10/20/40Gbps nginx large files caching webserver [20Gbps reached]
I would like to find out the best possible configuration/hardware to deliver 40Gbps from a single server in this question.
Situation
We have a video share proxy server that offloads peaks from slow storage servers behind it. All traffic is HTTP only. The server acts as a reverse proxy (files that are not cached on the server) and a webserver (files that are stored on local drives).
There are currently something like 100TB of files and growing on the backend storage servers.
The caching mechanism is implemented independently and this question is not about caching itself as it works very well - currently delivers 14Gbps, passes to the backend servers only 2Gbps. So the cache usage is good.
Goal
Achieve 40Gbps or even more throughput from a single machine.
Hardware 1
HW: Supermicro SC825, X11SSL-F, Xeon E3-1230v5 (4C/[email protected]), 16GB DDR4 RAM, 2x Supermicro 10G STGN-i1S (LACP L3+4)
SSD: 1x 512GB Samsung, 2x 500GB Samsung, 2x480GB Intel 535, 1x 240GB Intel S3500
System:
- irqbalancer stopped
- set_irq_affinity for each interface (via script in ixgbe driver tarball)
- ixgbe-4.3.15
- I/O scheduler deadline
- iptables empty (unloaded modules)
- Filesystem: XFS
Nginx:
- sendfile off
- aio threads
- directio 1M
- tcp_nopush on
- tcp_nodelay on
As seen on the graphs, we were able to push 12.5Gbps. Unfortunately the server was unresponsive.
There are 2 things that took my attention. The first one is high amount of IRQ. In this case I don't unfortunately have graphs from /proc/interrupts. The second thing was high system load, which I think was caused by kswapd0 having problems to work with 16G of RAM only.
Hardware 2
HW: Supermicro SC119TQ, X10DRW-i, 2x Xeon E5-2609v4 (8C/[email protected]), 128GB DDR4 RAM, 2x Supermicro 10G STGN-i1S
SSD, System configuration are the same as hardware 1. Nginx is sendfile on (aio/sendfile compared further).
This seems better, so now as we a have server, which works in peaks, we can try some optimizations.
Sendfile vs aio threads
I tried to disable sendfile and use aio threads instead.
- sendfile off
- aio threads
- directio 1M (which matches all files we have)
vs
- sendfile on
Then at 15:00 I switched back to sendfile and reloaded nginx (so it took a while to finish existing connections). It is nice that the drive utilization (measured by iostat) went down. Nothing has changed on the traffic (unfortunately zabbix decided not to collect the data from bond0).
sendfile on/off
Just tried to switch send on/off. Nothing has changed except Rescheduling interrupts.
irqbalancer as a server/cron/disabled
As @lsd mentioned I tried to setup irqbalancer to be executed via cron:
*/5 * * * * root /usr/sbin/irqbalance --oneshot --debug 3 > /dev/null
Unfortunately it didn't help in my case. One of the network cards started behaving strange:
I couldn't find what was wrong in graphs and as it happened the next day again, I logged in to the server and saw that one core was at 100% (system usage).
I tried to start irqbalance as a service, the result was still the same.
Then I decided to use the set_irq_affinity script and it fixed the problem immediately and server pushed 17Gbps again.
Hardware 3
We did upgrade to new hardware: 2U 24 (+2) drives chassis (6xSFF), 2x Xeon E5-2620v4, 64GB DDR4 RAM (4x16GB modules), 13x SSD, 2x Supermicro (with Intel chip) network cards. New CPUs improved the performance a lot.
Current setup remains - sendfile, etc. Only difference is that we let only a single CPU handle both network cards (via set_irq_affinity script).
20Gbps limit has been reached.
Next goal? 30Gbps.
Feel free to shoot at me ideas how to improve the performance. I will be happy to test it live and share some heavy graphs in here.
Any ideas how to deal with large amount of SoftIRQs on the cpu?
This is not a question about capacity planning - I already have the hardware and the traffic. I can always split the traffic to several servers (which I will have to do in the future anyway) and fix the problem with money. This is however a question about system optimization and performance tunning in a real live scenario.
Disclaimer: The same advice applies to all services pushing more than 10Gbps. Included but not limited to load balancers, caching servers, webservers (HAProxy, Varnish, nginx, tomcat, ...)
What you want to do is wrong, don't do it
Use a CDN instead
CDN are meant to deliver cachable static content. Use the right tool for the job (akamai, MaxCDN, cloudflare, cloudfront, ...)
Any CDN, even a free one, will do better than whatever you can achieve on your own.
Scale horizontally instead
I expect a single server to handle 1-5Gbps out-of-the-box without much tweaking (note: serving static files only). The 8-10Gbps is usually within reach with advanced tuning.
Nonetheless there are many hard limits to what a single box can take. You should prefer to scale horizontally.
Run a single box, try things, measure, benchmark, optimize... until that box is reliable and dependable and its capabilities are well determined, then put more boxes like it with a global load balancer in front.
There are a few global load balancing options: most CDN can do that, DNS roundrobin, ELB/Google load balancers...
Let's ignore the good practices and do it anyway
Understanding the traffic pattern
WITHOUT REVERSE PROXY
[request ] user ===(rx)==> backend application
[response] user <==(tx)=== [processing...]
There are two things to consider: the bandwidth and the direction (emission or reception).
Small files are 50/50 tx/rx because the HTTP headers and TCP overhead are bigger than the file content.
Big files are 90/10 tx/rx because the request size is negligible compared to the response size.
WITH REVERSE PROXY
[request ] user ===(rx)==> nginx ===(tx)==> backend application
[response] user <==(tx)=== nginx <==(rx)=== [processing...]
The reverse proxy is relaying all messages in both directions. The load is always 50/50 and the total traffic is doubled.
It gets more complex with caching enabled. Requests may be diverted to the hard drive, whose data may be cached in memory.
Note: I'll ignore the caching aspect in this post. We'll focus on getting 10-40 Gbps on the network. Knowing whether the data come from the cache and optimizing that cache is another topic, it's pushed over the wire either way.
Monocore limitations
Load balancing is monocore (especially TCP balancing). Adding cores doesn't make it faster but it can make it slower.
Same for HTTP balancing with simple modes (e.g. IP, URL, cookie based. The reverse proxy reads headers on the fly, it doesn't parse nor process HTTP requests in a strict sense).
In HTTPS mode, the SSL decryption/encryption is more intensive than everything else required for the proxying. SSL traffic can and should be split over multiple cores.
SSL
Given that you do everything over SSL. You'll want to optimize that part.
Encrypting and decrypting 40 Gbps on the fly is quite an achievement.
Take a latest generation processor with the AES-NI instructions (used for SSL operations).
Tune the algorithm used by the certificates. There are many algorithms. You want the one that is the most effective on your CPU (do benchmarking) WHILE being supported by clients AND being just secure enough (no necessary over-encryption).
IRQ and core pinning
The network card is generating interrupts (IRQ) when there is new data to read and the CPU is pre-empted to immediately handle the queue. It's an operation running in the kernel and/or the device drivers and it's strictly monocore.
It can be the greatest CPU consumer with billions of packets going out in every directions.
Assign the network card a unique IRQ number and pin it down to a specific core (see linux or BIOS settings).
Pin the reverse proxy to other cores. We don't want these two things to interfere.
Ethernet Adapter
The network card is doing a lot of the heavy lifting. All devices and manufacturers are not equal when it comes to performances.
Forget about the integrated adapter on motherboards (doesn't matter if server or consumer motherboard), they just suck.
TCP Offloading
TCP is a very intensive protocol in terms of processing (checksums, ACK, retransmission, reassembling packets, ...) The kernel is handling most of the work but some operations can be offloaded to the network card if it supports it.
We don't want just a relatively fast card, we want one with all the bells and whistles.
Forget about Intel, Mellanox, Dell, HP, whatever. They don't support all of that.
There is only one option on the table: SolarFlare -- The secret weapon of HFT firms and CDN.
The world is split in two kind of people: "The ones who know SolarFlare" and "the ones who do not". (the first set being strictly equivalent to "people who do 10 Gbps networking and care about every bit"). But I digress, let's focus :D
Kernel TCP tuning
There are options in sysctl.conf
for kernel network buffers. What these settings do or not do. I genuinely don't know.
net.core.wmem_max
net.core.rmem_max
net.core.wmem_default
net.core.rmem_default
net.ipv4.tcp_mem
net.ipv4.tcp_wmem
net.ipv4.tcp_rmem
Playing with these settings is the definitive sign of over optimization (i.e. generally useless or counter productive].
Exceptionally, that might make sense given the extreme requirements.
(Note: 40Gbps on a single box is over-optimization. The reasonable route is to scale horizontally.)
Some Physical Limits
Memory bandwidth
Some numbers about memory bandwidth (mostly in GB/s): http://www.tweaktown.com/articles/6619/crucial-ddr4-memory-performance-overview-early-look-vs-ddr2-ddr3/index.html
Let's say the range is 150-300 Gbps for memory bandwidth (maximum limit in ideal conditions).
All packets have to be in the memory at some point. Just ingesting data at a 40 Gbps line rate is a heavy load on the system.
Will there be any power left to process the data? Well, let's not get our expectations too high on that. Just saying ^^
PCI-Express bus
PCIe 2.0 is 4 Gb/s per lane. PCIe 3.0 is 8 Gbps per lane (not all of it is available for the PCI card).
A 40 Gbps NIC with a single Ethernet port is promising more than the PCIe bus if the connector is anything less than 16x length on the v3.0 specifications.
Other
We could go over other limits. The point is that hardware have hard limitations inherent to the law of physics.
Software can't do better than the hardware it's running on.
The network backbone
All these packets have to go somewhere eventually, traversing switches and routers. The 10 Gbps switches and router are [almost] a commodity. The 40 Gbps are definitely not.
Also, the bandwidth has to be end-to-end so what kind of links do you have up to the user?
Last time I checked with my datacenter guy for a little 10M users side project, he was pretty clear that there would be only 2x 10 Gbits links to the internet at most.
Hard drives
iostat -xtc 3
Metrics are split by read and write. Check for queue (< 1 is good), latency (< 1 ms is good) and transfer speed (the higher the better).
If the disk is slow, the solution is to put more AND bigger SSD in raid 10. (note that SSD bandwidth increases linearly with SSD size).
CPU choice
IRQ and other bottlenecks only run on one core so aim for the CPU with the highest single core performances (i.e. highest frequency).
SSL encryption/decryption need the AES-NI instructions so aim for the latest revision of CPU only.
SSL benefit from multiple cores so aim for many cores.
Long story short: The ideal CPU is the newest one with the highest frequency available and many cores. Just pick the most expensive and that's probably it :D
sendfile()
Sendfile ON
Simply the greatest progress of modern kernels for high performance webservers.
Final Note
1 SolarFlare NIC 40 Gbps (pin IRQ and core)
2 SolarFlare NIC 40 Gbps (pin IRQ and core)
3 nginx master process
4 nginx worker
5 nginx worker
6 nginx worker
7 nginx worker
8 nginx worker
...
One thing pinned down to one CPU. That's the way to go.
One NIC leading to the external world. One NIC leading to the internal network. Splitting responsibilities is always nice (though dual 40 Gbps NIC may be overkill).
That's a lot of things to fine tuned, some of which could be the subject of a small book. Have fun benchmarking all of that. Come back to publish the results.