, as described |
|---|---|---|
| Explicit synchronization | Calls sync_all after flush when the mode requires it, before the streaming helper returns. |
Skips that explicit sync stage when the mode does not require it. |
| Persistence assumption | Makes a stronger explicit synchronization request before later commit steps. | Relies more on operating-system and filesystem writeback behavior. |
| Performance claim | Synchronous persistence can add latency; no numerical penalty is published in the reviewed sources. | The vendor says throughput can improve; no numerical gain is published. |
| What still matters | Operating system, filesystem, device, controller, and hardware behavior. | The same underlying stack, with different assumptions about when writeback reaches persistent storage. |
| Evidence status | Vendor implementation description; no independent crash-test result or quantified comparison is reported. | Vendor implementation description; no independent crash-test result or quantified comparison is reported. |
These descriptions support a comparison of synchronization behavior, not a universal “safe versus unsafe” ranking. The available sources do not establish that either mode is right for every workload or deployment.
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What staging and commit ordering are intended to protect
Staging keeps an incomplete request separate from normal committed-object visibility. The vendor says an interrupted stream should not appear as an ordinary object returned by GET, multipart parts do not become the final object until multipart completion, and an interrupted replacement is intended to leave the previous committed object intact. Its failure-window discussion distinguishes an orphaned file that consumes disk space from partial data exposed as a committed object. These are documented design intentions, not independent demonstrations of every failure combination.
The filesystem and RocksDB are separate systems, so their operations do not become atomic merely because they are performed in sequence. The vendor says a metadata-first inverse order could leave metadata pointing to missing bytes; its described approach instead uses staging, filesystem rename semantics where supported, metadata checks, and rollback for synchronous metadata failure. That strategy does not eliminate every recovery concern, including orphaned-file cleanup.
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- Storage capacity: Please Select
- Formatted as FAT32 file system
- USB 3.0 Hard drive interface
- Support plug and play
- No external power needed
How to evaluate the modes for a deployment
There are no published Lioran-specific benchmark figures in the reviewed material: no measured strict-versus-balanced throughput or latency delta, and no independently measured durability rate. The vendor’s suggested benchmark record includes the selected mode, filesystem, disk type, object size, concurrency, reverse proxy, network path, CPU, RAM, and software version. Its timing instrumentation separates receive, write, SHA-256, flush, fsync, close, directory creation, rename, metadata, and total durations. Those timings can help identify whether a particular run is network-, disk-, synchronization-, or hashing-bound; they are not a substitute for durability testing.
For evaluation, the vendor proposes testing on disposable systems. These are test cases, not reported results:
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- Storage capacity: Please Select
- Formatted as FAT32 file system
- USB 3.0 Hard drive interface
- Support plug and play
- No external power needed
- Terminate the process during a PUT and during a multipart upload, then restart and compare checksums.
- Exercise disk-full and quota conditions.
- Test host reboot and filesystem remount behavior.
Keep object data and metadata on persistent storage. The vendor’s Docker deployment description notes that a container-only data path is not durable across container removal. A UPS can reduce exposure to external power interruption, but it does not replace synchronization or backups, and the available sources do not establish it as a persistence guarantee.
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