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Posts Tagged ‘cloud computing’

On Why Auto-Scaling in the Cloud Rocks

December 9, 2008 70 comments
SkyNet Lives - EC2 at SmugMug

In high school, I had a great programmable calculator. I’d program it to solve complicated math and science problems “automatically” for me. Most of my teachers got upset if they found out, but I’ll always remember one especially enlightened teacher who didn’t. He said something to the effect of “Hey, if you managed to write software to solve the equation, you must thoroughly understand the problem. Way to go!”.

George Reese wrote up a blog post over at O’Reilly the other day called On Why I Don’t Like Auto-Scaling in the Cloud. His main argument seems to be that auto-scaling is bad and reflects poor capacity planning. In the comments, he specifically calls SmugMug out, saying we’re “using auto-scaling as a crutch for poor or non-existent capacity planning”.

George is like one of those math teachers who doesn’t “get it”. I was tempted not to write this post because he gets it so wrong, I’d hate to spread that meme. SkyNet auto-scales well. No humans at SmugMug are monitoring it and it just hums along, doing its job. Why is it so efficient? Because I understand the equation. I know what metrics drive our capacity planning and I programmed SkyNet to take these into account. It checks an awful lot of data points every minute or so – this isn’t simply “oh, we have idle CPU, let’s kill some instances.” (I would argue that, depending on the application, simple auto-scaling based on CPU usage or similar data point can be very effective, too, though).

SkyNet has been in production for over a year with only two incidents of note and SmugMug has more than doubled in size and capacity during that time without adding any new operations people. How on earth is this a bad thing?

I'm *not* speaking at Cloud Computing Expo 2008

November 17, 2008 11 comments

Just a quick update, I was invited to speak at Sys-Con’s Cloud Computing Expo 2008 West (how’s that for a mouthful?) and accepted, planning on talking about SkyNet, S3, and our future use of cloud computing. Alas, my Inbox is so crazy, I failed to see the handful of emails the conference sent me asking me to sign a contract of some type. So I missed the deadline and they canceled my spot. (BTW, I can’t recall a conference ever asking me to sign something to speak, but this one does and I was full of FAIL.) 😦

So, I’m sorry, despite being listed on the program, I’m *not* speaking there this week. It was my bad – I just missed the emails (as I miss so many emails these days). But still, a phone call from them wouldn’t have hurt, would it?

Who knows if I’ll be on their invitation list next year, but the conference will be great anyway, so have a great time without me!

Huge EC2 release: Load Balancing & Auto-Scaling!

October 27, 2008 7 comments
June 5th, 2008 near Maryville, Missouri

June 5th, 2008 near Maryville, Missouri by Shane Kirk

In case you didn’t see it, Amazon had a huge EC2 announcement the other day that included:

  • EC2 is now out of beta.
  • EC2 has a SLA!
  • Windows is now availabled on EC2
  • SQL Server is now available on EC2

But the really cool bits, if you ask me, are the announcements about the next wave of related services:

  • Monitoring
  • Load Balancing
  • Auto-Scaling
  • A web-based management console

As frequent readers of my blog and/or conference talks will know, this means one of the last important building blocks to creating fully cloud-hosted applications *at scale* is nearly ready for primetime.

For those keeping score at home, my personal checklist shows that the only thing now missing is a truly scalable, truly bottomless database-like data store. Neither Elastic Block Storage (EBS) nor SimpleDB really solve the entire scope of the problem, though they’re great building blocks that do solve big pieces (or everything, at smaller scale). I’m positive that someone (Amazon or other) will solve this problem and I can start moving more stuff “to the Cloud”.

I can’t wait.

Live-tweeting Cloud keynote at PDC 2008

October 27, 2008 1 comment
UFO OR CLOUD?

UFO OR CLOUD? by Shane Kirk

Microsoft is announcing some exciting Cloud Computing stuff today at their Professional Developers Conference (PDC). Assuming it’s the same stuff (and more?) I’ve been briefed on over the last year, it’s pretty exciting stuff.

I’ll be live-tweeting the best bits over on my Twitter account. If this stuff is interesting to you, come check it out.

SkyNet Lives! (aka EC2 @ SmugMug)

June 3, 2008 53 comments
SkyNet Lives - EC2 at SmugMug

Everyone knows that SmugMug is a heavy user of S3, storing well over half a petabyte of data (non-replicated) there. What you may not know is that EC2 provides a core part of our infrastructure, too. Thanks to Amazon, the software and hardware that processes all of your high-resolution photos and high-definition video is totally scalable without any human intervention. And when I say scalable, I mean both up and down, just the way it should be. Here’s our approach in a nutshell:

OVERVIEW

The architecture basically consists of three software components: the rendering workers, the batch queuing piece, and the controller. The rendering workers live on EC2, and both the queuing piece and the controller live at SmugMug. We don’t use SQS for our queuing mechanism for a few reasons:

  • We’d already built a queuing mechanism years ago, and it hasn’t (yet?) hit any performance or reliability bottlenecks.
  • SQS’s pricing used to be outta whack for what we needed. They’ve since dramatically lowered the pricing and it’s now much more in line with what we’d expect – but by then, we were done.
  • The controller consumes historical data to make smart decisions, and our existing queuing system was slightly easier to generate the historical data from.

RENDER WORKERS

Our render workers are totally “dumb”. They’re literally bare-bones CentOS 5 AMIs (you can build your own, or use RightScale’s, or whatever you’d like) with a single extra script on them which is executed from /etc/rc.d/rc.local. What does that script do? It fetches intelligence. 🙂

When that script executes, it sends an authenticated request to get a software bundle, extracts the bundle, and starts the software inside. That’s it. Further, the software inside the bundle is self-aware and self-updating, too, automatically fetching updated software, terminating older versions, and relaunching itself. This makes it super-simple to push out new SmugMug software releases – no bundling up new AMIs and testing them or anything else that’s messy. Simply update the software bundle on our servers and all of the render workers automatically get the new release within seconds.

Of course, worker instances might have different roles or be assigned to work with different SmugMug clusters (test vs production, for example), so we have to be able to give it instructions at launch. We do this through the “user-data” launch parameter you can specify for EC2 instances – they give the software all the details needed to choose a role, get software, and launch it. Reading the user-data couldn’t be easier. If you haven’t done it before, just fetch http://169.254.169.254/latest/user-data from your running instance and parse it.

Once they’re up and running, they simply ping the queue service with a “Hi, I’m looking for work. Do you have any?” request, and the queue service either supplies them with work or gives them some other directive (shutdown, software update, take a short nap, etc). Once a job is done (or generated an error), the worker stores the work result on S3 and notifies the queue service that the job is done and asks for more work. Simple.

QUEUE SERVICE

This is your basic queuing service, probably very similar to any other queueing service you’ve seen before. Ours supports job types (new upload, rotate, watermark, etc) and priorities (Pros go to the head of the line, etc) as well as other details. Upon completion, it also logs historical data such as time to completion. It also supports time-based re-queueing in the event of a worker outage, miscommunication, error, or whatever. I haven’t taken a really hard look at SQS in quite some time, but I can’t imagine it would be very difficult to implement on SQS for those of you starting fresh.

CONTROLLER (aka SkyNet)

For me, this was the fun part. Initially we called it RubberBand, but we had an ususual partial outage one day which caused it to go berzerk and launch ~250 XL instances (~2000 normal EC2 instances) in a single call. Clearly, it had gained sentience and was trying to take over the world, so we renamed it SkyNet. (We’ve since corrected the problem, and given SkyNet more reasonable thresholds and limits. And yes, I caught it within the hour.).

SkyNet is completely autonomous – it operates with with zero human interaction, either watching or providing interactive guidance. No-one at SmugMug even pays attention to it anymore (and we haven’t for many months) since it operates so efficiently. (Yes, I realize that means it’s probably well on its way to world domination. Sorry in advance to everyone killed in the forthcoming man-machine war.)

Roughly once per minute, SkyNet makes an EC2 decision: launch instance(s), terminate instance(s), or sleep. It has a lot of inputs – it checks anywhere from 30-50 pieces of data to make an informed decision. One of the reasons for that is we have a variety of different jobs coming in, some of which (uploads) are semi-predictable. We know that lots of uploads come in every Sunday evening, for example, so we can begin our prediction model there. Other jobs, though, such as watermarking an entire gallery of 10,000 photos with a single click, aren’t predictable in a useful way, and we can only respond once the load hits the queue.

A few of the data points SkyNet looks at are:

  • How many jobs are pending?
  • What’s the priority of the jobs?
  • What type of jobs are they?
  • How complex are the pending jobs? (ex: HD video vs 1Mpix photo)
  • How time-sensitive are the pending jobs? (ex: Uploads vs rotations)
  • Current load of the EC2 cluster
  • Current # of jobs per sample processed
  • Average time per job per sample
  • Historical load and job performance
  • How close any instances are to the end of their 1-hour cost window
  • Recent SkyNet actions (start/terminate/etc)

.. and the list goes on.

Our goal is to keep enough slack around to handle surges of unpredictable batch operations, but not enough so it drains our bank account. We’ve settled on an average of roughly 25% of excess compute capacity available when averaged over a full 24 hour period and SkyNet keeps us remarkably close to that number. We always err on the side of more excess (so we get faster processing times) rather than less when we have to make a decision. It’s great to save a few bucks here and there that we can plow back into better customer service or a new feature – but not if photo uploads aren’t processing, consistently, within 5-30 seconds of upload.

SkyNet Lives - EC2 at SmugMug

Our workers like lots of threads, so SkyNet does its best to launch c1.xlarge instances (Amazon calls these “High-CPU Instances“), but is smart enough to request equivalent other instance sizes (2 x Large, 8 x Small, etc) in the event it can’t allocate as many c1.xlarge instances as it would like. Our application doesn’t care how big/small the instances are, just that we get lots of CPU cores in aggregate. (We were in the Beta for the High-CPU feature, so we’ve been using it for months).

One interesting thing we had to take into account when writing SkyNet was the EC2 startup lag. Don’t get me wrong – I think EC2 starts up reasonably fast (~5 mins max, usually less), but when SkyNet is making a decision every minute, that means you could launch too many instances if you don’t take recent actions into account to cover startup lag (and, conversely, you need to start instances a little earlier than you might actually need them otherwise you get behind).

THE MONEY

SmugMug is a profitable business, and we like to keep it that way. The secrets to efficiently using EC2, at least in our use case, are as follows:

  • Take advantage of the free S3 transfers. This is a biggy. Our workers get and put almost all of their bytes to/from S3.
  • Make sure you have scaling down working as well as scaling up. At 3am on an average Wednesday morning, we have very few instances running.
  • Use the new High-CPU Instances. Twice the CPU resources for the same $$ if you don’t need RAM.
  • Amazon kindly gives you 30 days to monetize your AWS expenses. Use those 30 days wisely – generate revenues. 🙂

WHY NO WEB SERVERS?

I get asked this question a lot, and it really comes down to two issues, one major and one minor:

  • No complete DB solution. SimpleDB is interesting, and the new EC2 Persistent Storage is too, but neither provides a complete solution for us. EC2 storage isn’t performant enough without some serious, painful partitioning to a finer grain than we do now – which comes with its own set of challenges, and SimpleDB both isn’t performant enough and doesn’t address all of our use cases. Since latency to our DBs matters a great deal to our web servers, this is a deal-killer – I can’t have EC2 web servers talking to DBs in my datacenters. (There are a few corner cases we’re exploring where we probably can, but they’re the exception – not the rule).
  • No load balancing API. They’ve got an IP address solution in the form of Elastic IPs, which is awesome and major step forward, but they don’t have a simple Load Balancer API that I can throw my web boxes behind. Yes, I realize I can manually do it using EC2 instances, but that’s more fragile and difficult (and has unknown scaling properties at our scale). If the DB issue were solved, I’d probably dig into this and figure out how to do it ourselves – but since it’s not, I can keep asking for this in the meantime.

Let me be very clear here: I really don’t want to operate datacenters anymore despite the fact that we’re pretty good at it. It’s a necessary evil because we’re an Internet company, but our mission is to be the best photo sharing site. We’d rather spend our time giving our customers great service and writing great software rather than managing physical hardware. I’d rather have my awesome Ops team interacting with software remotely for 100% of their duties (and mostly just watching software like SkyNet do its thing). We’ll get there – I’m confident of that – we’re just not there yet.

Until then, we’ll remain a hybrid approach.

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