tl;dr: EFS is NFS. Networked file systems have inherent tradeoffs over local filesystem access—EFS doesn't change that. Don't expect the moon, benchmark and monitor it, and you'll do fine.
On a recent project, I needed to have a shared network file system that was available to all servers, and able to scale horizontally to anywhere between 1 and 100 servers. It needed low-latency file access, and also needed to be able to handle small file writes and file locks synchronously with as little latency as possible.
Amazon EFS, which uses NFS v4.1, checks all of those checkboxes (at least, to a certain extent), and if you're already building infrastructure inside AWS, EFS is a very cost-effective way to manage a scalable NFS filesystem. I'm not going to go too much into the technical details of EFS or NFS v4.1, but I would like to highlight some of the painful lessons my team has learned implementing EFS for a fairly hefty CMS-based project.
Monitor EFS Burst Credits
I'm pretty sure this is one of the most mentioned suggestions in every guide to using EFS I've seen. And it's par for the course with AWS offerings—you can usually start out using the free/cheap tier of a service, but once you start putting production loads on the service, you'll have your first major outage with no discernible cause.
That is, if you're not monitoring burst credits.
My team spent over an hour trying to diagnose why MySQL connections were stacking up, application threads were clogged, and extremely few requests were getting responses. Finally, we noticed that file operations were really slow. Really really slow. And then I remembered I had built a dashboard in our monitoring system for EFS, so I looked there, found that our Burst Credits were expired, and our Permitted Throughput went from 50 Mbps to 0.5 Mbps. And this was in the middle of a full EFS backup (more on that later!).
So, make sure you add alerts in CloudWatch or elsewhere on your BurstCreditBalance. If it starts going down, make sure it doesn't keep going down. And if you need more burst credits, or a higher normal throughput limit, see the next section:
Write dummy data to get better performance
NOTE: As of July 2018, EFS now supports Provisioned Throughput. For many people, this is a better way to guarantee a certain level of performance instead of writing large files to your EFS filesystem.
For most AWS services (well, at least all the ones predicated on instances and/or clusters), you can always upsize your instances, or change from network-optimized to CPU-optimized, or RAM-optimized, or GPU-optimized.
For EFS, there is no 'instance class'. The only real control you have over what kind of I/O limits you have is switching between 'general performance' (good for low latency, high horizontal scalability), or 'max IO' (good for larger volumes of data transfer, but with slightly higher latency).
When you create a new EFS volume, you get a paltry .5 MB/s sustained transfer rate, and 7.2 minutes worth of burst credits (up to 100 MB/s). How do you increase these limits? You write a giant file to the filesystem, and EFS takes up to an hour to increase your limits, according to this chart (taken from the EFS Performance page):
Lesson learned: Immediately after creating a new EFS volume, mount it somewhere, and write a large file to it (or many smaller files if you want to delete some of this 'dummy data' as your data usage expands):
sudo dd if=/dev/urandom of=test_large_file bs=1024k count=256000 status=progress
Be sure to exclude such files from any backups you take, otherwise you'll be paying for more backup space, as well as all that extra transfer bandwidth to back up the large file that gives you the bandwidth in the first place! I've asked AWS about any chance to create volumes and not have to write big files to jump to higher IO stats (after all, you don't start on a t2.micro instance when you sign up for a beefy c5.4xlarge in EC2!). If you want to pay up front for the performance, it seems odd that AWS won't allow it. I know many people who have been burned by this same problem.
Don't even think about running app code from EFS
I see a lot of people try to use EFS (or NFS in general) as a jerry-rigged deployment mechanism so they can manage a codebase in one directory shared on multiple servers. NFS/EFS, Gluster, ObjectiveFS... all these networked filesystems are not built for low-latency, multi-file access. If you're running a PHP or Ruby application with hundreds or thousands of small files that need to be read from disk (even if using opcache), you're going to have a very bad time. Same goes for using Git on EFS/NFS—almost always a bad idea.
Instead, use a tool like Ansible to deploy your code to a local filesystem on each server (hey, I wrote a book on that!); or build a 12-factor app and use disposable servers or containers to deploy your application code. Whatever the case, run code from a local, fast filesystem. Even a slow spinning-disk local filesystem will be a lot faster than a file system accessed over the network (see Latency Numbers Every Programmer Should Know).
Use NFS/EFS for storage of things like media assets, exported data files, and asynchronous logs that don't require extremely low-latency to work well. You don't ever want EFS to be in the critical path of your application's code.
Use multiple EFS volumes for latency-sensitive directories
If you do have to have a shared volume store latency-sensitive components of your application (e.g. lock files used by
flock), and there is other data (e.g. media files or logs) being read from and written to your EFS volume, consider adding a second EFS volume used only for the latency-sensitive operations. This still won't make things fly like using the local disk, but you'll have more consistent latency at least. (Note that I'm currently doing some testing in this area—I'll update this post if I find any other helpful improvements for this use case.)
Use the correct
AWS recommends the use of certain NFS mount options when setting up EFS mounts in Linux. Unless you have very specific needs, and have tested and thoroughly benchmarked any other options or changes to the recommended options, use AWS' recommendations.
They likely tweak their NFS backends and networks for the specific
wsize they specify.
Also, use NFS v4.1 if at all possible. It might be difficult to get an NFS 4.1 client installed on some older OSes, and in that case you can consider sticking with something older—but if not, use the latest and greatest; there are a lot of protocol improvements.
Careful with backups
EFS backups are one of the most annoying pain points of using EFS. For many AWS products, like Aurora, there is a dead-simple, easy-to-configure, and inexpensive snapshot process that allows easy backup and restore. With EFS... you're pretty much on your own.
And if you're like me, and you design a backup process that basically copies all X GB of files on EFS to a new server each backup—and you don't rate-limit the server's file copy—then you realize your backup just depleted your EFS burst credits, and now production is offline while EFS scrapes along at 0.5 MB/s ?.
I've used Gluster, NFS, EFS, and a few other shared filesystems for various projects. All have their tradeoffs, and all will, by the nature of being accessed over a network interface, be at least an order of magnitude slower than accessing files on a local (or in AWS, EBS) volume. The best thing to do when needing horizontal scalability is write your applications to not be dependent on low-ms-level file operation latency, and move things like lock mechanisms to a different layer, e.g. Redis or database.