The “Elastic” in “Elastic Load Balancing”: ELB Elasticity and How to Test it

how to load balance iis

by Shlomo Swidler on July 12, 2009

Update March 2012:  Amazon published their own official guide to ELB’s architecture and building and testing applications that use it. The official material is very consistent with the presentation offered here, more than two and a half years prior.

Elastic Load Balancing is a long-anticipated AWS feature that aims to ease the deployment of highly-scalable web applications. Let’s take a look at how it achieves elasticity, based on experience and based on the information available in the AWS forums (mainly this thread ). The goal is to understand how to design and test ELB deployments properly.

ELB: Two Levels of Elasticity

ELB is a distributed system. An ELB virtual appliance does not have a single public IP address. Instead, when you create an ELB appliance, you are given a DNS name such as Amazon encourages you to set up a DNS CNAME entry pointing (say) to the ELB-supplied DNS name.

Why does Amazon use a DNS name? Why not provide an IP address? Why encourage using a CNAME? Why can’t we use an Elastic IP for an ELB? In order to understand these issues, let’s take a look at what happens when clients interact with the ELB.

Here is the step-by-step flow of what happens when a client requests a URL served by your application:

  1. The client looks in DNS for the resolution of your web server’s name, Because you have set up your DNS to have a CNAME alias pointing to the ELB name DNS responds with the name .
  2. The client looks in DNS for the resolution of the name This DNS entry is controlled by Amazon since it is under the domain. Amazon’s DNS server returns an IP address, say .
  3. The client opens a connection with the machine at the provided IP address The machine at this address is really an ELB virtual appliance.
  4. The ELB virtual appliance at address passes through the communications from the client to one of the EC2 instances in the load balancing pool. At this point the client is communicating with one of your EC2 application instances.

As you can see, there are two levels of elasticity in the above protocol. The first scalable point is in Step 2, when Amazon’s DNS resolves the ELB name to an actual IP address. In this step, Amazon can vary the actual IP addresses served to clients in order to distribute traffic among multiple ELB machines. The second point of scalability is in Step 4, where the ELB machine actually passes the client communications through to one of the EC2 instances in the ELB pool. By varying the size of this pool you can control the scalability of the application.

Both levels of scalability, Step 2 and Step 4, are necessary in order to load-balance very high traffic loads. The Step 4 scalability allows your application to exceed the maximum connections per second capacity of a single EC2 instance: connections are distributed among a pool of application instances, each instance handling only some of the connections. Step 2 scalability allows the application to exceed the maximum inbound network traffic capacity of a single network connection: an ELB machine’s network connection can only handle a certain rate of inbound network traffic. Step 2 allows the network traffic from all clients to be distributed among a pool of ELB machines, each appliance handling only some fraction of the network traffic.

If you only had Step 4 scalability (which is what you have if you run your own software load balancer on an EC2 instance) then the maximum capacity of your application is still limited by the inbound network traffic capacity of the front-end load balancer: no matter how many back-end application serving instances you add to the pool, the front-end load balancer will still present a network bottleneck. This bottleneck is eliminated by the addition of Step 2: the ability to use more than one load balancer’s inbound network connection.

[By the way, Step 2 can be replicated to a limited degree by using Round-Robin DNS to serve a pool of IP addresses, each of which is a load balancer. With such a setup you could have multiple load-balanced clusters of EC2 instances, each cluster sitting behind its own software load balancer on an EC2 instance. But Round Robin DNS has its own limitations (such as the inability to take into account the load on each load-balanced unit, and the difficulty of dynamically adjusting the pool of IP addresses to distribute), from which ELB does not suffer.]

Behind the scenes of Step 2, Amazon maps an ELB DNS name to a pool of IP addresses. Initially, this pool is small (see below for more details on the size of the ELB IP address pool). As the traffic to the application and to the ELB IP addresses in the pool increases, Amazon adds more IP addresses to the pool. Remember, these are IP addresses of ELB machines, not your application instances. This is why Amazon wants you to use a CNAME alias for the front-end of the ELB appliance: Amazon can vary the ELB IP address served in response to the DNS lookup of the ELB DNS name.

It is technically possible to implement an equivalent Step 2 scalabililty feature without relying on DNS CNAMEs to provide “delayed binding” to an ELB IP address. However, doing so requires implementing many features that DNS already provides, such as cached lookups and backup lookup servers. I expect that Amazon will implement something along these lines when it removes the limitation that ELBs must use CNAMEs – to allow, for example, an Elastic IP to be associated with an ELB. Now that would be cool.

How ELB Distributes Traffic

As explained above, ELB uses two pools: the pool of IP addresses of ELB virtual appliances (to which the ELB DNS name resolves), and the pool of your application instances (to which the ELBs pass through the client connection).

How is traffic distributed among these pools?

ELB IP Address Distribution

The pool of ELB IP addresses initially contains one IP address. More precisely, this pool initially consists of one ELB machine per availability zone that your ELB is configured to serve. This can be inferred from this page  in the ELB documentation, which states that “Incoming traffic is load balanced equally across all Availability Zones enabled for your load balancer”. I posit that this behavior is implemented by having each ELB machine serve the EC2 instances within a single availability zone. Then, multiple availability zones are supported by the ELB having in its pool at least one ELB machine per enabled availability zone. Update April 2010: An availability zone that has no healthy instances will not receive any traffic. Previously, the traffic would be evenly divided across all enables availability zones regardless of instance health, possibly resulting in 404 errors. Recent upgrades to ELB no longer exhibit this weakness.

Back to the scalability of the ELB machine pool. According to AWS folks in the forums. this pool is grown in response to increased traffic reaching the ELB IP addresses already in the pool. No precise numbers are provided, but a stream of gradually-increasing traffic over the course of a few hours should cause ELB to grow the pool of IP addresses behind the ELB DNS name. ELB grows the pool proactively in order to stay ahead of increasing traffic loads.

How does ELB decide which IP address to serve to a given client? ELB varies the chosen address “from time to time”. No more specifics are given. However, see below for more information on making sure you are actually using the full pool of available ELB IP addresses when you test ELB.

Back-End Instance Connection Distribution

Each ELB machine can pass through client connections to any of the EC2 instances in the ELB pool within a single availability zone. According to user reports in other forum posts, clients from a single IP address will tend to be connected to the same back-end instance.  According to AWS ELB does round-robin among the least-busy back-end instances, keeping track of approximately how many connections (or requests) are active at each instance but without monitoring CPU or anything else on the instances. It is likely that earlier versions of ELB exhibited some stickiness, but today the only way to ensure stickiness is to use the Sticky Sessions feature.

How much variety is necessary in order to cause the connections to be fairly distributed among your back-end instances? AWS says that “a dozen clients per configured availability zone should more than do the trick”. Additionally, in order for the full range of ELB machine IP addresses to be utilized, “make sure each [client] refreshes their DNS resolution results every few minutes.”

How to Test ELB

Let’s synthesize all the above into guidelines for testing ELB:

  1. Test clients should use the ELB DNS name, ideally via a CNAME alias in your domain. Make sure to perform a DNS lookup for the ELB DNS name every few minutes. If you are using Sun’s Java VM you will need to change the system property to be different than the default value of -1, which causes DNS lookups to be cached until the JVM exits. 120 (seconds) is a good value for this property for ELB test clients. If you’re using IE 7 clients, which cache DNS lookups for 30 minutes by default, see the Microsoft-provided workaround to set that cache timeout to a much lower value.
Update 14 August 2008. If your test clients cache DNS lookups (or use a DNS provider that does this) beyond the defined TTL, traffic may be misdirected during ramp-up or ramp-down. See my article for a detailed explanation.
  • One test client equals one public IP address. ELB machines seem to route all traffic from a single IP address to the same back-end instance, so if you run more than one test client process behind a single public IP address, ELB regards these as a single client.
  • Use 12 test clients for every availability zone you have enabled on the ELB. These test clients do not need to be in different availability zones – they do not even need to be in EC2 (although it is quite attractive to use EC2 instances for test clients). If you have configured your ELB to balance among two availability zones then you should use 24 test clients.
  • Each test client should gradually ramp up its load over the course of a few hours. Each client can begin at (for example) one connection per second, and increase its rate of connections-per-second every X minutes until the load reaches your desired target after a few hours.
  • The mix of requests and connections that each test client performs should represent a real-world traffic profile for your application. Paul@AWS recommends the following:

    In general, I’d suggest that you collect historical data or estimate a traffic profile and how it progresses over a typical (or perhaps extreme, but still real-world) day for your scenario. Then, add enough headroom to the numbers to make you feel comfortable and confident that, if ELB can handle the test gracefully, it can handle your actual workload.

    The elements of your traffic profile that you may want to consider in your test strategy may include, for example:

    • connections / second
    • concurrent connections
    • requests / second
    • concurrent requests
    • mix of request sizes
    • mix of response sizes
  • Use the above guidelines as a starting point to setting up a testing environment that exercises you application behind an ELB. This testing environment should validate that the ELB, and your application instances, can handle the desired load.

    A thorough understanding of how ELB works can go a long way to helping you make the best use of ELB in your architecture and toward properly testing your ELB deployment. I hope this article helps you design and test your ELB deployments.


    Category: Forex

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