Solved: Advice 600TB NAS file system

#devops #programming #tutorial #cloud

🚀 Executive Summary

TL;DR: A 600TB NAS experiencing ‘disk full’ alerts despite available space is likely suffering from inode exhaustion, where the filesystem runs out of metadata pointers for files. Solutions involve reformatting with a higher inode density, migrating to a dynamically allocated filesystem like ZFS, or pivoting to infinitely scalable object storage.

🎯 Key Takeaways

Inode exhaustion occurs when a traditional filesystem’s fixed number of inodes are consumed by a large quantity of small files, even if physical disk space remains.
ZFS dynamically allocates inodes as needed, effectively eliminating inode exhaustion and offering features like compression, snapshots, and checksums for data integrity.
Object storage (e.g., AWS S3, MinIO) provides near-infinite scalability without inode limitations, treating data as objects and requiring applications to use an S3-compatible API.

Navigating the pitfalls of massive filesystems requires more than just adding disks; it demands a shift in architecture. Learn to solve the 600TB NAS challenge by understanding inode limits and choosing between traditional filesystem tweaks, modern solutions like ZFS, or pivoting to object storage.

So, Your 600TB NAS is Full… But Not Really.

I remember it like it was yesterday. It was 2 AM, and my on-call pager went off. The alert was screaming: DISK_FULL on media-archive-01. “Impossible,” I muttered. We had just added another 100TB to that array; df -h showed we were only at 65% capacity. I logged in, ran the command, and sure enough, plenty of terabytes to spare. But any attempt to write a new file, even a tiny one, failed. That, my friends, was my introduction to the soul-crushing nightmare of inode exhaustion. Someone had unzipped a research dataset with 150 million tiny sensor reading files, and our filesystem’s “card catalog” was full, even though the “library shelves” were empty. This Reddit thread brought all those painful memories flooding back.

The “Why”: It’s Not About Space, It’s About Bookkeeping

Let’s get one thing straight. When you format a traditional filesystem like ext4 or XFS, you aren’t just carving out raw space. You’re also creating a fixed number of inodes. Think of an inode as an index card in a library’s card catalog. Each file or directory gets one card. The card tells the system where to find the actual book (the data) on the shelves (the disk blocks).

The problem is, you decide how many “index cards” you want to create upfront. For general use, the default is fine. But when you’re dealing with hundreds of terabytes that might contain billions of tiny files—like log files, images, or scientific data—you can run out of index cards long before you run out of shelf space. That’s inode exhaustion. The system literally can’t track any more files.

Solution 1: The “Sledgehammer” Fix (Reformat with More Inodes)

This is the classic, brute-force approach. You have the hardware, but you set up the filesystem incorrectly for your workload. The fix? Nuke it and start over. I call it the Sledgehammer because it’s not subtle, but it gets the job done if you’re stuck with your current hardware and filesystem type.

The Plan:

Back up all 600TB of data. (Yes, really. Don’t even think about skipping this.)
Unmount the filesystem.
Reformat the volume using mkfs, but this time, you manually specify a much smaller bytes-per-inode ratio. The default is often 16384; you might want to drop it to 4096.
Restore all the data.

Here’s what that reformat command might look like for an ext4 filesystem:

# WARNING: This command destroys all data on /dev/sdb1
# The -i 4096 flag creates one inode for every 4096 bytes of disk space.
sudo mkfs.ext4 -i 4096 /dev/sdb1

Darian’s Warning: This is a high-downtime, high-risk operation. A backup or restore failure on a 600TB dataset is a career-defining event, and not in a good way. Only do this if you have a rock-solid, tested backup and a generous maintenance window.

Solution 2: The Architect’s Choice (Use a Better Filesystem)

If you have the chance to rebuild or migrate, don’t just reformat—upgrade. For this scale, my go-to recommendation is ZFS. We use it at TechResolve for our beefiest on-prem storage arrays for a reason. ZFS throws the concept of a fixed inode table out the window.

Instead, ZFS allocates inodes dynamically as they’re needed. Essentially, you will only run out of inodes when you physically run out of disk space. For a workload with an unpredictable mix of large and small files, this is a lifesaver.

The Plan:

Provision a new server or array with your disks.
Install an OS that has first-class ZFS support (like TrueNAS CORE or Ubuntu Server).
Create a ZFS pool (a zpool) and a ZFS filesystem (a dataset).
Migrate the data from the old NAS to the new ZFS-based one.

The setup is surprisingly simple:

# Create a new mirrored pool (RAID1) named 'tank' with two disks
sudo zpool create tank mirror /dev/sdb /dev/sdc

# Create a filesystem within that pool for your data
sudo zfs create tank/media_archive

# Enable compression - it's practically free on modern CPUs!
sudo zfs set compression=lz4 tank/media_archive

Plus, you get killer features like compression, snapshots, and checksums for data integrity, which are critical at this scale.

Solution 3: The Cloud-Native Pivot (Stop Using a Filesystem)

This is where I put on my Cloud Architect hat. Let’s ask a tough question: does this data need to be on a POSIX-compliant filesystem that you can ls -l? If it’s a massive archive of assets, backups, or raw data, the answer is probably no. You’re fighting the wrong battle.

The real solution is to treat it like what it is: a giant collection of objects. Move it to an object storage service.

The Plan:

Choose an object storage provider (AWS S3, Google Cloud Storage, Backblaze B2) or an on-prem S3-compatible solution like MinIO.
Create a bucket (e.g., techresolve-media-archive).
Use a high-throughput tool to sync the data from your NAS to the bucket.
Update your applications to speak to the S3 API instead of the local filesystem.

Object storage has no concept of inodes. You can store trillions of objects without issue. It’s infinitely scalable, and you pay for what you use, often with tiered pricing for data you access infrequently (like Glacier for S3).

# Example: Syncing a local directory to an S3 bucket
# This can be run in parallel on multiple machines to speed it up.
aws s3 sync /mnt/nas/my_data s3://techresolve-media-archive/

Pro Tip: This isn’t just for cloud. You can run your own S3-compatible object store on-prem with software like MinIO on the same commodity hardware you’d use for a ZFS server. It gives you the scalability of the cloud model without the data transfer bills.

Comparing The Approaches

There’s no single right answer, only the right answer for your specific constraints (time, budget, and application requirements).


Approach	Effort / Risk	Scalability	Best For…
1. Reformat (More Inodes)	High Risk, High Downtime	Poor (Just kicks the can)	Emergency situations where you can’t change hardware or core software.
2. ZFS Migration	Medium Effort (Migration)	Excellent (within the array)	New on-prem builds or major upgrades needing high performance and data integrity.
3. Object Storage Pivot	High Effort (App Changes)	Near-Infinite	Archival, media, backups, or any cloud-native application. The long-term strategic move.

Ultimately, a 600TB problem is rarely just a storage problem; it’s an architecture problem. Before you throw more disks at it, take a step back and ask if you’re using the right tool for the job. Your on-call self from two years in the future will thank you.