Lioran S3’s V1 Pre-Alpha documentation describes two durability modes, a staged object-write design, and separate controls for bucket quotas and host disk space. These are vendor-described behaviors, not independently verified guarantees: Lioran identifies the release as a single-node pre-alpha system, and the published material reports no crash-test results or strict-versus-balanced benchmarks.
What strict and balanced durability modes change
Lioran’s durability article, published October 1, 2026, describes the modes in terms of when writes are synchronously persisted. The distinction is a stated tradeoff; the article does not provide measured throughput figures or establish that either mode survives every hardware, filesystem, or power failure.
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| Mode | Vendor-described behavior | Practical implication |
|---|---|---|
strict |
Uses explicit flush and sync boundaries before storage metadata is treated as durable. | Provides a more conservative persistence path in the documented design, but is not an independently tested guarantee against all failures. |
balanced |
Uses less per-write synchronous persistence and relies more on operating-system and filesystem writeback. | The vendor says this can improve throughput while changing assumptions about what survives sudden power loss; no quantitative comparison is published. |
The article’s conceptual strict-mode sequence is: receive bytes, write a staged file, flush, call fsync, commit metadata, promote the object, then acknowledge success. Treat this as the documented model, not proof that every possible interruption point has been tested.
How staged writes, multipart uploads, and replacements are meant to behave
The vendor describes a separation between work in progress and committed objects. Temporary writes should not appear as completed objects through normal object APIs. Multipart uploads may have stored parts without a final assembled object; completion is described as the transition to committed object state.
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For a replacement, the stated design goal is to preserve the prior committed object if the new write is interrupted. A PUT walkthrough excerpt also says the server checks host free-space guardrails before receiving data, uses overwrite-aware quota projections, creates separate object and staging identifiers, and streams bytes into staging. The excerpt does not establish further commit ordering. These descriptions explain intended behavior, but do not demonstrate that every crash window passes testing.
Why host free space and bucket quotas are separate controls
A bucket quota limits logical consumption by a bucket or tenant. A host free-space threshold protects physical disk headroom for the machine and its other workloads. One does not imply the other: a bucket can have quota remaining while the host is nearly out of disk, or a host can have free space while a bucket has reached its quota.
| Control | Scope | What it is intended to limit |
|---|---|---|
| Bucket quota | Logical bucket or tenant | How much object storage that bucket or tenant may consume. |
BASTION_MIN_FREE_SPACE_BYTES |
Host filesystem | How little physical free space may remain before the host-level guardrail applies. |
| Optional percentage threshold | Host filesystem | A percentage-based minimum-free-space guardrail; the article does not give a universal value. |
The durability article gives BASTION_MIN_FREE_SPACE_BYTES=536870912, equal to 512 MiB, as an example configuration—not a universal safe setting. Lioran says to size headroom for the actual disk and neighboring workloads. The PUT walkthrough excerpt describes an early projected quota check followed by an exact check once the actual bytes are known; because only the excerpt is available, it supports those checks but not additional implementation claims.
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What integrity checks can—and cannot—do
Lioran says its pipeline tracks integrity metadata such as SHA-256 and lists upload verification, corruption detection, download validation, and ETag or integrity identifiers as uses. These checks can help detect or verify content changes. They do not provide another copy of lost data: the vendor explicitly cautions that checksums are not a substitute for backups or replication.
A separate physical backup destination, such as an external hard drive, is one possible way to keep a copy outside the object store. The cited materials do not identify or test a particular drive, interface, capacity, or backup procedure.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Shutdown behavior and a practical validation plan
The vendor says graceful shutdown drains active requests before metadata stores close, while warning that graceful shutdown does not address uncontrolled termination. Its article suggests validation work; it does not report that these tests have been completed or passed.
- Start with controlled conditions. Pin the software version for reproducibility and use
strictmode while evaluating persistence behavior, as the vendor recommends. - Exercise writes and interruptions. Test PUT and multipart operations during termination, including interrupted multipart uploads, then inspect whether incomplete work remains out of committed object state and whether orphan cleanup behaves as expected.
- Check reads and recovery paths. Evaluate GET during shutdown, restart metadata and the proxy, reboot the host, and remount the filesystem. Compare content checksums across the relevant steps.
- Probe limits safely. Test quota boundaries and disk-full behavior only in disposable environments; monitor memory during large streams.
- Repeat rather than infer. Repeat restart tests and record outcomes for the exact version and configuration in use. A successful run does not establish behavior for every failure mode.
Pre-alpha scope and reliability limits
Lioran’s product overview, published October 1, 2026, describes V1 Pre-Alpha as a self-hosted Rust object-storage server focused on a single-node engine. It says RocksDB stores metadata while object payloads reside on the filesystem, and that the current server does not yet expose a drop-in AWS S3 compatibility layer. Clustering and replication are described as roadmap items, not current capabilities. The overview warns that APIs, storage formats, protocol details, SDK behavior, and operational assumptions may change before stable releases.
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The available vendor materials do not publish independent crash-test outcomes, a reliability statistic, or measured strict-versus-balanced performance results. Readers evaluating the system should treat the write lifecycle, persistence behavior, and guardrails as documented design claims to validate against their own workloads—not as evidence of a tested production durability contract.
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