How do you design and handle peak load on the Cloud ?

We see these questions time and time again – “How do I design for Peak load” and “How do I scale out on the cloud?”. First lets figure out how to give some definition for Peak load:

We will make a stab at defining peak load as: “A percentage of activity on a day/week/month/year that comes within a window of a few hours and is deemed as extreme and occurs because of either seasonality or because of unpredictable spikes.”

The Thomas Consulting Group have a good stab(ppt) at a forumla to try and predict and plan for Peak load. Their formula and example is shown below:

H = peak hits per second
h = # hits received over a one month period
a = % of activity that comes during peak time
t = peak time in hours
then
H = h * a / (days * t * minutes * seconds)
H = h * a / (108,000 * t)

Determine the peak Virtual Users: Peak hits/second + page view times

U = peak virtual users
H = peak hits per second
p = average number of hits / page
v = average time a user views a page

U = (H / p) * v

Example:

h = 150,000,000 hits per month
a = 10% of traffic occurs during peak time
t = peak time is 2 hours
p = a page consists of 6 hits
v = the average view time is 30 seconds

H = (h X a) / (108,000 * t)
H = (150,000,000 * .1) / (108,000 X 2)
H = 48

U = (H / p) * v
U = (48 / 6) * 30
U = 8 * 30
U = 240

Desired Metric – 48 Hits / Sec or 240 Virtual Users

In the example Thomas Consulting present above  Peak load is 15,000 hits in two hours whereas the  normal average of hits for two hours is 411 [(((h*12)/365)/24)*2]. This is over a 70% increase and a huge difference, and this example is not even extreme. Online web consumer companies can do 70% of their yearly business in December alone.

Depending on the what else occurs during the transactionality of the hits, then this could be difference between having 1 EC2 instance and having 10, or a cost difference between $6912 to $82,944 over the course of a year (based on a large Amazon EC2 instance).  And of course building for what you think is peak can still lead to problems. A famous quote by Scott Gulbransen from Intuit is:

“Every year, we take the busiest minute of the busiest hour of the busiest day and build capacity on that, We built our systems to (handle that load) and we went above and beyond that.” Despite this the systems still could not handle the load.

What we really want to be able to do is to have our site build for our average load, excluding peak, and have scale on demand built into the Architecture. As EC2 is the most mature cloud platform we will look at tools that can achieve this on EC2:

GigaSpaces XAP: From version 6.6 of the GigaSpaces XAP Platform Cloud tooling is built in. GigaSpaces is a next generation virtualised middleware platform that hosts logic, data, and messaging in-memory, and has less moving parts so that scaling out can be achieved linearly, unlike traditional middlware platforms. GigaSpaces us underpinned by a service grid which enables application level Service Level Agreement’s to be set and which are monitored and acted on in real-time. This means if load is increased then GigaSpaces can scale threads or the number of virtualised middlware instances to ensure that the SLA is met, which in our example would be the ability to act process the number of requests. GigaSpaces also partner with RightScale. GigaSpaces lets you try their Cloud offering for free before following the traditional utility compute pricing model.

Scalr:Scalr is a series of  Amazon Machine Images (AMI), for basic website needs i.e. an app server, a load balancer, and a database server. The AMIs are pre-built with a management suite that monitors the load and operating status of the various servers on the cloud. Scalr purports to increase / decrease capacity as demand fluctuates, as well as detecting and rebuilding improperly functioning instances. Scalr has open source and commercial versions and is a relatively new infrastructure service / application. We liked the the  ‘Synchronize to All’ features of Scalr.  This auto-bundles an AMI and then re-deploys it on a new instance. It does this without interrupting the core running of your site. This saves time going through the EC2 image/AMI creation process. To find out more about Scalr you should check out the Scalr Google Groups forum.

RightScale: RightScale has an automated Cloud Management platform. RightScale services include auto-scaling of servers according to usage load, and pre-built installation templates for common software stacks. RightScale support Amazon EC2, Eucalyptus, FlexiScale, and GoGrid. They are quoted as saying that RackSpace support will happen also at some point.  RightScale has a great case study oveview on their blog about Animoto and also explains how they have launched, configured and managed over 200,oo0 instances to date. RightScale are VC backed and in December 2008 did a $13 million series B funding round. RightScale have free and commercial offerings.

FreedomOSS:  Freedom OSS has created custom templates, called jPaaS (JBoss Platform as a Service), for scaling resources such as JBoss Application Server, JBoss Messaging, JBoss Rules, jBPM, Hibernate and JBoss Seam. jPaaS monitors the instances for load and scales them as necessary. jPaaS takes care of updating the vhosts file and other relevant configuration files to ensure that all instances of Apache respond to this hostname. The newly deployed app that runs either on Tomcat or JBoss becomes part of the new app server image.

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3 thoughts on “How do you design and handle peak load on the Cloud ?

  1. Nice post – very informative and to the point, well done.

    I’ve posted a post covering that topic and how GigaSpaces handles it with reference to real example of web application that runs on EC2 and autoscale when the load increases.
    You can read the full details here

    BTW i’d love to have a chat with you if you have experience in this field.

    Nati S.
    http://www.gigaspaces.com/cloud

  2. Pingback: Supporting SLA’s on the Cloud | Cloudiquity

  3. Pingback: Liddle Thoughts » Blog Archive » The SLA Driven Cloud

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