ZFS tuning cheat sheet

Quick and dirty cheat sheet for anyone getting ready to set up a new ZFS pool. Here are all the settings you’ll want to think about, and the values I think you’ll probably want to use.

I am not generally a fan of tuning things unless you need to, but unfortunately a lot of the ZFS defaults aren’t optimal for most workloads.

SLOG and L2ARC are special devices, not parameters… but I included them anyway. Lean into it.

parameter best* value why / what does it do?
ashift 12 Ashift tells ZFS what the underlying physical block size your disks use is. It’s in bits, so ashift=9 means 512B sectors (used by all ancient drives), ashift=12 means 4K sectors (used by most modern hard drives), and ashift=13 means 8K sectors (used by some modern SSDs).

If you get this wrong, you want to get it wrong high. Too low an ashift value will cripple your performance. Too high an ashift value won’t have much impact on almost any normal workload.

Ashift is per vdev, and immutable once set. This means you should manually set it at pool creation, and any time you add a vdev to an existing pool, and should never get it wrong because if you do, it will screw up your entire pool and cannot be fixed.

 xattr  sa  Sets Linux eXtended ATTRibutes directly in the inodes, rather than as tiny little files in special hidden folders.

This can have a significant performance impact on datasets with lots of files in them, particularly if SELinux is in play. Unlikely to make any difference on datasets with very few, extremely large files (eg VM images).

 compression  lz4  Compression defaults to off, and that’s a losing default value. Even if your data is incompressible, your slack space is (highly) compressible.

LZ4 compression is faster than storage. Yes, really. Even if you have a $50 tinkertoy CPU and a blazing-fast SSD. Yes, really. I’ve tested it. It’s a win.

You might consider gzip compression for datasets with highly compressible files. It will have better compression rate but likely lower throughput. YMMV, caveat imperator.

 atime  off  If atime is on – which it is by default – your system has to update the “Accessed” attribute of every file every time you look at it. This can easily double the IOPS load on a system all by itself.

Do you care when the last time somebody opened a given file was, or the last time they ls’d a directory? Probably not. Turn this off.

 recordsize  16K  If you have files that will be read from or written to in random batches regularly, you want to match the recordsize to the size of the reads or writes you’re going to be digging out of / cramming into those large files.

For most database binaries or VM images, 16K is going to be either an exact match or at least a much better one than the default recordsize, 128K.

This can improve the IOPS capability of an array used for db binaries or VM images fourfold or more.

 recordsize  1M  Wait, didn’t we just do recordsize…? Well, yes, but different workloads call for different settings if you’re tuning.

If you’re only reading and writing in fairly large chunks – for example, a collection of 5-8MB JPEG images from a camera, or 100GB movie files, either of which will not be read or written random access – you’ll want to set recordsize=1M, to reduce the IOPS load on the system by requiring fewer individual records for the same amount of data. This can also increase compression ratio, for compressible data, since each record uses its own individual compression dictionary.

If you’re using bittorrent, recordsize=16K results in higher possible bittorrent write performance… but recordsize=1M results in lower overall fragmentation, and much better performance when reading the files you’ve acquired by torrent later.

 SLOG  maybe  SLOG isn’t a setting, it’s a special vdev type that acts as a write aggregation layer for the entire pool. It only affects synchronous writes – asynchronous writes are already aggregated in the ZIL in RAM.

SLOG doesn’t need to be a large device; it only has to accumulate a few seconds’ worth of writes. Having one means that synchronous writes perform like asynchronous writes; it doesn’t really act like a “write cache” in the way new ZFS users tend to hope it will.

Great for databases, NFS exports, or anything else that calls sync() a lot. Not too useful for more casual workloads.

 L2ARC  nope!  L2ARC is a layer of ARC that resides on fast storage rather than in RAM. It sounds amazing – super huge super fast read cache!

Yeah, it’s not really like that. For one thing, L2ARC is ephemeral – data in L2ARC  doesn’t survive reboots. For another thing, it costs a significant amount of RAM to index the L2ARC, which means now you have a smaller ARC due to the need for indexing your L2ARC.

Even the very fastest SSD is a couple orders of magnitude slower than RAM. When you have to go to L2ARC to fetch data that would have fit in the ARC if it hadn’t been for needing to index the L2ARC, it’s a massive lose.

Most people won’t see any real difference at all after adding L2ARC. A significant number of people will see performance decrease after adding L2ARC. There is such a thing as a workload that benefits from L2ARC… but you don’t have it. (Think hundreds of users, each with extremely large, extremely hot datasets.)

* “best” is always debatable. Read reasoning before applying. No warranties offered, explicit or implied.

Routing between wg interfaces with WireGuard

Aha! This was the last piece I was really looking for with WireGuard. It gets a bit tricky when you want packets to route between WireGuard clients. But once you grok how it works, well, it works.

This also works for passing traffic between WireGuard clients on the same interface – the trick is in making certain that AllowedIPs in the client configs includes the entire IP subnet services by the server, not just the single IP address of the server itself (with a /32 subnet)… and that you not only set up the tunnel on each client, but initialize it with a bit of data as well.

Set up your server with two WireGuard interfaces:

root@server:~# touch /etc/wireguard/keys/server.wg0.key
root@server:~# chmod 600 /etc/wireguard/keys/server.wg0.key 
root@server:~# wg genkey > /etc/wireguard/keys/server.wg0.key root@server:~# wg pubkey < /etc/wireguard/keys/server.wg0.key > /etc/wireguard/keys/server.wg0.pub

root@server:~# touch /etc/wireguard/keys/server.wg1.key
root@server:~# chmod 600 /etc/wireguard/keys/server.wg1.key 
root@server:~# wg genkey > /etc/wireguard/keys/server.wg1.key root@server:~# wg pubkey < /etc/wireguard/keys/server.wg1.key > /etc/wireguard/keys/server.wg1.pub

Don’t forget to make sure ipv4 forwarding is enabled on your server:

root@server:~# sed -i 's/^#net\.ipv4\.ip_forward=1/net.ipv4.ip_forward=1/' /etc/sysctl.conf
root@server:~# sysctl -p

Now set up your wg0.conf:

# server.wg0.conf

[Interface] 
   Address = 10.0.0.1/24 
   ListenPort = 51820
   PrivateKey = WG0_SERVER_PRIVATE_KEY
   SaveConfig = false

[Peer] 
   # client1 
   PublicKey = PUBKEY_FROM_CLIENT_ONE
   AllowedIPs = 10.0.0.2/32

And your wg1.conf:

# server.wg1.conf

[Interface] 
 Address = 10.0.1.1/24 
 ListenPort = 51821
 PrivateKey = WG1_SERVER_PRIVATE_KEY
 SaveConfig = false

[Peer] 
 # client2 
 PublicKey = PUBKEY_FROM_CLIENT_TWO
 AllowedIPs = 10.0.1.2/32

Gravy. Now enable both interfaces, and bring them online.

root@server:~# systemctl enable wg-quick@wg0 ; systemctl enable wg-quick@wg1
root@server:~# systemctl start wg-quick@wg0 ; systemctl start wg-quick@wg1

Server’s done. Now, set up your clients.

Client install, multi-wg server:

Client one will connect to the server’s wg0, and client two will connect to the server’s wg1. After creating your keys, set them up as follows:

# /etc/wireguard/wg0.conf on Client1
#    connecting to server/wg0
 
[Interface]
   Address = 10.0.0.2/24
   PrivateKey = PRIVATE_KEY_FROM_CLIENT1
   # set up routing from server/wg0 to server/wg1
   PostUp = route add -net 10.0.1.0/24 gw 10.0.0.1 ; ping -c1 10.0.0.1
   PostDown = route delete -net 10.0.1.0/24 gw 10.0.0.1
   SaveConfig = false

[Peer]
   PublicKey = PUBKEY_FROM_SERVER
   AllowedIPs = 10.0.0.1/24, 10.0.1.1/24
   Endpoint = wireguard.yourdomain.tld:51820

Now set up wg0 on Client2:

# /etc/wireguard/wg0.conf on Client2
#   connecting to server/wg1 

[Interface]
   Address = 10.0.1.2/24
   PrivateKey = PRIVATE_KEY_FROM_CLIENT2
   # set up routing from server/wg1 to server/wg0
   PostUp = route add -net 10.0.0.0/24 gw 10.0.1.1 ; ping -c1 10.0.1.1
   PostDown = route delete -net 10.0.0.0/24 gw 10.0.1.1
   SaveConfig = false

[Peer]
   PublicKey = PUBKEY_FROM_SERVER
   AllowedIPs = 10.0.0.1/24, 10.0.1.1/24
   Endpoint = wireguard.yourdomain.tld:51821

Now start up the client interfaces. First, Client1:

root@client1:~# systemctl start wg-quick@wg0
root@client1:~# wg
interface: wg0
 public key: MY_PUBLIC_KEY
 private key: (hidden)
 listening port: some-random-port

peer: SERVER_PUBLIC_KEY
 endpoint: server-ip-address:51820
 allowed ips: 10.0.0.0/24, 10.0.1.0/24
 latest handshake: 3 seconds ago
 transfer: 2.62 KiB received, 3.05 KiB sent

Now Client2:

root@client2:~# systemctl start wg-quick@wg0
root@client2:~# wg
interface: wg0
 public key: MY_PUBLIC_KEY
 private key: (hidden)
 listening port: some-random-port

peer: SERVER_PUBLIC_KEY
 endpoint: server-ip-address:51821
 allowed ips: 10.0.0.0/24, 10.0.1.0/24
 latest handshake: 4 seconds ago
 transfer: 2.62 KiB received, 3.05 KiB sent

Now that both clients are connected, we can successfully send traffic back and forth between client1 and client2.

root@client1:~# ping -c3 10.0.1.2
PING 10.0.1.2 (10.0.1.2) 56(84) bytes of data.
64 bytes from 10.0.1.2: icmp_seq=1 ttl=63 time=80.4 ms
64 bytes from 10.0.1.2: icmp_seq=2 ttl=63 time=83.5 ms
64 bytes from 10.0.1.2: icmp_seq=3 ttl=63 time=83.2 ms

--- 10.0.1.2 ping statistics ---
3 packets transmitted, 3 received, 0% packet loss, time 2003ms
rtt min/avg/max/mdev = 80.492/82.410/83.501/1.380 ms

Sweet.

The step some of you undoubtedly missed:

There’s a little trick that will frustrate you to no end if you glossed over the client config files without paying attention.

PostUp = route add -net 10.0.0.0/24 gw 10.0.1.1 ; ping -c1 10.0.1.1

If you left out that ping command in one or both of the clients, then you won’t be able to ping client1 from client2, or vice versa, until each client has sent some data down the tunnel. This frustrated the crap out of me initially – ping client2 from client1 would be broken, but then ping client1 from client2 would work and then ping client2 from client1 would work. The solution, as shown, is just to make sure we immediately chuck a packet down the tunnel whenever each client connects; then everything works as intended.

What if I don’t want multiple interfaces?

If all you want to do is pass traffic from one client to the next, you don’t need two interfaces on the server, and you don’t need PostUp and PostDown route commands, either. The trick is that you do need to make sure that AllowedIPs on each client is set to a range that includes the other client, and you do need the PostUp ping -c1 server-ip-addresscommand on each client as well. Without that PostUp ping, you’re going to get frustrated by connectivity that “sometimes works and sometimes doesn’t”.

If you want to give access to some clients but not all clients, you can do that by setting multiple AllowedIPs arguments on the clients, like so:

[Peer]
   PublicKey = PUBKEY_FROM_SERVER
   # this stanza allows access from the server (.1), client one (.2),
   # and client two (.3) - but not from any clients at .4-.254.
   AllowedIPs = 10.0.0.1/32, 10.0.0.2/32, 10.0.0.3/32
   Endpoint = wireguard.yourdomain.tld:51820

That is a sample [Peer] stanza of a client wg config, not a[Peer] stanza of the server wg config! The[Peer] stanzas of the server config should only allow connection to a single IP (using a /32 subnet) for each individual[Peer] definition.

If you try to set AllowedIPs 10.0.0.0/24 on both client1 and client2’s[Peer] stanzas in the server’s wg config, you’ll break one or the other client – they can’t BOTH be allowed the entire subnet.

This bit’s a little confusing, I know, but that’s how it works.

As always, caveat imperator.

Just like the last couple of posts, everything here is tested and working. Also just like the last couple of posts, this is day zero of my personal experience with Wireguard. While everything here works, I still have not delved into any of the actual crypto components’ configurability or personally evaluated/researched how sane the defaults are.

These configs absolutely will encrypt the data sent down the tunnel – I’ve verified that much! – but I cannot offer a well-established and researched opinion on how well they encrypt that data, or what weaknesses there might be. I have no particular reason to believe they’re not secure, but I haven’t done any donkey-work to thoroughly establish that they are secure either.

Caveat imperator.

I may come back to edit out these dire warnings in a few weeks or months as I hammer at this stuff more. Or I might forget to! Feel free to tweet @jrssnet if you want to ask how or if things have changed; I am definitely going to continue my evaluation and testing.

Working VPN-gateway configs for WireGuard

Want to set up a simple security VPN, that routes all your internet traffic out of a potentially hostile network through a trusted VM somewhere? Here you go. Note that while all this is tested and working, this is still literal day zero of my personal experience with Wireguard; in particular while Wireguard claims to use only the most secure crypto (the best, everybody says that!) I not only have not really investigated that, I don’t know how to configure that part of it, so this is just using whatever the WG defaults are. Caveat imperator.

Installing Wireguard, generating keys:

This first set of steps is the same for all machines. Substitute the actual machine name as appropriate; you want to make sure you know which of these keys is which later on down the line, so actually name them and don’t be sloppy about it.

root@machine:~# apt-add-repository ppa:wireguard/wireguard ; apt update ; apt install wireguard-dkms wireguard-tools

root@machinename:~# mkdir /etc/wireguard/keys
root@machinename:~# chmod 700 /etc/wireguard/keys

root@machinename:~# touch /etc/wireguard/keys/machinename.wg0.key
root@machinename:~# chmod 600 /etc/wireguard/keys/machinename.wg0.key

root@machinename:~# wg genkey > /etc/wireguard/keys/machinename.wg0.key
root@machinename:~# wg pubkey < /etc/wireguard/keys/machinename.wg0.key > /etc/wireguard/keys/machinename.wg0.pub

OK, you’ve installed wireguard on your server VM and one or two clients, and you’ve generated some keys.

Setting up your server VM:

Create your config file on the server, at /etc/wireguard/wg0.conf:

[Interface] 
   Address = 10.0.0.1/24 
   ListenPort = 51820 
   PrivateKey = YOUR_SERVER_PRIVATE_KEY
   SaveConfig = false
 
   # Internet Gateway config: nat wg1 out to the internet on eth0 
   PostUp = iptables -A FORWARD -i wg1 -j ACCEPT; iptables -t nat -A POSTROUTING -o eth0 -j MASQUERADE 
   PostDown = iptables -D FORWARD -i wg1 -j ACCEPT; iptables -t nat -D POSTROUTING -o eth0 -j MASQUERADE

[Peer] 
   # Client1
   PublicKey = PUBLIC_KEY_FROM_CLIENT1
   AllowedIPs = 10.0.0.2/32

[Peer] 
   # Client2 
   PublicKey = PUBLIC_KEY_FROM_CLIENT2
   AllowedIPs = 10.0.0.3/32

Now you’ll need to enable ipv4 forwarding in /etc/sysctl.conf.

root@server:~# sed -i 's/^#net\.ipv4\.ip_forward=1/net.ipv4.ip_forward=1/' /etc/sysctl.conf
root@server:~# sysctl -p

Enable your wg0 interface to start automatically at boot, and bring it up:

root@server:~# sysctl enable wg-quick@wg0
root@server:~# sysctl start wg-quick@wg0

Server should be good to go now.

Setting up your clients:

Client setup is a bit simpler; all you really need is the /etc/wireguard/wg0.conf file itself.

[Interface] 
   # CLIENT1 
   Address = 10.0.0.2/24 
   PrivateKey = CLIENT1_PRIVATE_KEY
   SaveConfig = false

   # the DNS line is broken on 18.04 due to lack of resolvconf 
   # DNS = 1.1.1.1

[Peer] 
   # SERVER 
   PublicKey = PUBLIC_KEY_FROM_SERVER
   Endpoint = wireguard.yourdomain.fqdn:51820

   # gateway rule - send all traffic out over the VPN
   AllowedIPs = 0.0.0.0/0

Note that I have the DNS = 1.1.1.1 line commented out above – its syntax is correct, and it works fine on Ubuntu 16.04, but on 18.04 it will cause the entire interface not to come up due to a lack of installed resolvconf.

You can use sysctl enable wg-quick@wg0 to have the wg0 interface automatically start at boot the way we did on the server, but you likely won’t want to. Without enabling it to start automatically at boot, you can use sysctl start wg-quick@wg0 by itself to manually start it, and sysctl stop wg-quick@wg0 to manually disconnect it. Or if you’re not in love with systemd, you can accomplish the same thing with the raw wg-quick commands: wg-quick up wg0 to start it, and wg-quick down wg0 to bring it down again. Your choice.

What about Windows? Android? Etc?

You can use TunSafe as a Windows client, and the WireGuard app on Android. Setup steps will basically be the same as shown above. On a Mac, you can reportedly brew install wireguard-tools and have everything work as above (though you’ll need to invoke wg-quick directly; systemd isn’t a thing there).

If you’ve rooted your Android phone, you can build a kernel that includes the Wireguard kernel module; if you haven’t, stock kernels work fine – the Android app just runs in userspace mode, which is somewhat less efficient. (You’re currently stuck in userspace mode on a Mac no matter what, AFAIK; not sure what the story is with TunSafe on Windows.)

If you’re using iOS, there’s a Git repository that purports to be a Wireguard client for iPhone/iPad; but good f’n luck actually doing anything with it unless you’re pretty deep into the iOS development world already.

Some testing notes on WireGuard

I got super, super interested in WireGuard when Linus Torvalds heaped fulsome praise on its design (if you’re not familiar with Linus’ commentary, then trust me – that’s extremely fulsome in context) in an initial code review this week. WireGuard aims to be more secure and faster than competing VPN solutions; as far as security goes, it’s certainly one hell of a lot more auditable, at 4,000 lines of code compared to several hundred thousand lines of code for OpenVPN/OpenSSL or IPSEC/StrongSwan.

I’ve got a decade-and-a-half of production experience with OpenVPN and various IPSEC implementations, and “prettiness of code” aside, frankly they all suck. They’re not so bad if you only work with a client or ten at a time which are manually connected and disconnected; but if you’re working at a scale of hundred+ clients expected to be automatically connected 24/7/365, they’re a maintenance nightmare. The idea of something that connects quicker and cleaner, and is less of a buggy nightmare both in terms of security and ongoing usage, is pretty strongly appealing!

WARNING:  These are my initial testing notes, on 2018-Aug-05. I am not a WireGuard expert. This is my literal day zero. Proceed at own risk!

Alright, so clearly I wanna play with this stuff.  I’m an Ubuntu person, so my initial step is apt-add-repository ppa:wireguard/wireguard ; apt update ; apt install wireguard-dkms wireguard-tools .

After we’ve done that, we’ll need to generate a keypair for our wireguard instance. The basic commands here are wg genkey and wg pubkey. You’ll need to pipe private key created with wg genkey into wg pubkey to get a working private key.  You don’t have to store your private key anywhere outside the wg0.conf itself, but if you’re a traditionalist and want them saved in nice organized files you can find (and which aren’t automagically monkeyed with – more on that later), you can do so like this:

root@box:/etc/wireguard# touch machinename.wg0.key ; chmod 600 machinename.wg0.key
root@box:/etc/wireguard# wg genkey > machinename.wg0.key
root@box:/etc/wireguard# wg pubkey < machinename.wg0.key > machinename.wg0.pub

You’ll need this keypair to connect to other wireguard machines; it’s generated the same way on servers or clients. The private key goes in the [Interface] section of the machine it belongs to; the public key isn’t used on that machine at all, but is given to machines it wants to connect to, where it’s specified in a [Peer] section.

From there, you need to generate a wg0.conf to define a wireguard network interface. I had some trouble finding definitive information on what would or wouldn’t work with various configs on the server side, so let’s dissect a (fairly) simple one:

# /etc/wireguard/wg0.conf - server configs

[Interface]
   Address = 10.0.0.1/24
   ListenPort = 51820
   PrivateKey = SERVER_PRIVATE_KEY
   
   # SaveConfig = true makes commenting, formattting impossible
   SaveConfig = false
   # This stuff sets up masquerading through the server's WAN,
   # if you want to route all internet traffic from your client
   # across the Wireguard link. 
   #
   # You'll also need to set net.ipv4.ip_forward=1 in /etc/sysctl.conf
   # if you're going this route; sysctl -p to reload sysctl.conf after
   # making your changes.
   #
   PostUp = iptables -A FORWARD -i wg0 -j ACCEPT; iptables -t nat -A POSTROUTING -o eth0 -j MASQUERADE; ip6tables -A FORWARD -i wg0 -j ACCEPT; ip6tables -t nat -A POSTROUTING -o eth0 -j MASQUERADE
   PostDown = iptables -D FORWARD -i wg0 -j ACCEPT; iptables -t nat -D POSTROUTING -o eth0 -j MASQUERADE; ip6tables -D FORWARD -i wg0 -j ACCEPT; ip6tables -t nat -D POSTROUTING -o eth0 -j MASQUERADE

OK, so far so good. Note that SERVER_PRIVATE_KEY above is not a reference to a filename – it’s the server’s private key itself, pasted directly into the config file!

With the above server config file (and a real private key on the private key line), wg0 will start, and will answer incoming connections. The problem is, it’ll answer incoming connections from anybody who has the server’s public key – no verification of the client necessary. (TESTED)

Here’s a sample client config:

# client config - client 1 - /etc/wireguard/wg0.conf

[Interface]
   Address = 10.0.0.2/20
   SaveConfig = true
   PrivateKey = MY_PRIVATE_KEY

   # Warning: setting DNS here won't work if you don't
   # have resolvconf installed... and if you're running
   # Ubuntu 18.04, you probably don't have resolvconf
   # installed. If you set this without resolvconf available,
   # the whole interface will fail to come up.
   #
   # DNS = 1.1.1.1

[Peer]
   PublicKey = SERVER_PUBLIC_KEY
   Endpoint = wireguard.mydomain.wtflol:51820

   # this restricts tunnel traffic to the VPN server itself
   AllowedIPs = 172.29.128.1/32

   # if you wanted to route ALL traffic across the VPN, do this instead:
   # AllowedIPs = 0.0.0.0/0

Notice that we set SaveConfig=true in wg0.conf here on our client. This may be more of a bug than a feature. See those nice helpful comments we put in there? And notice how we specified an FQDN instead of a raw IP address for our server endpoint? Well, with SaveConfig=true on, those are going to get wiped out every time the service is restarted (such as on boot). The comments will just get wiped, stuff like the random dynamic port the client service uses will get hard-coded into the file, and the FQDN will be replaced with whatever IP address it resolved to the last time the service was started.

So, yes, you can use an FQDN in your configs – but if you use SaveConfig=true you might as well not bother, since it’ll get immediately replaced with a raw IP address anyway. Caveat imperator.

If we want our server to refuse random anonymous clients and only accept clients who have a private key matching a pubkey in our possession, we need to add [Peer] section(s):

[Peer]
PublicKey = PUBLIC_KEY_OF_CLIENT_ONE
AllowedIPs = 10.0.0.2/32

This works… and with it in place, we will no longer accept connections from anonymous clients. If we haven’t specifically authorized the pubkey for a connecting client, it won’t be allowed to send or receive any traffic. (TESTED.)

We can have multiple peers defined, and they’ll all work simultaneously, on the same port on the same server: (TESTED)

# appended to wg0.conf on SERVER

[Peer]
PublicKey = PUBKEY_OF_CLIENT_ONE
AllowedIPs = 10.0.0.2/32

[Peer]
PublicKey = PUBKEY_OF_CLIENT_TWO
AllowedIPs = 10.0.0.3/32

Wireguard won’t dynamically reload wg0.conf looking for new keys, though; so if we’re adding our new peers manually to the config file like this we’ll have to bring the wg0 interface down and back up again to load the changes, with wg-quick down wg0 && wg-quick up wg0. This is definitely not a good way to do things in production at scale, because it means approximately 15 seconds of downtime for existing clients before they automatically reconnect themselves: (TESTED)

64 bytes from 172.29.128.1: icmp_seq=10 ttl=64 time=35.0 ms
64 bytes from 172.29.128.1: icmp_seq=11 ttl=64 time=39.3 ms
64 bytes from 172.29.128.1: icmp_seq=12 ttl=64 time=37.6 ms

[[[       client disconnected due to server restart      ]]]
[[[  16 pings dropped ==> approx 15-16 seconds downtime  ]]]
[[[ client automatically reconnects itself after timeout ]]]

64 bytes from 172.29.128.1: icmp_seq=28 ttl=64 time=51.4 ms
64 bytes from 172.29.128.1: icmp_seq=29 ttl=64 time=37.6 ms

A better way to do things in production is to add our clients manually with the wg command itself. This allows us to dynamically add clients without bringing the server down, and that doing so will also add those clients into wg0.conf for persistence across reboots and what-have-you.

If we wanted to use this method, the CLI commands we’ll need to run on the server look like this: (TESTED)

root@server:/etc/wireguard# wg set wg0 peer CLIENT3_PUBKEY allowed-ips 10.0.0.4/24

The client CLIENT3 will immediately be able to connect to the server after running this command; but its config information won’t be added to wg0.conf, so this isn’t a persistent addition. To make it persistent, we’ll either need to append a [Peer] block for CLIENT3 to wg0.conf manually, or we could use wg-quick save wg0 to do it automatically. (TESTED)

root@server:/etc/wireguard# wg-quick save wg0

The problem with using wg-quick save (which does not require, but shares the limitations of, SaveConfig = true in the wg0.conf itself) is that it strips all comments and formatting, permanently resolves FQDNs to raw IP addresses, and makes some things permanent that you might wish to keep ephemeral (such as ListenPort on client machines). So in production at scale, while you will likely want to use the wg set command to directly add peers to the server, you probably won’t want to use wg-quick save to make the addition permanent; you’re better off scripting something to append a well-formatted [Peer] block to your existing wg0.conf instead.

Once you’ve gotten everything working to your liking, you’ll want to make your wg0 interface come up automatically on boot. On Ubuntu Xenial or later, this is (of course, and however you may feel about it) a systemd thing:

root@box:/etc/wireguard# systemctl enable wg-quick@wg0

This is sufficient to automatically bring up wg0 at boot; but note that since we’ve already brought it up manually with wg-quick up in this session, an attempt to systemctl status wg-quick@wg0 will show an error. This is harmless, but if it bugs you, you’ll need to manually bring wg0 down, then start it up again using systemctl:

root@box:/etc/wireguard# wg-quick down wg0
root@box:/etc/wireguard# systemctl start wg-quick@wg0

At this point, you’ve got a working wireguard interface on server and client(s), that’s persistent across reboots (and other disconnections) if you want it to be.

What we haven’t covered

Note that we haven’t covered getting packets from CLIENT1 to CLIENT2 here – if you try to communicate directly between two clients with this setup and no additional work, you’ll see the following error: (TESTED)

root@client1:/etc/wireguard# ping -c1 CLIENT2
From 10.0.0.2 icmp_seq=1 Destination Host Unreachable
ping: sendmsg: Required key not available
--- 10.0.0.3 ping statistics ---
1 packets transmitted, 0 received, +1 errors, 100% packet loss, time 0ms

We also haven’t looked around at any kind of crypto configuration yet; at this point we’re blindly accepting whatever defaults for algorithms, key sizes, and so forth and hoping for the best. Make sure you understand these (and I don’t, yet!) before deploying in production.

At this point, though, we’ve at least got something working we can play with. Happy hacking, and good luck!

ZFS does NOT favor lower latency devices. Don’t mix rust disks and SSDs!

In an earlier post, I addressed the never-ending urban legend that ZFS writes data to the lowest-latency vdev. Now the urban legend that never dies has reared its head again; this time with someone claiming that ZFS will issue read operations to the lowest-latency disk in a given mirror vdev.

TL;DR – this, too, is a myth. If you need or want an empirical demonstration, read on.

I’ve got an Ubuntu Bionic machine handy with both rust and SSD available; /tmp is an ext4 filesystem on an mdraid1 SSD mirror and /rust is an ext4 filesystem on a single WD 4TB black disk. Let’s play.

root@box:~# truncate -s 4G /tmp/ssd.bin
root@box:~# truncate -s 4G /rust/rust.bin
root@box:~# mkdir /tmp/disks
root@box:~# ln -s /tmp/ssd.bin /tmp/disks/ssd.bin ; ln -s /rust/rust.bin /tmp/disks/rust.bin
root@box:~# zpool create -oashift=12 test /tmp/disks/rust.bin
root@box:~# zfs set compression=off test

Now we’ve got a pool that is rust only… but we’ve got an ssd vdev off to the side, ready to attach. Let’s run an fio test on our rust-only pool first. Note: since this is read testing, we’re going to throw away our first result set; they’ll largely be served from ARC and that’s not what we’re trying to do here.

root@box:~# cd /test
root@box:/test# fio --name=read --ioengine=sync  --rw=randread --bs=16K --size=1G --numjobs=1 --end_fsync=1

OK, cool. Now that fio has generated its dataset, we’ll clear all caches by exporting the pool, then clearing the kernel page cache, then importing the pool again.

root@box:/test# cd ~
root@box:~# zpool export test
root@box:~# echo 3 > /proc/sys/vm/drop_caches
root@box:~# zpool import -d /tmp/disks test
root@box:~# cd /test

Now we can get our first real, uncached read from our rust-only pool. It’s not terribly pretty; this is going to take 5 minutes or so.

root@box:/test# fio --name=read --ioengine=sync  --rw=randread --bs=16K --size=1G --numjobs=1 --end_fsync=1
[ ... ]
Run status group 0 (all jobs):
  READ: bw=17.6MiB/s (18.5MB/s), 17.6MiB/s-17.6MiB/s (18.5MB/s-18.5MB/s), io=1024MiB (1074MB), run=58029-58029msec

Alright. Now let’s attach our ssd and make this a mirror vdev, with one rust and one SSD disk.

root@box:/test# zpool attach test /tmp/disks/rust.bin /tmp/disks/ssd.bin
root@box:/test# zpool status test
  pool: test
 state: ONLINE
  scan: resilvered 1.00G in 0h0m with 0 errors on Sat Jul 14 14:34:07 2018
config:

    NAME                     STATE     READ WRITE CKSUM
    test                     ONLINE       0     0     0
      mirror-0               ONLINE       0     0     0
        /tmp/disks/rust.bin  ONLINE       0     0     0
        /tmp/disks/ssd.bin   ONLINE       0     0     0

errors: No known data errors

Cool. Now that we have one rust and one SSD device in a mirror vdev, let’s export the pool, drop all the kernel page cache, and reimport the pool again.

root@box:/test# cd ~
root@box:~# zpool export test
root@box:~# echo 3 > /proc/sys/vm/drop_caches
root@box:~# zpool import -d /tmp/disks test
root@box:~# cd /test

Gravy. Now, do we see massively improved throughput when we run the same fio test? If ZFS favors the SSD, we should see enormously improved results. If ZFS does not favor the SSD, we’ll not-quite-doubled results.

root@box:/test# fio --name=read --ioengine=sync  --rw=randread --bs=16K --size=1G --numjobs=1 --end_fsync=1
[...]
Run status group 0 (all jobs):
   READ: bw=31.1MiB/s (32.6MB/s), 31.1MiB/s-31.1MiB/s (32.6MB/s-32.6MB/s), io=1024MiB (1074MB), run=32977-32977msec

Welp. There you have it. Not-quite-doubled throughput, matching half – but only half – of the read ops coming from the SSD. To confirm, we’ll do this one more time; but this time we’ll detach the rust disk and run fio with nothing in the pool but the SSD.

root@box:/test# cd ~
root@box:~# zpool detach test /tmp/disks/rust.bin
root@box:~# zpool export test
root@box:~# zpool import -d /tmp/disks test
root@box:~# cd /test

Moment of truth… this time, fio runs on pure solid state:

root@box:/test# fio --name=read --ioengine=sync  --rw=randread --bs=16K --size=1G --numjobs=1 --end_fsync=1
[...]
Run status group 0 (all jobs):
  READ: bw=153MiB/s (160MB/s), 153MiB/s-153MiB/s (160MB/s-160MB/s), io=1024MiB (1074MB), run=6710-6710msec

Welp, there you have it.

Rust only: reads 18.5 MB/sec
SSD only: reads 160 MB/sec
Rust + SSD: reads 32.6 MB/sec

No, ZFS does not read from the lowest-latency disk in a mirror vdev.

Please don’t perpetuate the myth that ZFS favors lower latency devices.

sample netplan config for ubuntu 18.04

Here’s a sample /etc/netplan config for Ubuntu 18.04. HUGE LIFE PRO TIP: against all expectations of decency, netplan refuses to function if you don’t indent everything exactly the way it likes it and returns incomprehensible wharrgarbl errors like “mapping values are not allowed in this context, line 17, column 15” if you, for example, have a single extra space somewhere in the config.

I wish I was kidding.

Anyway, here’s a sample /etc/netplan/01-config.yaml with a couple interfaces, one wired and static, one wireless and dynamic. Enjoy. And for the love of god, get the spacing exactly right; I really wasn’t kidding about it barfing if you have one too many spaces for a whitespace indent somewhere. Ask me how I know. >=\

If for any reason you have trouble reading this exact spacing, the rule is two spaces for each level of indent. So the v in “version” should line up under the t in “network”, the d in “dhcp4” should line up under the o in “eno1”, and so forth.

# This file describes the network interfaces available on your system
# For more information, see netplan(5).
network:
  version: 2
  renderer: networkd
  ethernets:
    eno1:
      dhcp4: no
      dhcp6: no
      addresses: [192.168.0.1/24]
      gateway4: 192.168.0.1
      nameservers:
        addresses: [8.8.8.8, 1.1.1.1]
  wifis:
    wlp58s0:
      dhcp4: yes
      dhcp6: no
      access-points:
        "your-wifi-SSID-name":
          password: "your-wifi-password"

Wait for network to be configured (no limit)

In Ubuntu 16.04 or up (ie, post systemd) if you’re ever stuck staring for two straight minutes at “Waiting for network to be configured (no limit)” and despairing, there’s a simple fix:

systemctl mask systemd-networkd-wait-online.service

This links the service that sits there with its thumb up its butt if you don’t have a network connection to /dev/null, causing it to just return instantly whenever it’s called. Which is probably a good idea. There may indeed be a situation in which I want a machine to refuse to boot until it gets an IP address, but whatever that situation MIGHT be, I’ve never encountered it in 20+ years of professional system administration, so…

Primer: How data is stored on-disk with ZFS

As with a lot of things at this blog, I’m largely writing this to confirm and solidify my own knowledge. I tend to be pretty firm on how disks relate to vdevs, and vdevs relate to pools… but once you veer down deeper into the direct on-disk storage, I get a little hazier. So here’s an attempt to remedy that, with citations, for my benefit (and yours!) down the line.

Top level: the zpool

The zpool is the topmost unit of storage under ZFS. A zpool is a single, overarching storage system consisting of one or more vdevs. Writes are distributed among the vdevs according to how much FREE space each vdev has available – you may hear urban myths about ZFS distributing them according to the performance level of the disk, such that “faster disks end up with more writes”, but they’re just that – urban myths. (At least, they’re only myths as of this writing – 2018 April, and ZFS through 7.5.)

A zpool may be created with one or more vdevs, and may have any number of additional vdevs zpool added to it later – but, for the most part, you may not ever remove a vdev from a zpool. There is working code in development to make this possible, but it’s more of a “desperate save” than something you should use lightly – it involves building a permanent lookup table to redirect requests for records stored on the removed vdevs to their new locations on remaining vdevs; sort of a CNAME for storage blocks.

If you create a zpool with vdevs of different sizes, or you add vdevs later when the pool already has a substantial amount of data in it, you’ll end up with an imbalanced distribution of data that causes more writes to land on some vdevs than others, which will limit the performance profile of your pool.

A pool’s performance scales with the number of vdevs within the pool: in a pool of n vdevs, expect the pool to perform roughly equivalently to the slowest of those vdevs, multiplied by n. This is an important distinction – if you create a pool with three solid state disks and a single rust disk, the pool will trend towards the IOPS performance of four rust disks.

Also note that the pool’s performance scales with the number of vdevs, not the number of disks within the vdevs. If you have a single 12 disk wide RAIDZ2 vdev in your pool, expect to see roughly the IOPS profile of a single disk, not of ten!

There is absolutely no parity or redundancy at the pool level. If you lose any vdev, you’ve lost the entire pool, plain and simple. Even if you “didn’t write to anything on that vdev yet” – the pool has altered and distributed its metadata accordingly once the vdev was added; if you lose that vdev “with nothing on it” you’ve still lost the pool.

It’s important to realize that the zpool is not a RAID0; in conventional terms, it’s a JBOD – and a fairly unusual one, at that.

Second level: the vdev

A vdev consists of one or more disks. Standard vdev types are single-disk, mirror, and raidz. A raidz vdev can be raidz1, raidz2, or raidz3. There are also special vdev types – log and l2arc – which extend the ZIL and the ARC, respectively, onto those vdev types. (They aren’t really “write cache” and “read cache” in the traditional sense, which trips a lot of people up. More about that in another post, maybe.)

A single vdev, of any type, will generally have write IOPS characteristics similar to those of a single disk. Specifically, the write IOPS characteristics of its slowest member disk – which may not even be the same disk on every write.

All parity and/or redundancy in ZFS occurs within the vdev level.

Single-disk vdevs

This is as simple as it gets: a vdev that consists of a single disk, no more, no less.

The performance profile of a single-disk vdev is that of, you guessed it, that single disk.

Single-disk vdevs may be expanded in size by replacing that disk with a larger disk: if you zpool attach a 4T disk to a 2T disk, it will resilver into a 2T mirror vdev. When you then zpool detach the 2T disk, the vdev becomes a 4T vdev, expanding your total pool size.

Single-disk vdevs may also be upgraded permanently to mirror vdevs; just zpool attach one or more disks of the same or larger size.

Single-disk vdevs can detect, but not repair, corrupted data records. This makes operating with single-disk vdevs quite dangerous, by ZFS standards – the equivalent, danger-wise, of a conventional RAID0 array.

However, a pool of single-disk vdevs is not actually a RAID0, and really shouldn’t be referred to as one. For one thing, a RAID0 won’t distribute twice as many writes to a 2T disk as to a 1T disk. For another thing, you can’t start out with a three disk RAID0 array, then add a single two-disk RAID1 array (or three five-disk RAID5 arrays!) to your original array, and still call it “a RAID0”.

It may be tempting to use old terminology for conventional RAID, but doing so just makes it that much more difficult to get accustomed to thinking in terms of ZFS’ real topology, hindering both understanding and communication.

Mirror vdevs

Mirror vdevs work basically like traditional RAID1 arrays – each record destined for a mirror vdev is written redundantly to all disks within the vdev. A mirror vdev can have any number of constituent disks; common sizes are 2-disk and 3-disk, but there’s nothing stopping you from creating a 16-disk mirror vdev if that’s what floats your boat.

A mirror vdev offers usable storage capacity equivalent to that of its smallest member disk; and can survive intact as long as any single member disk survives. As long as the vdev has at least two surviving members, it can automatically repair corrupt records detected during normal use or during scrubbing – but once it’s down to the last disk, it can only detect corruption, not repair it. (If you don’t scrub regularly, this means you may already be screwed when you’re down to a single disk in the vdev – any blocks that were already corrupt are no longer repairable, as well as any blocks that become corrupt before you replace the failed disk(s).

You can expand a single disk to a mirror vdev at any time using the zpool attach command; you can also add new disks to an existing mirror in the same way. Disks may also be detached and/or replaced from mirror vdevs arbitrarily. You may also expand the size of an individual mirror vdev by replacing its disks one by one with larger disks; eg start with a mirror of 2T disks, then replace one disk with a 4T disk, wait for it to resilver, then replace the second 2T disk with another 4T disk. Once there are no disks smaller than 4T in the vdev, and it finishes resilvering, the vdev will expand to the new 4T size.

Mirror vdevs are extremely performant: like all vdevs, their write IOPS are roughly those of a single disk, but their read IOPS are roughly those of n disks, where n is the number of disks in the mirror – a mirror vdev n disks wide can read blocks from all n members in parallel.

A pool made of mirror vdevs closely resembles a conventional RAID10 array; each has write IOPS similar to n/2 disks and read IOPS similar to disks, where n is the total number of disks. As with single-disk vdevs, though, I’d advise you not to think and talk sloppily and call it “ZFS RAID10” – it really isn’t, and referring to it that way blurs the boundaries between pool and vdev, hindering both understanding and accurate communication.

RAIDZ vdevs

RAIDZ vdevs are striped parity arrays, similar to RAID5 or RAID6. RAIDZ1 has one parity block per stripe, RAIDZ2 has two parity blocks per stripe, and RAIDZ3 has three parity blocks per stripe. This means that RAIDZ1vdevs can survive loss of a single disk, RAIDZ2 can survive the loss of two disks, and RAIDZ3 vdevs can survive the loss of as many as three disks.

Note, however, that – just like mirror vdevs – once you’ve stripped away all the parity, you’re vulnerable to corruption that can’t be repaired. RAIDZ vdevs take typically take significantly longer to resilver than mirror vdevs do, as well – so you really don’t want to end up completely “uncovered” (surviving, but with no remaining parity blocks) with a RAIDZ array.

Each raidz vdev offers n-(parity*n) storage capacity, where n is the storage capacity of a single disk, and parity is the number of parity blocks per stripe. So a six-disk RAIDZ1 vdev offers the storage capacity of five disks, an eight-disk RAIDZ2 vdev offers the storage capacity of six disks, and so forth.

You may create RAIDZ vdevs using mismatched disk sizes, but the vdev’s capacity will be based around the smallest member disk. You can expand the size of an existing RAIDZ vdev by replacing all of its members individually with larger disks than were originally used, but you cannot expand a RAIDZ vdev by adding new disks to it and making it wider – a 5-disk RAIDZ1 vdev cannot be converted into a 6-disk RAIDZ1 vdev later; neither can a 6-disk RAIDZ2 be converted into a 6-disk RAIDZ1.

It’s a common misconception to think that RAIDZ vdev performance scales linearly with the number of disks used. Although throughput under ideal conditions can scale towards n-parity disks, throughput under moderate to serious load will rapidly degrade toward the profile of a single disk – or even slightly worse, since it scales down toward the profile of the slowest disk for any given operation. This is the difference between IOPS and bandwidth (and it works the same way for conventional RAID!)

RAIDZ vdev IOPS performance is generally more robust than that of a conventional RAID5 or RAID6 array of the same size, because RAIDZ offers variable stripe write sizes – if you routinely write data in records only one record wide, a RAIDZ1 vdev will write to only two of its disks (one for data, and one for parity); a RAIDZ2 vdev will write to only three of its disks (one for data, and two for parity) and so on. This can mitigate some of the otherwise-crushing IOPS penalty associated with wide striped arrays; a three-record variable stripe write to a six-disk RAIDZ vdev only lights up half the disks both when written, and later, when read – which can make the performance profile of that six-disk RAIDZ resemble that of two three-disk RAIDZ1 vdevs rather than that of a single vdev.

The performance improvement described above assumes that multiple reads and writes of the three-record stripes are being requested concurrently; otherwise the entire vdev still binds while waiting for a full-stripe read or write.

Remember that you can – and with larger servers, should – have multiple RAIDZ vdevs per pool, not just one. A pool of three eight-disk RAIDZ2 vdevs will significantly outperform a pool with a single 24-disk RAIDZ2 or RAIDZ3 vdev – and it will resilver much faster when replacing failed disks.

Third level: the metaslab

Each vdev is organized into metaslabs – typically, 200 metaslabs per vdev (although this number can change, if vdevs are expanded and/or as the ZFS codebase itself becomes further optimized over time).

When you issue writes to the pool, those writes are coalesced into a txg (transaction group), which is then distributed among individual vdevs, and finally allocated to specific metaslabs on each vdev. There’s a fairly hefty logic chain which determines exactly what metaslab a record is written to; it was explained to me (with no warranty offered) by a friend who worked with Oracle as follows:

• Is this metaslab “full”? (zfs_mg_noalloc_threshold)
• Is this metaslab excessively fragmented? (zfs_metaslab_fragmentation_threshold)
• Is this metaslab group excessively fragmented? (zfs_mg_fragmentation_threshold)
• Have we exceeded minimum free space thresholds? (metaslab_df_alloc_threshold) This one is weird; it changes the whole storage pool allocation strategy for ZFS if you cross it.
• Should we prefer lower-numbered metaslabs over higher ones? (metaslab_lba_weighting_enabled) This is totally irrelevant to all-SSD pools, and should be disabled there, because it’s pretty stupid without rust disks underneath.
• Should we prefer lower-numbered metaslab groups over higher ones? (metaslab_bias_enabled) Same as above.

You can dive into the hairy details of your pool’s metaslabs using the zdb command – this is a level which I have thankfully not personally needed so far, and I devoutly hope I will continue not to need it in the future.

Fourth level: the record

Each ZFS write is broken into records, the size of which is determined by the zfs set recordsize=command. The default recordsize is currently 128K; it may range from 512B to 1M.

Recordsize is a property which can be tuned individually per dataset, and for higher performance applications, should be tuned per dataset. If you expect to largely be moving large chunks of contiguous data – for example, reading and writing 5MB JPEG files – you’ll benefit from a larger recordsize than default. Setting recordsize=1M here will allow your writes to be less fragmented, resulting in higher performance both when making the writes, and later when reading them.

Conversely, if you expect a lot of small-block random I/O – like reading and writing database binaries, or VM (virtual machine) images – you should set recordsize smaller than the default 128K. MySQL, as an example, typically works with data in 16K chunks; if you set recordsize=16K you will tremendously improve IOPS when working with that data.

ZFS CSUMs – cryptographic hashes which verify its data’s integrity – are written on a per-record basis; data written with recordsize=1M will have a single CSUM per 1MB; data written with recordsize=8K will have 128 times as many CSUMs for the same 1MB of data.

Setting recordsize to a value smaller than your hardware’s individual sector size is a tremendously bad idea, and will lead to massive read/write amplification penalties.

Fifth (and final) level: ashift

Ashift is the property which tells ZFS what the underlying hardware’s actual sector size is. The individual blocksize within each record will be determined by ashift; unlike recordsize, however, ashift is set as a number of bits rather than an actual number.  For example, ashift=13 specifies 8K sectors, ashift=12 specifies 4K sectors, and ashift=9 specifies 512B sectors.

Ashift is per vdev, not per pool – and it’s immutable once set, so be careful not to screw it up!  In theory, ZFS will automatically set ashift to the proper value for your hardware; in practice, storage manufacturers very, very frequently lie about the underlying hardware sector size in order to keep older operating systems from getting confused, so you should do your homework and set it manually. Remember, once you add a vdev to your pool, you can’t get rid of it; so if you accidentally add a vdev with improper ashift value to your pool, you’ve permanently screwed up the entire pool!

Setting ashift too high is, for the most part, harmless – you’ll increase the amount of slack space on your storage, but unless you have a very specialized workload this is unlikely to have any significant impact. Setting ashift too low, on the other hand, is a horrorshow. If you end up with an ashift=9 vdev on a device with 8K sectors (thus, properly ashift=13), you’ll suffer from massive write amplification penalties as ZFS needs to write, read, rewrite again over and over on the same actual hardware sector. I have personally seen improperly set ashift cause a pool of Samsung 840 Pro SSDs perform slower than a pool of WD Black rust disks!

Even if you’ve done your homework and are absolutely certain that your disks use 512B hardware sectors, I strongly advise considering setting ashift=12 or even ashift=13 – because, remember, it’s immutable per vdev, and vdevs cannot be removed from pools. If you ever need to replace a 512B sector disk in a vdev with a 4K or 8K sector disk, you’ll be screwed if that vdev is ashift=9.

How data gets imbalanced on ZFS

In an earlier post, I demonstrated that ZFS distributes writes evenly across vdevs according to FREE space per vdev (not based on latency or anything else: just FREE).

There are three ways I know of that you can end up with an imbalanced distribution of data across your vdevs. The first two are dead obvious; the third took a little head-scratching and empirical testing before I was certain of it.

Different-sized vdevs

If you used vdevs of different sizes in the first place, you end up with more data on the larger vdevs than the smaller vdevs.

This one’s a no-brainer: we know that ZFS will distribute writes according to the amount of FREE on each vdev, so if you create a pool with one 1T vdev and one 2T vdev, twice as many writes will go on the 2T vdev as the 1T vdev; natch.

Vdevs ADDed after data was already written to the pool

If you zpool add one or more vdevs to an existing pool that already has data on it, ZFS isn’t going to redistribute the writes you already made to the older vdevs.

For example, let’s say you create a pool with a single 2T vdev, write 1T of data to it, then add another 2T vdev. You’ve got 1T FREE on one vdev and 2T FREE on the other vdev; ZFS will now write two records to the new vdev for every one record it writes to the old one; this means that while your writes will remain imbalanced for the rest of the pool’s life, each vdev will become full at about the same time.

You might ask, why not bias writes to the new vdevs even more heavily, so that they achieve balance before the pool’s full? The answer is consistency. If you distribute two writes to a 2T FREE vdev for every one write to a 1T FREE vdev, you have a consistent write performance profile for the remainder of the life of the pool, rather than a really bad performance profile either now (if you bias all the writes to the vdev with more FREE) or at the end of the pool’s life (if you deliver writes evenly until one vdev is entirely full, then have no choice but to send all writes to the one vdev that still has FREEspace remaining).

Balanced writes, imbalanced deletes

OK, this is the fun one. Let’s say you create a pool with two equally-sized vdevs, and a year later you look at it and you’ve got imbalanced writes. What gives?

Well, this is going to be more likely the larger your recordsize is, since as far as I can tell each record is written to a single vdev (not split across the pool as a whole in ashift-sized blocks). Basically, although ZFS wrote your data balanced across your equally-sized vdevs, you deleted more records from one vdev than another.

To demonstrate this effect (and give myself a sanity check!), I created a pool with two equally-sized 500GB vdevs, set recordsize=1M, and wrote a ton of 900K files to the pool.

root@banshee:~# zpool create -oashift=13 alloctest /ssd/alloctest/disk1.raw /rust/alloctest/disk2.raw
root@banshee:~# zfs set recordsize=1M alloctest

root@banshee:~# for i in {1..3636} do ; cp /tmp/900K.bin /alloctest/$i.bin ; done

root@banshee:~# zpool iostat -v alloctest
                               capacity   operations  bandwidth
pool                          alloc free  read  write read write
----------------------------- ----- ----- ----- ----- ----- -----
alloctest                     3.14G 989G  0     45    4.07K 14.2M
 /rust/alloctest/disk1.raw    1.57G 494G  0     22    2.04K 7.10M
 /ssd/alloctest/disk2.raw     1.57G 494G  0     22    2.04K 7.09M
----------------------------- ----- ----- ----- ----- ----- -----

As expected, these files are balanced equally across each vdev in the pool… even though one of the vdevs is much, much faster than the other, since they had the same FREE space available.

Now, we write a tiny bit of Perl to delete only the even-numbered files from alloctest

#!/usr/bin/perl

opendir (my $dh, "/alloctest") || die "Can't open directory: $!";

while (readdir $dh) { 
    my $file = $_; 
    $file =~ s/\.bin$// ; 
    if ($file/2 == int($file/2)) { 
        # this is an even-numbered file - delete it
        unlink "/alloctest/$file.bin"; 
    }
}

closedir $dh;

Now we run our little bit of Perl, delete the even-numbered files only, and see if we’re left with imbalanced data:

root@banshee:~# perl ~/deleteevens.pl

root@banshee:~# zpool iostat -v alloctest
                               capacity   operations  bandwidth
pool                          alloc free  read  write read write
----------------------------- ----- ----- ----- ----- ----- -----
alloctest                     1.57G 990G  0     24    2.13K 7.44M
 /rust/alloctest/disk1.raw    12.3M 496G  0     12    1.07K 3.72M
 /ssd/alloctest/disk2.raw     1.56G 494G  0     12    1.07K 3.72M
----------------------------- ----- ----- ----- ----- ----- -----

Bingo! 12.3M ALLOCed on disk1, and 1.56G ALLOCed on disk2 – it took some careful planning, but we now have imbalanced data on a pool with equally-sized vdevs that have been present since the pool’s creation.

However, it’s not imbalanced because ZFS wrote it that way, it’s imbalanced because we deleted it that way.  By deleting all the even-numbered files, we got rid of the files on /ssd/alloctest/disk1.raw while leaving all the files (actually, all the records) on /ssd/alloctest/disk2.rawintact. And since ZFS allocates writes according to FREE per vdev, we know that our data will slowly creep back into balance, as ZFS favors the vdev with a higher FREE count on new writes.

In practice, most people shouldn’t see a really large imbalance like this in normal usage, even with a large recordsize. I had to pretty specifically gimmick this scenario up to save files right at the desired recordsize and then delete them very specifically in a pattern which would produce the results I was looking for; organic deletions should be very unlikely to create a large imbalance.

ZFS allocates writes according to free space per vdev, not latency per vdev

I frequently see the mistaken idea popping up that ZFS allocates writes to the quickest vdev to respond. This isn’t the case: ZFS allocates pool writes in proportion to the amount of free space available on each vdev, so that the vdevs will become full at roughly the same time regardless of how small or large each was to begin with.

Testing: one large slow vdev, one small fast vdev

We can demonstrate this quickly and easily. Below, I use the truncate command to create raw storage files on two pools: rust and ssd.  By creating a 10G storage file on rust and a 2G storage file on ssd, we will see quickly whether ZFS prefers to allocate data according to free space or to latency: the ssd storage is tremendously lower latency, but the size of the device on the rust is larger.

root@banshee:~# zfs create ssd/alloctest
root@banshee:~# zfs create rust/alloctest
root@banshee:~# zfs set compression=off ssd/alloctest
root@banshee:~# zfs set compression=off rust/alloctest
root@banshee:~# truncate -s 10G /rust/alloctest/10Grust.raw
root@banshee:~# truncate -s 2G /ssd/alloctest/2Gssd.raw
root@banshee:~# zpool create -oashift=13 alloctest /rust/alloctest/10Grust.raw /ssd/alloctest/2Gssd.raw
root@banshee:~# zfs set compression=off alloctest

root@banshee:~# zpool list -v alloctest
NAME                          SIZE  ALLOC FREE EXPANDSZ FRAG CAP DEDUP HEALTH ALTROOT
alloctest                     11.9G 672K  11.9G -       0%   0% 1.00x ONLINE -
 /rust/alloctest/10Grust.raw  9.94G 416K  9.94G -       0%   0%
 /ssd/alloctest/2Gssd.raw     1.98G 256K  1.98G -       0%   0%

OK, now we’ve got our lopsided pool “alloctest”, which has one very fast 2G vdev and one much slower 10G vdev. Let’s see what happens when we dump 2GB of data into it:

root@banshee:~# dd if=/dev/zero bs=256M count=8 of=/alloctest/2G.bin
8+0 records in
8+0 records out
2147483648 bytes (2.1 GB, 2.0 GiB) copied, 16.6184 s, 129 MB/s

root@banshee:~# zpool list -v alloctest
NAME                          SIZE  ALLOC FREE EXPANDSZ FRAG CAP DEDUP HEALTH ALTROOT
alloctest                     11.9G 2.00G 9.92G -       9%   16% 1.00x ONLINE -
 /rust/alloctest/10Grust.raw  9.94G 1.56G 8.37G -       9%   15%
 /ssd/alloctest/2Gssd.raw     1.98G 451M  1.54G -       13%  22%

We’ve ALLOC’d 451M to the smaller vdev, and 1.56G to the larger vdev – a ratio of 3.54:1, quite close to the 5:1 ratio of the storage sizes themselves.

What if we dump more data in?

root@banshee:~# dd if=/dev/zero bs=256M count=12 of=/alloctest/3G.bin
12+0 records in
12+0 records out
3221225472 bytes (3.2 GB, 3.0 GiB) copied, 29.0672 s, 111 MB/s

root@banshee:~# zpool list -v alloctest
NAME                          SIZE  ALLOC FREE  EXPANDSZ FRAG CAP DEDUP HEALTH ALTROOT
alloctest                     11.9G 5.01G 6.91G -        24%  42% 1.00x ONLINE -
 /rust/alloctest/10Grust.raw  9.94G 3.92G 6.02G -        23%  39%
 /ssd/alloctest/2Gssd.raw     1.98G 1.09G 916M  -        34%  54%

3.92G to 1.09G – 3.59 to 1, or no real change. Let’s fill the pool literally to bursting:

root@banshee:~# dd if=/dev/zero bs=256M count=48 of=/alloctest/12G.bin
dd: error writing '/alloctest/12G.bin': No space left on device
27+0 records in
26+0 records out
7014973440 bytes (7.0 GB, 6.5 GiB) copied, 99.4393 s, 70.5 MB/s

root@banshee:~# zpool list -v alloctest
NAME                          SIZE  ALLOC FREE  EXPANDSZ FRAG CAP DEDUP HEALTH ALTROOT
alloctest                     11.9G 11.5G 381M  -        58%  96% 1.00x ONLINE -
 /rust/alloctest/10Grust.raw  9.94G 9.61G 330M  -        58%  96%
 /ssd/alloctest/2Gssd.raw     1.98G 1.93G 50.8M -        61%  97%

With the pool entirely full, we have a ratio of 4.98:1 – still not quite the exact 5:1 ratio of our vdevs’ sizes, but pretty damn close.

Testing: one large fast vdev, one small slow vdev

OK… now what if we repeat the same experiment, but this time we put the big vdev on ssd and the little one on rust?

root@banshee:~# truncate -s 10G /ssd/alloctest/10Gssd.raw
root@banshee:~# truncate -s 2G /rust/alloctest/2Grust.raw
root@banshee:~# zpool create -oashift=13 alloctest /ssd/alloctest/10Gssd.raw /rust/alloctest/2Grust.raw
root@banshee:~# zfs set compression=off alloctest

root@banshee:~# zpool list -v alloctest
NAME                        SIZE  ALLOC FREE  EXPANDSZ FRAG CAP DEDUP HEALTH ALTROOT
alloctest                   11.9G 552K  11.9G -        0%   0% 1.00x ONLINE -
 /ssd/alloctest/10Gssd.raw  9.94G 336K  9.94G -        0%   0%
 /rust/alloctest/2Grust.raw 1.98G 216K  1.98G -        0%   0%

OK, the tables have turned. Now we’ve got a 12G pool with 10G of the storage on fast SSD, and 2G of the storage on slow rust. Let’s dump data in it:

root@banshee:~# dd if=/dev/zero bs=256M count=8 of=/alloctest/2G.bin
8+0 records in
8+0 records out
2147483648 bytes (2.1 GB, 2.0 GiB) copied, 13.5287 s, 159 MB/s

root@banshee:~# zpool list -v alloctest
NAME                        SIZE  ALLOC FREE  EXPANDSZ FRAG CAP DEDUP HEALTH ALTROOT
alloctest                   11.9G 1.98G 9.95G -        9%   16% 1.00x ONLINE -
 /ssd/alloctest/10Gssd.raw  9.94G 1.55G 8.39G -        9%   15%
 /rust/alloctest/2Grust.raw 1.98G 440M  1.56G -        13%  21%

1.55G to 440M – 3.6:1. That’s a pretty familiar ratio, isn’t it? Let’s dump another 3G of data in, just like we did earlier, when the big vdev was rust:

root@banshee:~# dd if=/dev/zero bs=256M count=12 of=/alloctest/3G.bin
12+0 records in
12+0 records out
3221225472 bytes (3.2 GB, 3.0 GiB) copied, 23.5282 s, 137 MB/s

root@banshee:~# zpool list -v alloctest
NAME                        SIZE  ALLOC FREE  EXPANDSZ FRAG CAP DEDUP HEALTH ALTROOT
alloctest                   11.9G 5.01G 6.91G -        25%  42% 1.00x ONLINE -
 /ssd/alloctest/10Gssd.raw  9.94G 3.92G 6.02G -        24%  39%
 /rust/alloctest/2Grust.raw 1.98G 1.09G 916M  -        34%  54%

1.09G to 3.92G ALLOCated… simplified, that’s 3.6:1 again. Just like it was when the big vdev was rust and the small vdev was ssd.

What about high-IOPS, small random writes?

For this one, I set up equally-sized vdevs on rust and ssd, created a pool with no compression, and began populating them with 4K synchronously written files, which is just about the maximum IOPS load you can put on a pool:

root@banshee:~# for i in {1..1048576}
> do
> cp /tmp/4K.bin /alloctest/$i.bin
> sync
> done

This gives us a stream of steady 4K synchronous writes to the pool (as ensured by that sync command in the loop).

Checking zpool iostat -v alloctest while the data is streaming onto the pool confirms that the writes are balanced equally between the equal-sized drives, even though we’re doing 4K writes, and one of the vdevs is an Intel 480GB SSD and the other is WD Red 4TB rust drive:

root@banshee:~# zpool iostat -v alloctest
 capacity operations bandwidth
pool                          alloc free  read  write read  write
----------------------------- ----- ----- ----- ----- ----- -----
alloctest                     4.57G 987G  171   334   1.34M 6.12M
 /ssd/alloctest/500G.raw      2.29G 494G  85    172   683K  3.08M
 /rust/alloctest/500G.raw     2.28G 494G  85    161   685K  3.05M
----------------------------- ----- ----- ----- ----- ----- -----

There’s no significant difference: each device is receiving roughly the same number of operations, and the same amount of bandwidth, at any given second; and we’re accumulating the same amount of data on each same-sized vdev.

The rule of thumb – as we’re seeing here – is that writes to any given vdev bind on the slowest disk in the vdev, and writes to a pool bind on the slowest vdev in the pool. In this case, we’re binding on the performance of the rust vdev. The reason we’re binding on that slower vdev is to keep the pool from filling imbalanced.

Conclusion

ZFS allocates writes to the pool according to the amount of free space left on each vdev, period. With the small vdev sizes we used for testing here, this didn’t result in a “perfect” allocation ratio exactly matching our vdev sizes – but the “imperfect” ratio we got was the same whether the smaller vdev was the slower one or the faster one. And when we tested with 4K synchronous writes to a pool with evenly sized vdevs, the throughput bound to the slower of the two vdevs, and we could see the data moving at the same pace onto each of those vdevs – not allocated according to their individual capacities.

This should remove any confusion about whether ZFS (at least, as of 0.6.5.6) “prefers” faster/lower latency vdevs when allocating writes. It does not.

If you’re frowning because you’ve got an imbalanced distribution of data across your pool and not sure how it happened, see here.