Lightboard Lessons: What is DDoS?

Over the last quarter, there were approximately 500 DDoS attacks daily around the world with some lasting as long as 300 hours. In this Lightboard Lesson I light up some #basics about DoS and DDoS attacks.



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Related:

• DDoS attacks in Q2 2017
• DDoS attack - Distributed Denial of Service
• DDoS Attacks 101: Types, targets, and motivations

Lightboard Lessons: What are Bots?

In this Lightboard Lesson, I light up some #basics about internet bots and botnets. Humans account for less than 50% of internet traffic and the rest is spread between the good bots and bad ones.



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Related:

• The Facts about Botnets
• The state of botnets in late 2015 and early 2016
• What are bots?

Lightboard Lessons: What is HTTP?

In this Lightboard Lesson, I light up some #basics about HTTP. HTTP defines the structure of messages between web components such as browser or command line clients, servers like Apache or Nginx, and proxies like the BIG-IP.



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Related:

• What is HTTP?
• What is HTTP Part II - Underlying Protocols

Lightboard Lessons: What is BIG-IP APM?

In this Lightboard, I light up some lessons on BIG-IP Access Policy Manager. BIG-IP APM provides granular access controls to discreet applications and networks supporting 2FA and federated identity management. You can also check out Chase's written article What is BIG-IP APM?



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What is a Proxy?

The term ‘Proxy’ is a contraction that comes from the middle English word procuracy, a legal term meaning to act on behalf of another. You may have heard of a proxy vote. Where you submit your choice and someone else votes the ballot on your behalf.

In networking and web traffic, a proxy is a device or server that acts on behalf of other devices. It sits between two entities and performs a service. Proxies are hardware or software solutions that sit between the client and the server and does something to requests and sometimes responses.

The first kind of proxy we’ll discuss is a half proxy. With a Half-Proxy, a client will connect to the proxy and the proxy will establish the session with the servers. The proxy will then respond back to the client with the information. After that initial connection is set up, the rest of the traffic with go right through the proxy to the back-end resources. The proxy may do things like L4 port switching, routing or NAT’ing but at this point it is not doing anything intelligent other than passing traffic.

Basically, the half-proxy sets up a call and then the client and server does their thing. Half-proxies are also good for Direct Server Return (DSR). For protocols like streaming protocols, you’ll have the initial set up but instead of going through the proxy for the rest of the connections, the server will bypass the proxy and go straight to the client. This is so you don’t waste resources on the proxy for something that can be done directly server to client.

A Full Proxy on the other hand, handles all the traffic. A full proxy creates a client connection along with a separate server connection with a little gap in the middle. The client connects to the proxy on one end and the proxy establishes a separate, independent connection to the server. This is bi-directionally on both sides. There is never any blending of connections from the client side to the server side – the connections are independent. This is what we mean when we say BIG-IP is a full proxy architecture.

The full proxy intelligence is in that OSI Gap. With a half-proxy, it is mostly client side traffic on the way in during a request and then does what it needs…with a full proxy you can manipulate, inspect, drop, do what you need to the traffic on both sides and in both directions. Whether a request or response, you can manipulate traffic on the client side request, the server side request, the server side response or client side response. You get a lot more power with a full proxy than you would with a half proxy.

With BIG-IP (a full proxy) on the server side it can be used as a reverse proxy. When clients make a request from the internet, they terminate on the reverse proxy sitting in front of application servers. Reverse proxies are good for traditional load balancing, optimization, server side caching, and security functionality. If you know certain clients or IP spaces are acceptable, you can whitelist them. Same with known malicious sources or bad ranges/clients, you can blacklist them. You can do it at the IP layer (L4) or you can go up the stack to Layer 7 and control an http/s request. Or add a BIG-IP ASM policy on there. As it inspects the protocol traffic if it sees some anomaly that is not native to the application like a SQL injection, you can block it.

On the client side, BIG-IP can also be a forward proxy. In this case, the client connects to the BIG-IP on an outbound request and the proxy acts on behalf of the client to the outside world. This is perfect for things like client side caching (grabbing a video and storing locally), filtering (blocking certain time-wasting sites or malicious content) along with privacy (masking internal resources) along with security.

You can also have a services layer, like an ICAP server, where you can pass traffic to an inspection engine prior to hitting the internet. You can manipulate client side traffic out to the internet, server side in from the internet, handle locally on the platform or or pass off to a third party services entity. A full proxy is your friend in an application delivery environment.

If you'd like to learn more about Proxies, check out the resources below including the Lightboard Lesson: What is a Proxy?

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Related:

• Lightboard Lessons: What is a Proxy?
• Encrypted malware vs. F5's full proxy architecture
• The Concise Guide to Proxies
• The Full-Proxy Data Center Architecture
• Three things your proxy can't do unless it's a full-proxy
• Back to Basics: The Many Modes of Proxies

What is Virtual Desktop Infrastructure (VDI)

What is VDI?

Imagine not having to carry around a laptop or be sitting in a cubicle to access your work desktop applications. Virtual desktop infrastructure (VDI) is appealing to many different constituencies because it combines the benefits of anywhere access with desktop support improvements.

Employees typically use a wide range of mobile devices from laptops to tablets and from desktops to smartphones are being used. The diversity of these mobile devices and the sheer number of them in the workplace can overwhelm IT and strain your resources.

Desktop Virtualization centralizes sets of desktops, usually in a data center or cloud environment, and then provide access to your employees whether they are in the office, at home or mobile.  VDI deployments virtualize user desktops by delivering them to distinctive endpoint devices over the network from a central location. There are many reasons why organizations deploy VDI solutions – it’s easier for IT to manage, it can reduce capital expenditures, improve security and helps companies run a ‘greener’ business.

Since users’ primary work tools are now located in a data center rather than on their own local machines, VDI can strain network resources, and the user experience can be negatively affected. Desktop virtualization is a bit more complex than server virtualization since it requires more network infrastructure, servers, server administrators, authentication systems, and storage. VDI’s effect on the network is significant; it may necessitate infrastructure changes to accommodate the large volume of client information that will be traversing the network. When a user’s desktop moves from a physical machine under the desk to the data center, the user experience becomes paramount; a poor VDI deployment will result in IT being flooded with “My desktop is too slow” calls.

Why VDI?

Mobile devices and bring your own computing are popular drivers for VDI deployments.  It enables employees to work from anywhere and simplifies/unifies desktop management, especially updating operating systems and applications.  It can lower costs, provide flexible remote access; improve security and compliance along with potentially offering organizations disaster recovery options.  It also enables employee flexibility and reduced IT risk of employee owned devices. VDI allows employees work with a wide range of devices from laptops to tablets to smartphones.  Employees can sign on from wherever they are, whenever they like and with whichever device they choose.

Deploying virtual desktops can also increase IT efficiency and reduce IT workload since the desktops are centralized.  It also benefits IT with greater access and compliance control, while at the same time, allowing employees the freedom to use their mobile device of choice. IT departments can remove obsolete versions of application software or perhaps enhance the security policy. Either way, the employee always has the most up to date desktop image.

Things to Consider

Desktop virtualization is no longer about the desktop, it’s about allowing employees desktop access from wherever they are. So things like availability, access, security, DR, authentication, storage, network latency and SSO are all areas to keep in mind when deploying a VDI solution.

VDI Providers

Some VDI solutions include VMware View, Citrix XenDesktop, and Microsoft RDS.

Next Steps

If you'd like to learn more or dig deeper into VDI, here are some additional resources:

• VDI the F5 Way
• Lightboard Lessons: Secure & Optimize VDI
• Citrix VDI iApp template
• VMware Horizon View iApp
• Also, here are some other articles from the #Basics Series.

What is an Application Delivery Controller - Part II

Application Delivery Basics

One of the unfortunate effects of the continued evolution of the load balancer into today's application delivery controller (ADC) is that it is often too easy to forget the basic problem for which load balancers were originally created—producing highly available, scalable, and predictable application services. We get too lost in the realm of intelligent application routing, virtualized application services, and shared infrastructure deployments to remember that none of these things are possible without a firm basis in basic load balancing technology. So how important is load balancing, and how do its effects lead to streamlined application delivery?

Let’s examine the basic application delivery transaction. The ADC will typically sit in-line between the client and the hosts that provide the services the client wants to use. As with most things in application delivery, this is not a rule, but more of a best practice in a typical deployment. Let's also assume that the ADC is already configured with a virtual server that points to a cluster consisting of two service points. In this deployment scenario, it is common for the hosts to have a return route that points back to the load balancer so that return traffic will be processed through it on its way back to the client.

The basic application delivery transaction is as follows:

1. The client attempts to connect with the service on the ADC.
2. The ADC accepts the connection, and after deciding which host should receive the connection, changes the destination IP (and possibly port) to match the service of the selected host (note that the source IP of the client is not touched).
3. The host accepts the connection and responds back to the original source, the client, via its default route, the load balancer.
4. The ADC intercepts the return packet from the host and now changes the source IP (and possible port) to match the virtual server IP and port, and forwards the packet back to the client.
5. The client receives the return packet, believing that it came from the virtual server or host, and continues the process. 

Figure 1. A basic load balancing transaction.

This very simple example is relatively straightforward, but there are a couple of key elements to take note of. First, as far as the client knows, it sends packets to the virtual server and the virtual server responds—simple. Second, the NAT takes place. This is where the ADC replaces the destination IP sent by the client (of the virtual server) with the destination IP of the host to which it has chosen to load balance the request. Step three is the second half of this process (the part that makes the NAT "bi-directional"). The source IP of the return packet from the host will be the IP of the host; if this address were not changed and the packet was simply forwarded to the client, the client would be receiving a packet from someone it didn't request one from, and would simply drop it. Instead, the ADC, remembering the connection, rewrites the packet so that the source IP is that of the virtual server, thus solving this problem.

The Application Delivery Decision

So, how does the ADC decide which host to send the connection to? And what happens if the selected host isn't working?

Let's discuss the second question first. What happens if the selected host isn't working? The simple answer is that it doesn't respond to the client request and the connection attempt eventually times out and fails. This is obviously not a preferred circumstance, as it doesn't ensure high availability. That's why most ADC technology includes some level of health monitoring that determines whether a host is actually available before attempting to send connections to it.

There are multiple levels of health monitoring, each with increasing granularity and focus. A basic monitor would simply PING the host itself. If the host does not respond to PING, it is a good assumption that any services defined on the host are probably down and should be removed from the cluster of available services. Unfortunately, even if the host responds to PING, it doesn't necessarily mean the service itself is working. Therefore most devices can do "service PINGs" of some kind, ranging from simple TCP connections all the way to interacting with the application via a scripted or intelligent interaction. These higher-level health monitors not only provide greater confidence in the availability of the actual services (as opposed to the host), but they also allow the load balancer to differentiate between multiple services on a single host. The ADC understands that while one service might be unavailable, other services on the same host might be working just fine and should still be considered as valid destinations for user traffic.

This brings us back to the first question: How does the ADC decide which host to send a connection request to? Each virtual server has a specific dedicated cluster of services (listing the hosts that offer that service) which makes up the list of possibilities. Additionally, the health monitoring modifies that list to make a list of "currently available" hosts that provide the indicated service. It is this modified list from which the ADC chooses the host that will receive a new connection. Deciding the exact host depends on the ADC algorithm associated with that particular cluster. The most common is simple round-robin where the ADC simply goes down the list starting at the top and allocates each new connection to the next host; when it reaches the bottom of the list, it simply starts again at the top. While this is simple and very predictable, it assumes that all connections will have a similar load and duration on the back-end host, which is not always true. More advanced algorithms use things like current-connection counts, host utilization, and even real-world response times for existing traffic to the host in order to pick the most appropriate host from the available cluster services.

Sufficiently advanced application delivery systems will also be able to synthesize health monitoring information with load balancing algorithms to include an understanding of service dependency. This is the case when a single host has multiple services, all of which are necessary to complete the user's request. A common example would be in e-commerce situations where a single host will provide both standard HTTP services (port 80) as well as HTTPS (SSL/TLS at port 443) and any other potential service ports that need to be allowed. In many of these circumstances, you don't want a user going to a host that has one service operational, but not the other. In other words, if the HTTPS services should fail on a host, you also want that host's HTTP service to be taken out of the cluster list of available services. This functionality is increasingly important as HTTP-like services become more differentiated with this things like XML and scripting.

To Load Balance or Not to Load Balance?

Load balancing in regards to picking an available service when a client initiates a transaction request is only half of the solution. Once the connection is established, the ADC must keep track of whether the following traffic from that user should be load balanced. There are generally two specific issues with handling follow-on traffic once it has been load balanced: connection maintenance and persistence.

Connection maintenance

If the user is trying to utilize a long-lived TCP connection (telnet, FTP, and more) that doesn't immediately close, the ADC must ensure that multiple data packets carried across that connection do not get load balanced to other available service hosts. This is connection maintenance and requires two key capabilities: 1) the ability to keep track of open connections and the host service they belong to; and 2) the ability to continue to monitor that connection so the connection table can be updated when the connection closes. This is rather standard fare for most ADCs.

Persistence

Increasingly more common, however, is when the client uses multiple short-lived TCP connections (for example, HTTP) to accomplish a single task. In some cases, like standard web browsing, it doesn't matter and each new request can go to any of the back-end service hosts; however, there are many more instances (XML, JavaScript, e-commerce "shopping cart," HTTPS, and so on) where it is extremely important that multiple connections from the same user go to the same back-end service host and not be load balanced. This concept is called persistence, or server affinity. There are multiple ways to address this depending on the protocol and the desired results. For example, in modern HTTP transactions, the server can specify a "keep-alive" connection, which turns those multiple short-lived connections into a single long-lived connection that can be handled just like the other long-lived connections. However, this provides little relief. Even worse, as the use of web and mobile services increases, keeping all of these connections open longer than necessary would strain the resources of the entire system. In these cases, most ADCs provide other mechanisms for creating artificial server affinity.

One of the most basic forms of persistence is source-address affinity. Source address affinity persistence directs session requests to the same server based solely on the source IP address of a packet. This involves simply recording the source IP address of incoming requests and the service host they were load balanced to, and making all future transaction go to the same host. This is also an easy way to deal with application dependency as it can be applied across all virtual servers and all services. In practice however, the wide-spread use of proxy servers on the Internet and internally in enterprise networks renders this form of persistence almost useless; in theory it works, but proxy-servers inherently hide many users behind a single IP address resulting in none of those users being load balanced after the first user's request—essentially nullifying the ADC capability. Today, the intelligence of ADCs allows organizations to actually open up the data packets and create persistence tables for virtually anything within it. This enables them to use much more unique and identifiable information, such as user name, to maintain persistence. However, organizations one must take care to ensure that this identifiable client information will be present in every request made, as any packets without it will not be persisted and will be load balanced again, most likely breaking the application.

Final Thoughts

It is important to understand that basic load balancing technology, while still in use, is now only considered a feature of Application Delivery Controllers. ADCs evolved from the first load balancers through the service virtualization process and today with software only virtual editions. They can not only improve availability, but also affect the security and performance of the application services being requested.

Today, most organizations realize that simply being able to reach an application doesn't make it usable; and unusable applications mean wasted time and money for the enterprise deploying them. ADCs enable organizations to consolidate network-based services like SSL/TLS offload, caching, compression, rate-shaping, intrusion detection, application firewalls, and even remote access into a single strategic point that can be shared and reused across all application services and all hosts to create a virtualized Application Delivery Network. Basic load balancing is the foundation without which none of the enhanced functionality of today's ADCs would be possible.

And if you missed What is an ADC Part 1, you can find it here.

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Next Steps

Now that you’ve gotten this far, would you like to dig deeper or learn more about how application delivery works? Cool, then check out these resources:

• Go Beyond POLB (Plain Old Load Balancing)
• The Cloud-Ready ADC
• BIG-IP Virtual Edition Products, The Virtual ADCs Your Application Delivery Network Has Been Missing
• Cloud Balancing: The Evolution of Global Server Load Balancing

What is an Application Delivery Controller - Part 1

A Little History

Application Delivery got its start in the form of network-based load balancing hardware. It is the essential foundation on which Application Delivery Controllers (ADCs) operate. The second iteration of purpose-built load balancing (following application-based proprietary systems) materialized in the form of network-based appliances. These are the true founding fathers of today's ADCs. Because these devices were application-neutral and resided outside of the application servers themselves, they could load balance using straightforward network techniques. In essence, these devices would present a "virtual server" address to the outside world, and when users attempted to connect, they would forward the connection to the most appropriate real server doing bi-directional network address translation (NAT).

Figure 1: Network-based load balancing appliances.

With the advent of virtualization and cloud computing, the third iteration of ADCs arrived as software delivered virtual editions intended to run on hypervisors. Virtual editions of application delivery services have the same breadth of features as those that run on purpose-built hardware and remove much of the complexity from moving application services between virtual, cloud, and hybrid environments. They allow organizations to quickly and easily spin-up application services in private or public cloud environments.

Basic Application Delivery Terminology

It would certainly help if everyone used the same lexicon; unfortunately, every vendor of load balancing devices (and, in turn, ADCs) seems to use different terminology. With a little explanation, however, the confusion surrounding this issue can easily be alleviated.

Node, Host, Member, and Server

Most ADCs have the concept of a node, host, member, or server; some have all four, but they mean different things. There are two basic concepts that they all try to express. One concept—usually called a node or server—is the idea of the physical or virtual server itself that will receive traffic from the ADC. This is synonymous with the IP address of the physical server and, in the absence of a ADC, would be the IP address that the server name (for example, www.example.com) would resolve to. We will refer to this concept as the host.

The second concept is a member (sometimes, unfortunately, also called a node by some manufacturers). A member is usually a little more defined than a server/node in that it includes the TCP port of the actual application that will be receiving traffic. For instance, a server named www.example.com may resolve to an address of 172.16.1.10, which represents the server/node, and may have an application (a web server) running on TCP port 80, making the member address 172.16.1.10:80. Simply put, the member includes the definition of the application port as well as the IP address of the physical server.  We will refer to this as the service.

Why all the complication? Because the distinction between a physical server and the application services running on it allows the ADC to individually interact with the applications rather than the underlying hardware or hypervisor. A host (172.16.1.10) may have more than one service available (HTTP, FTP, DNS, and so on). By defining each application uniquely (172.16.1.10:80, 172.16.1.10:21, and 172.16.1.10:53), the ADC can apply unique load balancing and health monitoring based on the services instead of the host. However, there are still times when being able to interact with the host (like low-level health monitoring or when taking a server offline for maintenance) is extremely convenient.

Most load balancing-based technology uses some concept to represent the host, or physical server, and another to represent the services available on it— in this case, simply host and services.

Pool, Cluster, and Farm

Load balancing allows organizations to distribute inbound application traffic across multiple back-end destinations, including cloud deployments. It is therefore a necessity to have the concept of a collection of back-end destinations. Clusters, as we will refer to them (also known as pools or farms) are collections of similar services available on any number of hosts. For instance, all services that offer the company web page would be collected into a cluster called "company web page" and all services that offer e-commerce services would be collected into a cluster called "e-commerce."
The key element here is that all systems have a collective object that refers to "all similar services" and makes it easier to work with them as a single unit. This collective object—a cluster—is almost always made up of services, not hosts.

Virtual Server

Although not always the case, today the term virtual server means a server hosting virtual machines. It is important to note that like the definition of services, virtual server usually includes the application port was well as the IP address. The term "virtual service" would be more in keeping with the IP:Port convention; but because most vendors, ADC and Cloud alike use virtual server, this article uses virtual server as well.

Putting It All Together

Putting all of these concepts together makes up the basic steps in load balancing. The ADC presents virtual servers to the outside world. Each virtual server points to a cluster of services that reside on one or more physical hosts.

Figure 2: Application Delivery comprises four basic concepts—virtual servers, clusters, services, and hosts.

While the diagram above may not be representative of a real-world deployment, it does provide the elemental structure for continuing a discussion about application delivery basics.

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Next Steps

Check out Part II coming January 26!

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What is Load Balancing?

The entire intent of load balancing is to create a system that virtualizes the "service" from the physical servers that actually run that service. A more basic definition is to balance the load across a bunch of physical servers and make those servers look like one great big server to the outside world. There are many reasons to do this, but the primary drivers can be summarized as "scalability," "high availability," and "predictability."

Scalability is the capability of dynamically, or easily, adapting to increased load without impacting existing performance. Service virtualization presented an interesting opportunity for scalability; if the service, or the point of user contact, was separated from the actual servers, scaling of the application would simply mean adding more servers or cloud resources which would not be visible to the end user.

High Availability (HA) is the capability of a site to remain available and accessible even during the failure of one or more systems. Service virtualization also presented an opportunity for HA; if the point of user contact was separated from the actual servers, the failure of an individual server would not render the entire application unavailable. Predictability is a little less clear as it represents pieces of HA as well as some lessons learned along the way. However, predictability can best be described as the capability of having confidence and control in how the services are being delivered and when they are being delivered in regards to availability, performance, and so on.

A Little Background

Back in the early days of the commercial Internet, many would-be dot-com millionaires discovered a serious problem in their plans. Mainframes didn't have web server software (not until the AS/400e, anyway) and even if they did, they couldn't afford them on their start-up budgets. What they could afford was standard, off-the-shelf server hardware from one of the ubiquitous PC manufacturers. The problem for most of them? There was no way that a single PC-based server was ever going to handle the amount of traffic their idea would generate and if it went down, they were offline and out of business. Fortunately, some of those folks actually had plans to make their millions by solving that particular problem; thus was born the load balancing market.

In the Beginning, There Was DNS

Before there were any commercially available, purpose-built load balancing devices, there were many attempts to utilize existing technology to achieve the goals of scalability and HA. The most prevalent, and still used, technology was DNS round-robin. Domain name system (DNS) is the service that translates human-readable names (www.example.com) into machine recognized IP addresses. DNS also provided a way in which each request for name resolution could be answered with multiple IP addresses in different order.

Figure 1: Basic DNS response for redundancy

The first time a user requested resolution for www.example.com, the DNS server would hand back multiple addresses (one for each server that hosted the application) in order, say 1, 2, and 3. The next time, the DNS server would give back the same addresses, but this time as 2, 3, and 1. This solution was simple and provided the basic characteristics of what customer were looking for by distributing users sequentially across multiple physical machines using the name as the virtualization point.

From a scalability standpoint, this solution worked remarkable well; probably the reason why derivatives of this method are still in use today particularly in regards to global load balancing or the distribution of load to different service points around the world. As the service needed to grow, all the business owner needed to do was add a new server, include its IP address in the DNS records, and voila, increased capacity. One note, however, is that DNS responses do have a maximum length that is typically allowed, so there is a potential to outgrow or scale beyond this solution.

This solution did little to improve HA. First off, DNS has no capability of knowing if the servers listed are actually working or not, so if a server became unavailable and a user tried to access it before the DNS administrators knew of the failure and removed it from the DNS list, they might get an IP address for a server that didn't work. 

Proprietary Load Balancing in Software

One of the first purpose-built solutions to the load balancing problem was the development of load balancing capabilities built directly into the application software or the operating system (OS) of the application server. While there were as many different implementations as there were companies who developed them, most of the solutions revolved around basic network trickery. For example, one such solution had all of the servers in a cluster listen to a "cluster IP" in addition to their own physical IP address.

Figure 2: Proprietary cluster IP load balancing

When the user attempted to connect to the service, they connected to the cluster IP instead of to the physical IP of the server. Whichever server in the cluster responded to the connection request first would redirect them to a physical IP address (either their own or another system in the cluster) and the service session would start. One of the key benefits of this solution is that the application developers could use a variety of information to determine which physical IP address the client should connect to. For instance, they could have each server in the cluster maintain a count of how many sessions each clustered member was already servicing and have any new requests directed to the least utilized server.

Initially, the scalability of this solution was readily apparent. All you had to do was build a new server, add it to the cluster, and you grew the capacity of your application. Over time, however, the scalability of application-based load balancing came into question. Because the clustered members needed to stay in constant contact with each other concerning who the next connection should go to, the network traffic between the clustered members increased exponentially with each new server added to the cluster. The scalability was great as long as you didn't need to exceed a small number of servers.

HA was dramatically increased with these solutions. However, since each iteration of intelligence-enabling HA characteristics had a corresponding server and network utilization impact, this also limited scalability. The other negative HA impact was in the realm of reliability. 

Network-Based Load balancing Hardware

The second iteration of purpose-built load balancing came about as network-based appliances. These are the true founding fathers of today's Application Delivery Controllers. Because these boxes were application-neutral and resided outside of the application servers themselves, they could achieve their load balancing using much more straight-forward network techniques. In essence, these devices would present a virtual server address to the outside world and when users attempted to connect, it would forward the connection on the most appropriate real server doing bi-directional network address translation (NAT).

Figure 3: Load balancing with network-based hardware

The load balancer could control exactly which server received which connection and employed "health monitors" of increasing complexity to ensure that the application server (a real, physical server) was responding as needed; if not, it would automatically stop sending traffic to that server until it produced the desired response (indicating that the server was functioning properly). Although the health monitors were rarely as comprehensive as the ones built by the application developers themselves, the network-based hardware approach could provide at least basic load balancing services to nearly every application in a uniform, consistent manner—finally creating a truly virtualized service entry point unique to the application servers serving it.

Scalability with this solution was only limited by the throughput of the load balancing equipment and the networks attached to it. It was not uncommon for organization replacing software-based load balancing with a hardware-based solution to see a dramatic drop in the utilization of their servers. HA was also dramatically reinforced with a hardware-based solution. Predictability was a core component added by the network-based load balancing hardware since it was much easier to predict where a new connection would be directed and much easier to manipulate. 

The advent of the network-based load balancer ushered in a whole new era in the architecture of applications. HA discussions that once revolved around "uptime" quickly became arguments about the meaning of "available" (if a user has to wait 30 seconds for a response, is it available? What about one minute?). 

This is the basis from which Application Delivery Controllers (ADCs) originated.

The ADC

Simply put, ADCs are what all good load balancers grew up to be. While most ADC conversations rarely mention load balancing, without the capabilities of the network-based hardware load balancer, they would be unable to affect application delivery at all. Today, we talk about security, availability, and performance, but the underlying load balancing technology is critical to the execution of all.

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Next Steps

Ready to plunge into the next level of Load Balancing? Take a peek at these resources:

• Go Beyond POLB (Plain Old Load Balancing)
• The Cloud-Ready ADC
• BIG-IP Virtual Edition Products, The Virtual ADCs Your Application Delivery Network Has Been Missing
• Cloud Balancing: The Evolution of Global Server Load Balancing