‘Format C:’ and Other Commands That Ruined Weekends

Why weekends die: destructive commands are still with us

“Format C:” became the punchline because it captured a truth: computers will do exactly what you told them to do, not what you meant. Modern systems just give you more ways to be precisely wrong. Instead of one disk, you have LVM layers, RAID controllers that virtualize reality, multipath device names, container overlay filesystems, ephemeral cloud volumes, and orchestration systems that can replicate your mistake at scale.

Destructive commands persist because deletion is a legitimate operation. We need to wipe disks, reset nodes, reinitialize filesystems, trim block devices, and garbage-collect old datasets. The difference between hygiene and homicide is usually one character, one assumption, or one stale mental model.

Here’s the operational pattern you should recognize: a routine maintenance task crosses paths with uncertainty (which device is which?) under time pressure (alerts are firing). The engineer tries to be efficient. Efficiency becomes speed. Speed becomes guesswork. Guesswork becomes a ticket that says “data missing” and a manager asking why backups didn’t magically cover it.

One quote you should keep taped to your monitor—because it’s true even when you don’t want it to be—is a paraphrased idea from John Allspaw: incidents are rarely the result of a single bad person; they come from normal people navigating messy systems.

Also: destructive commands don’t always look destructive. Sometimes the worst command is the one that “fixes” a performance issue by turning off the guardrails. Or the one that rebalances a cluster by “cleaning up” volumes. Or the one that changes mount options and corrupts assumptions, not data.

Joke 1/2: A destructive command is like a chainsaw—great tool, terrible fidget toy.

Facts & history you can use in incident postmortems

• The original DOS FORMAT command wasn’t just “erase”; it wrote filesystem structures. That distinction matters today: “formatting” can mean metadata reset, not zeroing.
• Early BIOS drive ordering made disk identity unstable. What looked like “Disk 0” could change after hardware changes—today’s equivalent is /dev/sdX renumbering after reboots or HBA swaps.
• Unix’s “everything is a file” made devices writable like files. That’s power and danger: dd doesn’t care whether the target is a test image or your boot disk.
• Many filesystems “delete” by removing references, not wiping content. That’s why forensic recovery sometimes works, and why secure erase is a separate problem.
• Device-mapper, LVM, and multipath introduced new abstraction layers. They solved problems (flexibility, HA paths) but made “which disk is that?” harder under pressure.
• Copy-on-write filesystems changed failure modes. Snapshots can save you from deletion, but fragmentation and space accounting can also surprise you during recovery.
• Cloud storage made disks disposable—and people treated data the same way. “Just rebuild the instance” is fine until you realize the state lived on the instance store.
• Enterprise RAID controllers can lie by omission. They present logical volumes that hide physical topology, so replacing “the wrong disk” can still break the right array.
• Automation expanded blast radius. The same IaC that can rebuild a fleet can also wipe a fleet if variable scoping or targeting is wrong.

Failure modes: how people end up nuking the wrong thing

1) Ambiguous identity: the “which disk is /dev/sdb?” problem

Linux device names are not identity. They’re order. Order is a suggestion. On systems with multiple HBAs, NVMe namespaces, iSCSI LUNs, or hotplug events, the mapping between /dev/sdX and “the disk you think you’re touching” is a coin flip disguised as determinism.

Serious operators use stable identifiers: WWN, serial, by-id paths, and filesystem UUIDs. The mistake is thinking you can “just check lsblk real quick.” Under incident pressure, “real quick” becomes “good enough,” and “good enough” becomes “oops.”

2) Wrong context: prod vs staging, host vs container, node vs cluster

Plenty of “destructive commands” were executed on the correct machine—just not the correct environment. Or executed inside a container while assuming it was the host. Or run on a Kubernetes node when the volume was actually attached elsewhere. Context errors happen because prompts lie, SSH sessions multiply, and people trust muscle memory more than they trust checks.

3) Commands that look safe because you’ve used them safely before

rm -rf is a classic, but the modern greatest hits include mkfs on the wrong device, parted on the wrong disk, zpool labelclear before you’re sure you have backups, and “cleanup” scripts that assume device paths are consistent. The command itself isn’t evil; the lack of verification is.

4) Optimization masquerading as correctness

When systems are slow, people get creative. They disable barriers, increase queue depths, tune dirty ratios, mount with risky options, or change writeback behavior. Some optimizations are legitimate, but anything that changes write ordering or durability semantics can turn a power flicker into corruption. Performance fixes are allowed; untested durability tradeoffs are not.

5) Recovery attempts that make recovery harder

The most common recovery-killer is continuing to write to a disk after accidental deletion. The second most common is “recreating” the filesystem, thinking it will restore a mountpoint. Once you run mkfs, you’ve overwritten key metadata. Some recovery is still possible, but you’ve moved from “restore from snapshot” to “call the data recovery vendor and start praying.”

Joke 2/2: Data recovery vendors don’t charge by the hour; they charge by the number of times you said “it’ll be quick.”

Three corporate mini-stories (all real enough to hurt)

Mini-story #1: The incident caused by a wrong assumption

A company had a small fleet of database replicas used for analytics. A senior engineer was asked to “wipe and rebuild the oldest replica” because its storage latency looked worse than the others. The host had two NVMe devices: one for the OS and one for the data. In the ticket, the data device was described as “the second NVMe.” That phrasing is how you summon chaos.

On that particular host, after a recent firmware update, the enumeration order changed. The device names were still /dev/nvme0n1 and /dev/nvme1n1, but which one was “data” was inverted compared to the engineer’s memory. They ran mkfs.xfs /dev/nvme1n1 believing it was the data disk. It was the OS disk. The node dropped from the cluster mid-command, as one does.

Because it was “only a replica,” the initial reaction was calm. Then the calm died. The replica was serving as the source for a downstream pipeline that had quietly become business-critical. Nobody documented that dependency. The rebuild took hours, and the pipeline’s consumers started backfilling aggressively, turning a data freshness issue into a load issue.

The postmortem wasn’t about the command. It was about the assumption: “second disk equals data disk.” The fix wasn’t “be more careful.” The fix was to standardize on stable identifiers, to label devices in automation, and to treat “replica” as “production until proven otherwise.”

Mini-story #2: The optimization that backfired

A storage-heavy service was struggling with write latency. Engineers saw spikes during peak hours, and the application team demanded a “quick win.” Someone suggested tuning the filesystem mount options and VM parameters to reduce latency by allowing more aggressive writeback. The change went through during a maintenance window, validated by a synthetic benchmark, and shipped.

For a week, latency graphs looked better. The team declared victory. Then there was an unplanned power event in a rack—brief, messy, the kind that’s “not supposed to happen” until it does. After reboot, several nodes reported filesystem inconsistencies. A few came back with corruption that required restoring from backups. A quick win turned into a slow recovery.

The root issue wasn’t “tuning is bad.” It was tuning without a durability threat model. Benchmarks don’t include brownouts. And a mount option that’s fine for a cache tier can be disastrous for primary state. If you change write ordering semantics, you must document the blast radius and test failure scenarios, not just happy-path performance.

The lasting improvement was boring: better write amplification measurement, separating hot data from cold, and choosing storage hardware that matched the workload. The risky tuning was rolled back, and the team added a policy: performance changes that touch durability need an explicit sign-off from storage/SRE and a failure injection test plan.

Mini-story #3: The boring but correct practice that saved the day

A different org ran a multi-tenant platform where customer data lived on ZFS datasets replicated to a second site. They had a strict practice: before any destructive maintenance, create a snapshot with a runbook-defined name and verify replication status. Engineers hated it because it added five minutes to every task. Five minutes is an eternity when you’re caffeinated and confident.

One evening, an on-call engineer was decommissioning a tenant. The ticket said “delete dataset pool/customers/acme.” They typed zfs destroy -r pool/customers/acme-prod by accident, because of course the naming was similar. The command succeeded immediately, and the dataset disappeared. That’s the moment your stomach tries to exit through your shoes.

But the snapshot policy had been followed. A snapshot existed from two minutes prior, and replication to the secondary site was current. Recovery was a controlled procedure: stop dependent services, rollback the dataset to the snapshot, and resume. No vendor calls. No archaeology. The incident became a small blip instead of a customer-facing catastrophe.

The postmortem didn’t praise heroics. It praised the checklist. The lesson was blunt: if your process depends on “people never making typos,” your process is fiction.

Practical tasks: commands, outputs, and decisions (12+)

These are tasks you can run during normal work and during incidents. Each includes: a command, what the output means, and what decision you make from it. The commands are Linux-focused because that’s where most modern “format C:” moments live, but the principles travel.

Task 1: Confirm where you are (host identity and environment)

cr0x@server:~$ hostnamectl
 Static hostname: prod-db-07
       Icon name: computer-vm
         Chassis: vm
      Machine ID: 9a2c3b...
         Boot ID: 4b113c...
  Virtualization: kvm
Operating System: Ubuntu 22.04.4 LTS
          Kernel: Linux 5.15.0-97-generic
    Architecture: x86-64

Meaning: This tells you the hostname, virtualization, and OS. If you expected staging and see prod-, stop.

Decision: If the identity is not exactly what your change ticket says, bail out. Reconnect using the correct bastion/profile.

Task 2: Make your prompt scream “PROD” (quick sanity check)

cr0x@server:~$ echo "$PS1"
\u@\h:\w\$

Meaning: A bland prompt encourages context mistakes.

Decision: If you operate production, use a prompt that includes environment and maybe color. This is preventative engineering, not aesthetics.

Task 3: List block devices with stable identifiers

cr0x@server:~$ lsblk -o NAME,TYPE,SIZE,MODEL,SERIAL,WWN,MOUNTPOINTS
NAME        TYPE  SIZE MODEL          SERIAL        WWN                MOUNTPOINTS
nvme0n1     disk  476G Samsung SSD    S4EVNX0R...   0x5002538d...       
├─nvme0n1p1 part  512M                             /boot
└─nvme0n1p2 part 475G                             /
nvme1n1     disk 1.75T Intel SSD     BTTV1234...   0x55cd2e41...       
└─nvme1n1p1 part 1.75T                             /var/lib/postgresql

Meaning: You can see which disk backs which mountpoints, plus serial/WWN for identity.

Decision: If a destructive action is planned, record the WWN/serial in the change log. Operate on that identity, not “nvme1n1.”

Task 4: Cross-check device paths via /dev/disk/by-id

cr0x@server:~$ ls -l /dev/disk/by-id/ | sed -n '1,12p'
total 0
lrwxrwxrwx 1 root root 13 Jan 21 10:11 nvme-INTEL_SSDPE2KX020T8_BTT... -> ../../nvme1n1
lrwxrwxrwx 1 root root 13 Jan 21 10:11 nvme-SAMSUNG_MZVLW512HMJP_S4E... -> ../../nvme0n1
lrwxrwxrwx 1 root root 15 Jan 21 10:11 nvme-eui.55cd2e4141414141 -> ../../nvme1n1
lrwxrwxrwx 1 root root 15 Jan 21 10:11 nvme-eui.5002538d22222222 -> ../../nvme0n1

Meaning: These symlinks provide stable-ish names. The EUI/WWN-style IDs are what you want in automation.

Decision: Use the by-id path in scripts and runbooks. Example: /dev/disk/by-id/nvme-eui.55cd....

Task 5: Confirm what’s mounted and what’s using it

cr0x@server:~$ findmnt -rno TARGET,SOURCE,FSTYPE,OPTIONS / /var/lib/postgresql
/ /dev/nvme0n1p2 ext4 rw,relatime,errors=remount-ro
/var/lib/postgresql /dev/nvme1n1p1 xfs rw,relatime,attr2,inode64,logbufs=8,logbsize=32k

Meaning: Shows filesystem type and mount options. If you’re about to wipe a disk that’s mounted, you’re about to have a bad time.

Decision: If the target is mounted, stop and unmount cleanly (or stop services first). If unmounting isn’t possible, you likely picked the wrong target.

Task 6: Identify what processes are writing to a mountpoint

cr0x@server:~$ sudo lsof +f -- /var/lib/postgresql | sed -n '1,8p'
COMMAND   PID USER   FD   TYPE DEVICE SIZE/OFF NODE NAME
postgres 2312  pg   cwd    DIR  259,1     4096    2 /var/lib/postgresql
postgres 2312  pg    10u   REG  259,1 10485760  123 /var/lib/postgresql/base/16384/2600
postgres 2312  pg    11u   REG  259,1  8388608  124 /var/lib/postgresql/base/16384/2601

Meaning: If you see active writes, you can’t treat the filesystem as “idle.”

Decision: Stop the service or drain the node before any disk maintenance. If you can’t stop it, reschedule or fail over.

Task 7: See immediate disk I/O pressure (the “is storage the bottleneck?” check)

cr0x@server:~$ iostat -xz 1 3
Linux 5.15.0-97-generic (prod-db-07)  01/21/2026  _x86_64_  (8 CPU)

avg-cpu:  %user   %nice %system %iowait  %steal   %idle
          12.10    0.00    3.22    8.45    0.00   76.23

Device            r/s     w/s   rkB/s   wkB/s  await  %util
nvme0n1          12.0   110.0   512.0  4096.0   2.10  18.0
nvme1n1         180.0   240.0  8192.0 16384.0  21.50  98.0

Meaning: High await and %util near 100% suggests the device is saturated or experiencing latency.

Decision: If nvme1n1 is at 98% util with 21ms await and your SLO expects low ms, you diagnose workload (queueing, write amplification) before you “optimize” mount options.

Task 8: Check filesystem space and inode pressure

cr0x@server:~$ df -hT /var/lib/postgresql
Filesystem     Type  Size  Used Avail Use% Mounted on
/dev/nvme1n1p1  xfs  1.8T  1.7T   90G  95% /var/lib/postgresql

Meaning: 95% full can trigger fragmentation, allocation issues, and write latency spikes.

Decision: If a filesystem is above ~85–90% used for heavy-write workloads, plan expansion or cleanup. Do not “fix performance” by disabling safety features.

Task 9: Verify what your RAID/LVM layer thinks is happening

cr0x@server:~$ sudo pvs; sudo vgs; sudo lvs -a -o +devices
  PV         VG   Fmt  Attr PSize   PFree
  /dev/sda2  vg0  lvm2 a--  931.00g 12.00g
  VG   #PV #LV #SN Attr   VSize   VFree
  vg0    1   2   0 wz--n- 931.00g 12.00g
  LV   VG   Attr       LSize   Pool Origin Data%  Meta%  Move Log Cpy%Sync Convert Devices
  root vg0  -wi-ao---- 100.00g                                            /dev/sda2(0)
  data vg0  -wi-ao---- 819.00g                                            /dev/sda2(25600)

Meaning: If your “disk” is actually a PV in a VG, wiping it wipes everything in that VG.

Decision: If you see LVM, treat the stack as a system. Plan changes at the correct layer and update diagrams/runbooks accordingly.

Task 10: Confirm ZFS pools and datasets before you destroy anything

cr0x@server:~$ sudo zpool status -v
  pool: tank
 state: ONLINE
  scan: scrub repaired 0B in 00:12:03 with 0 errors on Tue Jan 20 03:10:22 2026
config:

        NAME                        STATE     READ WRITE CKSUM
        tank                        ONLINE       0     0     0
          mirror-0                  ONLINE       0     0     0
            /dev/disk/by-id/ata-WDC_WD80...      ONLINE       0     0     0
            /dev/disk/by-id/ata-WDC_WD80...      ONLINE       0     0     0

errors: No known data errors

Meaning: Pool topology and device identity are explicit. If you see /dev/sdX here, fix that before it becomes a migration nightmare.

Decision: If you are about to remove/replace a disk, ensure you’re operating on the exact by-id device listed in zpool status.

Task 11: Snapshot before risky operations (ZFS example)

cr0x@server:~$ sudo zfs snapshot -r tank/customers/acme@pre-decom-2026-01-21
cr0x@server:~$ sudo zfs list -t snapshot -o name,used,refer -r tank/customers/acme | tail -n 3
tank/customers/acme@pre-decom-2026-01-21     0B  1.2T

Meaning: Snapshot exists and is cheap (0B used initially) because it references existing blocks.

Decision: If the snapshot creation fails or replication is behind, stop. Don’t proceed with a destructive change without a rollback handle.

Task 12: Dry-run deletions (where possible) and constrain scope

cr0x@server:~$ rsync -aHAXn --delete /srv/app/ /srv/app.new/ | sed -n '1,8p'
deleting old-cache/tmp123
deleting old-cache/tmp124
./
config/
config/app.yaml

Meaning: -n shows what would change. The word “deleting” should trigger careful review.

Decision: If the dry run shows unexpected deletes, fix your include/exclude rules before running without -n.

Task 13: Catch “oops, wrong directory” before rm -rf

cr0x@server:~$ pwd; ls -la
/var/lib/postgresql
total 24
drwx------  19 pg   pg  4096 Jan 21 10:02 .
drwxr-xr-x   3 root root 4096 Jan 10 09:11 ..
drwx------   5 pg   pg  4096 Jan 21 10:02 base
drwx------   2 pg   pg  4096 Jan 21 10:02 global

Meaning: If you’re in a data directory and your next command is “cleanup,” you’re gambling.

Decision: Use absolute paths in destructive commands. If you must use relative paths, explicitly print pwd first and read it like you’re reviewing a contract.

Task 14: Prove a block device is the one you intend (read-only check)

cr0x@server:~$ sudo blkid /dev/nvme1n1p1
/dev/nvme1n1p1: UUID="2a1d7c8f-3f2d-4b9d-9a7d-2ddfdd5d8b9a" TYPE="xfs" PARTUUID="b3d1..."

Meaning: This tells you what filesystem exists and its UUID.

Decision: If you expected “no filesystem” and you see a valid XFS/ext4 signature, stop. You’re about to erase something real.

Task 15: Inspect recent kernel logs for disk resets and errors

cr0x@server:~$ sudo dmesg -T | egrep -i 'nvme|reset|I/O error|blk_update_request' | tail -n 8
[Tue Jan 21 10:05:11 2026] nvme nvme1: I/O 123 QID 4 timeout, aborting
[Tue Jan 21 10:05:11 2026] nvme nvme1: Abort status: 0x371
[Tue Jan 21 10:05:12 2026] nvme nvme1: resetting controller
[Tue Jan 21 10:05:14 2026] blk_update_request: I/O error, dev nvme1n1, sector 983040 op 0x1:(WRITE) flags 0x0 phys_seg 1 prio class 0

Meaning: Timeouts and resets point to hardware, firmware, or driver issues—often misdiagnosed as “the database is slow.”

Decision: If you see resets/timeouts, stop tuning software and start isolating hardware, firmware, queueing, or path issues.

Task 16: Confirm TRIM/discard behavior (because “cleanup” can hurt)

cr0x@server:~$ lsblk -D -o NAME,DISC-ALN,DISC-GRAN,DISC-MAX,DISC-ZERO
NAME     DISC-ALN DISC-GRAN DISC-MAX DISC-ZERO
nvme0n1         0      512B       2G         0
nvme1n1         0      512B       2G         0

Meaning: Device supports discard. Depending on filesystem and mount options, deletes may issue discard/TRIM and make forensic recovery harder.

Decision: If you’re relying on undelete-style recovery, assume discard makes it less likely. Favor snapshots/backups over hope.

Fast diagnosis playbook: what to check first/second/third

This is the “stop guessing” sequence. You don’t need a war room to follow it. You need discipline and a willingness to be wrong quickly.

First: prove what is failing (symptom vs source)

1. Is the user-facing symptom latency, errors, or missing data? Missing data suggests destructive action or corruption. Latency suggests contention, saturation, or degradation.
2. Check the application error pattern. Timeouts often map to I/O waits; “no such file” maps to deletes/mount issues; checksum errors map to corruption.
3. Confirm you’re on the right host and right layer. Container vs host matters. A path inside a container may map to a volume you don’t expect.

Second: classify the bottleneck (CPU, memory, disk, network, lock contention)

1. CPU and run queue: if load is high but iowait is low, it’s not primarily storage.
2. Memory pressure: if swapping is active, everything looks like storage latency but it’s really memory starvation.
3. Disk saturation: high %util and growing await indicates queuing; correlate to workload spikes.
4. Network: if storage is remote (iSCSI, NFS, cloud block), measure network latency/loss.
5. Locks and fsync storms: databases can self-inflict I/O pain via checkpointing or sync-heavy patterns.

Third: choose the safest next action

1. If data might be deleted or corrupted: stop writes. Freeze the patient. Take snapshots (or LVM snapshots) if still possible.
2. If it’s performance: capture evidence first (iostat, vmstat, dmesg). Then apply reversible mitigations (rate limit, move workload, add capacity).
3. If hardware is suspect: do not “repair” by reformatting. Isolate, fail over, replace.

Common mistakes: symptoms → root cause → fix

1) “I formatted the wrong disk”

Symptoms: system won’t boot; mount fails; filesystem signature changed; immediate service crash.

Root cause: disk identity based on /dev/sdX or “second disk,” not stable IDs; no pre-flight checks; no snapshots.

Fix: use /dev/disk/by-id in runbooks; require lsblk with serial/WWN capture; enforce a pre-op snapshot where possible; do destructive actions in maintenance mode.

2) “rm -rf deleted more than expected”

Symptoms: sudden missing files; services failing to start; config directories gone; log shows deletions.

Root cause: relative path used from the wrong working directory; shell expansion; a variable was empty (rm -rf "$DIR" with DIR unset) or contained “/”.

Fix: use absolute paths; set set -u in scripts to fail on unset variables; add guard checks like “directory must match regex”; use dry runs (rsync -n) for mass deletes.

3) “dd wrote zeros to the wrong device”

Symptoms: partition table vanished; filesystem won’t mount; blkid returns nothing; data appears empty.

Root cause: device path confusion; copy/paste error; mixing up if= and of=.

Fix: never run dd without a read-only verification step; prefer safer tooling for wipe operations; when you must use dd, echo the command, confirm the target by-id, and require peer review for production.

4) “We optimized disk performance and got corruption later”

Symptoms: after reboot or crash, journal replay fails; database checksum errors; filesystem repairs required.

Root cause: changed mount options or kernel parameters impacting durability; disabled barriers; misconfigured RAID write cache without battery/flash protection.

Fix: treat durability semantics as a design constraint; run failure injection tests; document which tiers may trade durability for speed (cache) and which may not (source of truth).

5) “Everything is slow, but only sometimes”

Symptoms: periodic latency spikes; iowait spikes; app timeouts cluster at predictable times.

Root cause: background jobs (scrub, backup, compaction); snapshot expiration; RAID rebuild; cloud volume burst credits depleted.

Fix: correlate with schedules; throttle background tasks; isolate noisy neighbors; add steady-state capacity instead of relying on burst.

6) “We can’t recover because we kept writing”

Symptoms: attempted recovery fails; deleted files overwritten; undelete tools find nothing useful.

Root cause: continuing service writes after realizing deletion; recreating filesystem; automatic cleanup services running.

Fix: immediate write-stop procedure: stop services, remount read-only if possible, detach volume, snapshot at storage layer, then attempt recovery.

Checklists / step-by-step plan

A. Before any destructive storage command (wipe, mkfs, destroy, labelclear)

1. Confirm environment: host identity, account/profile, cluster context.
2. Identify the target by stable ID: WWN/serial, not sdX/nvmeX.
3. Prove what’s mounted: findmnt on the target.
4. Prove what’s writing: lsof or service status.
5. Create a rollback handle: snapshot/dataset snapshot/LVM snapshot or storage snapshot. If you can’t, get explicit approval for irreversible change.
6. State the blast radius in one sentence: “This will wipe disk backing /var/lib/postgresql on prod-db-07.” If you can’t write that sentence, you don’t understand the change.
7. Peer review: another human reads the exact device path and command. Not “looks fine.” They must re-derive the target.
8. Execute with guardrails: use by-id paths, use interactive confirmation where available, and log the command output.

B. If you suspect you ran the wrong command (damage control in the first 5 minutes)

1. Stop writes immediately. Stop services, detach volumes, cordon nodes—whatever stops further damage.
2. Do not run “fix” commands impulsively. Especially mkfs, “repair” tools, or re-partitioning.
3. Capture state: dmesg, lsblk, blkid, mount, storage layer status.
4. Snapshot if possible. Even a broken volume snapshot can preserve evidence and prevent further loss.
5. Escalate early. Storage and SRE should be in the loop before anyone tries a “quick recovery.”

C. If the problem is “storage is slow” (safe performance response)

1. Measure first: iostat, vmstat, per-process I/O, and kernel logs.
2. Identify top talkers: which process or job is driving I/O.
3. Mitigate reversibly: throttle batch jobs, shift load, add replicas, increase cache, reduce concurrency.
4. Only then tune: and only with a rollback plan and durability evaluation.

FAQ

1) Is “formatting” the same as “wiping”?

No. Formatting typically writes filesystem metadata (superblocks, allocation structures). Wiping implies overwriting more broadly. Either can destroy recoverability.

2) Why is /dev/sdX unreliable?

Because it’s assigned based on discovery order. Discovery order can change with reboots, firmware updates, path changes, or added devices. Use by-id paths, serials, WWNs, or UUIDs.

3) If I deleted the wrong directory, should I remount read-only?

If you suspect data recovery is needed and you can tolerate downtime, yes—stop writes. Writes overwrite freed blocks and reduce recovery options.

4) Does TRIM/discard make recovery impossible?

Not always, but it can make it dramatically harder. If blocks are discarded, the device may treat them as unmapped and return zeros. Assume discard reduces your chances.

5) Are snapshots a replacement for backups?

No. Snapshots are excellent for fast rollback and “oops” recovery, but they typically share the same failure domain. You still need separate backups (and tested restores).

6) What’s the safest way to run risky commands in production?

Make identity unambiguous (by-id), constrain scope (exact path/device), add a rollback handle (snapshot), and require a second human to validate the target.

7) Why do optimizations sometimes lead to corruption later?

Because some tuning changes durability semantics: write ordering, flush behavior, cache safety, or assumptions about power-loss protection. It can look fine until a crash tests it.

8) I ran mkfs on the wrong partition. Is there any hope?

Sometimes. Stop writes immediately. Do not re-run mkfs. Capture metadata and engage experienced recovery help. Your success depends on what was overwritten and how much has been written since.

9) How do I prevent scripts from doing “rm -rf /” style damage?

Use set -euo pipefail, validate variables, require explicit allowlists, and implement “are you sure?” prompts for interactive use. For automation, use staged rollouts and dry-run modes.

10) What’s the single best habit to avoid weekend-ruiners?

Force yourself to identify targets by stable identity and to say the blast radius out loud (or in the ticket) before you press Enter.

Conclusion: next steps that actually reduce risk

If you take one thing from the “format C:” era into modern ops, make it this: computers are literal, and production is unforgiving. Destructive commands aren’t going away. The goal is to make them deliberate, verifiable, and recoverable.

Do this next:

1. Update runbooks to use stable identifiers (/dev/disk/by-id, WWN/serial, UUIDs). Stop documenting “/dev/sdb” like it’s a fact of nature.
2. Adopt a mandatory pre-destructive snapshot policy where technically possible, and track exceptions explicitly.
3. Build a “stop writes” muscle memory for suspected data loss incidents. The first five minutes decide whether recovery is easy or archaeological.
4. Separate performance tuning from durability changes with a review gate and a rollback plan.
5. Practice recovery on non-production: restore from backup, rollback snapshots, import pools, mount volumes. The best time to learn is not during a customer outage.

Weekends are for sleeping, not for watching a progress bar on a restore job while you reconsider every life choice that led to “just a quick command.”