Tracing Dependencies Before a Storage Retirement

In any production infrastructure, retiring a storage volume is a high-risk operation. Before unmounting a filesystem, every dependency must be identified and either migrated or eliminated. Message [msg 6089] captures a precise moment in this process: the assistant runs a targeted reconnaissance command to discover which running services reference the /data mount point on an LXC container serving large language models via SGLang.

The Message

The assistant executes a single bash command over SSH:

ssh root@10.1.230.174 'grep -r "/data" /etc/systemd/system/*.service 2>/dev/null; echo "==="; cat /etc/systemd/system/sglang-qwen.service | grep /data; echo "==="; cat /etc/systemd/system/sglang-kimi.service 2>/dev/null | grep /data'

The output reveals two critical dependencies:

/etc/systemd/system/sglang-kimi.service:  --speculative-draft-model-path /data/eagle3/output_100k_sglang/4 \
/etc/systemd/system/sglang-qwen.service:  --model-path /data/models/Qwen3.5-397B-A17B-NVFP4 \

Both active SGLang services — the Qwen3.5-397B server and the Kimi-K2.5 server with EAGLE-3 speculative decoding — reference model files stored on /data.

Context and Motivation

This message does not occur in isolation. In the preceding message ([msg 6085]), the user gave a direct instruction:

"On the CT look if we're using anything in /data - the volume will be retired soon to cold backup, unmounted"

The user is planning to retire the /data volume — likely a large NVMe or network-backed storage partition — moving its contents to cold backup and unmounting it from the container. This is a common operational task: storage lifecycles, capacity planning, or cost optimization may drive a decision to decommission a volume. Before executing such a change, an operator must inventory everything that depends on that mount point.

The assistant had already begun this investigation in the immediately preceding messages ([msg 6086] through [msg 6088]), listing the contents of /data and measuring disk usage. Those checks revealed:

The Reasoning Process

The assistant's command design reveals a clear investigative strategy. Rather than searching broadly across the entire filesystem for /data references (which would return false positives from logs, caches, and temporary files), the assistant narrows the search to a single authoritative source: systemd unit files.

This choice reflects an understanding of how the container's services are managed. Both SGLang inference servers — the Qwen3.5-397B model and the Kimi-K2.5 model with EAGLE-3 speculative decoding — are deployed as systemd services (as established in earlier segments of the conversation). The ExecStart directives in these unit files contain the full command lines, including --model-path and --speculative-draft-model-path arguments that point to model weights on disk.

The command uses three parts separated by echo "===" markers:

  1. grep -r "/data" /etc/systemd/system/*.service — A recursive grep across all service files in the systemd directory. The -r flag is slightly redundant here since the glob *.service already matches individual files, but it ensures any subdirectories are also searched. The 2>/dev/null suppresses errors from files that can't be read.
  2. cat /etc/systemd/system/sglang-qwen.service | grep /data — An explicit double-check on the Qwen service file, which was just modified in earlier messages (the service was updated from --tp 8 to --tp 4 in [msg 6066] through [msg 6069]). This redundancy is intentional: it confirms the current state of the file after recent edits.
  3. cat /etc/systemd/system/sglang-kimi.service 2>/dev/null | grep /data — A check on the Kimi service file, which may or may not exist (hence the error suppression). The Kimi-K2.5 model was deployed earlier in the session with its own systemd service. The three-part structure is a form of progressive verification: first a broad scan, then targeted checks on the two known-critical services.

Assumptions Made

The assistant operates under several implicit assumptions:

That systemd service files are the authoritative source of runtime configuration. This is reasonable for a well-managed server where services are deployed as systemd units, but it is not exhaustive. A process could also be started manually, via cron, via a container orchestration layer, or via a shell script in /etc/rc.local. The assistant does not check these alternative sources.

That the model paths are specified as literal strings in the service files. The --model-path and --speculative-draft-model-path arguments could theoretically be read from environment variables or config files referenced by the service. If they were, the grep would miss them. However, the assistant's earlier work on these services (visible in [msg 6066] and [msg 6067]) confirms that the paths are hardcoded in the ExecStart lines.

That no other processes outside systemd depend on /data. The container runs an SGLang inference server, but there could be background data pipelines, monitoring scripts, or user home directories on /data that would also break upon unmount. The assistant's investigation is focused on the inference services because those are the primary workload.

That the /data mount is local to this container. The command runs inside LXC 129, which has its own /data mount. The user's question specifically asks "On the CT" (container), so this assumption is correct.

Potential Mistakes or Gaps

The most significant gap is the lack of a live process check. A process could have been started with /data paths without those paths appearing in a systemd unit file — for example, if the operator ran python3 -m sglang.launch_server ... directly in a shell or tmux session. The assistant does not run lsof or check /proc/*/cmdline to verify that no running process currently holds file handles on /data.

Additionally, the grep pattern "/data" is a substring match. It would match paths like /data_backup or /data_old if those happened to appear in a service file, though this is unlikely in practice. A more precise pattern would be "/data/" or "/data\b" to match the mount point specifically.

The assistant also does not check for bind mounts or symlinks that might point into /data from elsewhere in the filesystem. If a service's working directory or a configuration file were symlinked into /data, the service file itself might not contain the string /data at all.

Finally, the assistant does not check cron jobs (/etc/crontab, /var/spool/cron/) or tmpfiles.d configurations that might reference /data. These are less likely in an ML inference container but are valid dependency sources.

Input Knowledge Required

To understand this message, a reader needs:

Output Knowledge Created

This message produces concrete, actionable knowledge:

  1. The Qwen3.5-397B service depends on /data/models/Qwen3.5-397B-A17B-NVFP4 — This is the primary inference model, 223 GB of NVFP4-quantized weights. If /data is unmounted, this service will fail to start (or crash if restarted) because it cannot load its model.
  2. The Kimi-K2.5 EAGLE-3 service depends on /data/eagle3/output_100k_sglang/4 — This is the speculative draft model used for EAGLE-3-style speculative decoding. It is a smaller model that predicts multiple tokens per forward pass, accelerating inference. Without it, the Kimi service would either fall back to standard decoding or fail to start entirely.
  3. No other systemd services reference /data — The broad grep across all .service files returned only these two hits. This is negative knowledge: it tells the operator that no other registered service will break. This output directly informs the migration plan. Before /data can be unmounted, the operator must either: - Move the model files to a different path (e.g., /shared/models/) and update both service files - Or copy the models to the new location and create symlinks from /data to the new paths (a transitional approach) - Or accept that these services will be down during the migration window

The Broader Significance

Message [msg 6089] exemplifies a critical operational pattern: dependency discovery before infrastructure changes. In complex ML deployments, model weights can be hundreds of gigabytes and live on dedicated storage volumes. Retiring such a volume without first tracing every reference to it would cause service outages that might not be immediately obvious (the services would appear to be running but would fail on the next restart or when they try to load a checkpoint).

The assistant's approach — searching the service management layer rather than the filesystem or process table — reflects a pragmatic trade-off. Systemd unit files are declarative, versionable, and centralized. They represent the intended state of the system, which is often more useful than the current state when planning a migration. A process that currently holds a file handle on /data might exit before the unmount; a service file that references /data will cause a failure on every future start until it is updated.

This message also demonstrates the value of layered verification. The assistant does not stop at the broad grep; it explicitly checks the two services it knows about from prior work, confirming their specific paths. This catches any edge cases where the grep pattern might have missed a path (e.g., if the path were split across multiple lines in the service file).

Conclusion

Message [msg 6089] is a concise but essential step in a storage retirement workflow. By searching systemd service files for references to /data, the assistant identifies exactly two dependencies — the Qwen3.5-397B model path and the EAGLE-3 draft model path — that must be addressed before the volume can be safely unmounted. The command's design reflects a clear understanding of the system's architecture, a pragmatic narrowing of the search space, and a layered verification strategy. The output provides the operator with a concrete, actionable list of changes needed, transforming an abstract retirement plan into a specific migration task.