Zfs: moving storagenode to another pool, fast, and with no downtime

Node Operators
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The universal way to move the node is described in the documentation (it involves multiple rsync passes: one or more passes to transfer the bulk of the data first without shutting down the node, and then another pass to catch up to the current state with the node off). This is an inherently long, IO heavy process, however, if the target and a destinations are hosted on a ZFS filesystem, (including on different machines), the process can be significantly sped up by avoiding rsync and using ZFS send/receive and snapshots instead.

This is a short walkthrough, for reference for the future users.

Assumptions:

  1. storagenode node data is located on pool1/storagenode-old dataset, and databases are on the child dataset pool1/storagenode-old/databases
  2. OS is FreeBSD and node runs in a jail, named storagenode-jail
  3. We are moving the node to a new dataset on another pool on the same machine, named pool2/storagenode-new. If the target pool is on another machine — zfs send/receive should be piped over ssh, and the jail should be exported and imported on the target machine.

The process:

  1. Without stopping the node, create a recursive snapshot of the source node dataset. This happens instantly:
    zfs snapshot -r pool1/storagenode-old@snap1
  2. Send over the snapshot to the target filesystem. This takes huge amount of time (days), but node keeps running, so no hurry here:
    zfs send -Rv pool1/storagenode-old@snap1 | zfs receive pool2/storagenode-new
    Here R stands for Recursive, and v verbose, to see progress. If you are running this remotely, it’s a good idea to use tmux, to disconnect remote session without interrupting the transfer. The target dataset should not exist prior to running the command; it will be created.
    Now enjoy life until the process is done.
  3. While this has been running, node was adding and removing more data. So, let’s catch up with that too:
    zfs snapshot -r pool1/storagenode-old@snap2
zfs send -Rvi pool1/storagenode-old@snap1 pool1/storagenode-old@snap2 | zfs receive pool2/storagenode-new
    Here we create another snapshot, and then send the differential (i) update to the target filesystem. It can take few minutes to an hour – depending on how much data changed since last snapshot.
  4. Now we can finally stop the node and transfer small amount of changes accumulated since the snapshot in the previous step, to fully catch up:
    iocage stop storajenode-jail

zfs snapshot -r pool1/storagenode-old@snap3

zfs send -Rvi pool1/storagenode-old@snap2 pool1/storagenode-old@snap3 | zfs receive pool2/storagenode-new
    This shall take very little time, under a minute, since not much changes could have happened during previous short transfer.
  5. Now we have a coherent copy of the node data on the new dataset, but the jail mounts still point to the old one. Modify them:
    iocage fstab -e storagenode-jail
    This will open the editor with the fstab config. Edit the mounts to point to the new datasets at the target pool, save, and exit the editor.
  6. Now start the node:
    iocage start storagenode-jail
    At this point the node continues running from the state it was last stopped at, from the new dataset. Total downtime was under a minute spent in step 4 and a few seconds in step 5.
  7. Confirm node is up, and destroy the old dataset; it’s obsolete, out of date, and useless now:
    zfs destroy -rv -n pool1/storagenode-old
    r stands for “recursive”, v – verbose, and n – dry run. Review the output, and once you are content with what’s about to happen – re-run the command without the -n

That’s it.

9 Likes
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Just another reason, why you have to love ZFS :heart_eyes:

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yeah… but need to tune it (and have a lot of RAM…).
I almost sold on features, but… you know, there is always “but”… you really need much more RAM than with LVM and ext4. And speed, well, it’s not a dream even with a cache… But (again), it has a possibility to recover after a bitrot (in case of not a simple pool of course).
And you cannot (effectively) add a drive to the pool and simple extend it (recalculate parity and re-distribute data unlike LVM). I do not consider RAID0 or a simple volume (striped, extended, JBOD, whatever…), because the node will die with a one disk failure.

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I moved all my nodes to single drive LVMs recently. One of the nodes I moved to a different disk with vgextend/pvmove/vgreduce/lvextend afterwards. So much faster than a single rsync pass and the node can stay online throughout the whole move.

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Keep nodes on a single drive is a bad idea, not only because it breaks ToS, but also they will interfere each other slowing them down. And with failure of that disk they will die all together.

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Node can stay online in an rsync as well.
I have done it many time when moving to bigger harddrive.

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Using LVM, there would not be several rsync sessions and the node will be online all the time.
With rsync you will be forced to shutdown your node to make a final rsync with --delete option. With LVM pvmove this is not needed, because data is mirrored while in move.

However, LVM will not help, if you want to move to a remote device.

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Well, all I can say is that you should keep your setup as simple as possible, otherwise it can cause many strange errors which god knows how to fix. I recommend ext4 filesystem on a simple Linux distro like Debian, Ubuntu, Alpine; for disk setup please go JBOD, no RAID, nothing. By my experiences those fancy features will become hell some days…

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one node per disk only, otherwise it’s not better than RAID0 - with one disk failure the whole node is dead.

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If this was a reply to my post, of course I kept one node per disk. Each disk holds one volume group with one logical volume. I did this now to make moving my nodes to bigger disks in the future easier.

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Sorry, I misunderstood you. I though you placed them all on a one physical volume, which is equivalent of placing to the one HDD.

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This approach is not limited to zfs: this can be done on any filesystem that supports snapshots and replication: the goal is to drastically reduce IO by avoiding copying file by file, and instead streaming the entire filesystem, as the hard drives are very good at sequential IO and absolutely horrible at random. (For example, you can do the same thing almost verbatim with btrfs.)

Which brings us to the point @Alexey made:

While tuning is not really a problem or obstacle – it works fine as-is, and can be further optimized for storj, just like any other filesystem (e.g. sync=off), the ram requirement is indeed there.

However, in return, we get scalability: something that is “nice to have” today but unavoidable requirement in the future, if storj is to continue growing. See, today folks can get away with running storage node on a odroid with attached sata disk. Even without discussing filesystems, there is a ceiling of how much IO pressure can the HDD handle, it’s under 200 iops. at 4k this is under 1MBps… Below that node will be barely able to keep up and likely lose races, above that – it will simply choke. People already complain “omygawd filewalker ate all my IOPS”

So, in the future, when the traffic increases, these contraption will become unsustainable. Adding multiple disks together into load balanced config helps with IO linearly at best.

This one reason. Another – you still want to keep metadata in ram on any filesystem, including ext4, to avoid unnecessary IO and extra latency to first byte. So ram requirement grows linearly with the amount of data you store on any fs.

This is where other features of the zfs help a lot – such as ARC and special vdev. Everyone is more or less familiar with arc by now; but it’s the special device that brings the most performance improvement for storage node usecase: it allows to keep all metadata and small files under certain threshold on a separate (small) drive(s), such as fast SSDs. Not only this drastically, by order of magnitudes, not just linearly, reduces IO hitting the HDDs, but also now you don’t have have to keep all metadata in ram – reading is from SSD is still lightyears faster than from HDD, just like reading from ram. So, zfs, actually, helps reduce memory requirements in this case.

Ultimately, in my mind, there is no alternative going forward as storj grows. we’ll hopefully see more traffic, and therefore more IOPs, and therefore ZFS or similar filesystems will be either a requirement, or, at the very least, strong recommendation, that almost completely eliminates impact of hosting a storaagenode on your hardware, that is there sized for other reasons and purposes.

On other points:

With storage node, caching provides limited help, as soon as all metadata has been ingested: due to random nature of IO.

I don’t think this is important. You could use zfs pool with a 1-disk VDEV and 1-disk special device. It rots – fine. Network can tolerate that, it was designed to.

If we are talking about pool for storj – you definitely can.

First, once you accept that bit-rot is not something to be feared with storj data – you can use single disk vdevs.
And second: you can add new vdevs to the pool instantly, no checksums recompilation required; incoming data will be load balanced between all. (Those vdevs can be mirrors or raidz devices if you want to prevent rot). It’s much faster and better and more scalable that traditional raid

Understood. I would, if I had separate pool for storj: node dies – so what? I’ll start a new one, that’s the whole premise. But I don’t, beause I don’t buy separate hardware for storj, I use what I have, and I have a pool for my needs that is not yet fully utilized by those needs, and therefore it is fully redundant and performant array, that storagenode gets to benefit from. But I don’t have anything against non-redundant pools for stroagenode.

The key is to avoid copying file by file, so any solution that allows to stram filesystem is a win in the context of this topic.

This is until the traffic picks up and exceeds your HDDs max IOPS, at which point the node will choke. ZFS is as stable as anything can be, so I would not worry about risk that comes with fanciness – the whole premise of the filesystem is infinte scalability, and like anything else that came from SUN Microsystems – it’s brilliant. (the last one is my personal opinion :))

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if you mean to use a simple zfs pool without redundancy, it will increase risk to lose all data. But if you would use one disk per node (no stripe or JBOD), then there is an equal risk.

And striped pool in zfs after adding a disk will not start working faster (and usually striped volumes used exactly to increase speed), because there is no recalculation of the stripe size, so it will have the same IOPS as before, maybe less, if added disk has less IOPS.

With raidz adding a single disk to the pool will immediately convert it to RAID0 without redundancy, see Add drive to ZFS pool - HDD's & SSD's - Level1Techs Forums
The best you can do without re-creation is to make it some kind of RAID10 (but need at least two disks): Adding disks to ZFS pool - Unix & Linux Stack Exchange

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Yes, one pool, consisting of one-disk data vdev + one-SSD special vdev for metadata, per storage node.

By “disk” you mean here “vdev”. When you add a new VDEV to a pool and write new data, data is distributed across vdevs according to the remaining free space and performance. ZFS does load balancing. You can force redistribute/rebalance data with ZFS send/receive, if you really want to. But you don’t have to.

Pools in ZFS are not redundant. Only vdevs are. So if you are adding non-redundant vdev to a pool that so far contains redundant vdevs — you will lose redundancy. It does not make sense to do, and ZFS will refuse do it, unless you override with the -force flag.

However it does not convert everything to “raid0” either — your redundant vdevs are still tolerating disk failures. Still, mixing vdevs of different fault tolerance level is rarely justified.

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What I mean that extending a redundant array with adding only one HDD is not possible in zfs without re-creation or replacing them all to a bigger ones.
This is possible with LVM or BTRFS, but I would not recommend to use BTRFS for any important data, and LVM doesn’t have an error correction, so it’s not so good too.

So in short - there is no silver bullet to simple add a disk to extend a volume without increasing either costs or risks.