How do hardware load balancers work

In this, all the request related to a session is sent to the same server to maintain the session state and syncronization. This approach is used when we have session aware write operations in sync with client and the server so that it avoids any inconsistency. Now, load balancing softwares can have the smart implementation of the combination of the above three basic scheduling algorithm.

Such implementations are Weighted round robin scheduling and Weighted least connection scheduling. Many hybrid scheduling algorithm for load balancing has evolved using some variations or combinations of the above algorithms. Load balancing hardwares are often referred as specialized routers or switches which are deployed in between the servers and the client.

It can also be a dedicated system in between the the client and the server to balance the load. Layer 4 load balancers are mostly the network address translators NATs which shares load to the different servers getting translated to by these loadbalancer.

These routers hide multiple servers behind them and translate every response data packets coming from the server to be coming from same ipaddress. Similarly, when there is a request they reverse translate the request using the mapping table and distributes it among the multiple servers. This approach creates a load balancing effect whenever there is a dns lookup.

The diagram below depicts the highlevel overview of Layer 4 and Layer 7 load balancer working and techniques on OSI layer. Fig: Load Balancer — Layer 4 and Layer 7. Direct routing: This is a yet another configuration of hardware load balancing where the routers are aware of the server mac addresses and server may be ARP Address resolution Protocol disabled.

In direct routing, it is direct in the sense that all the income traffic is routed by the load balancer however all the outgoing traffic direct reaches the client which makes it super fast load balancing configuration. Tunnel or a IP tunneling often looks like Direct routing where response is directly sent to client however the traffic between the router and the server can be routed.

In this, client sends the request to the virtual IP of load balancer which further encapsulates the IP packets, keeps a hast table and distributes it to the different servers as per the configured load balancing technique. When the server is getting back the response, it decapsulates it and send back to the client directly according to the hash table which it has stored. This record is eventually removed from hash table when the connection is closed or there is a timeout.

This type of load balancers makes the decision according to the actual content of the message URLs, cookies, scripts since HTTP exists on the layer7. Hardware appliances often run proprietary software optimized to run on custom processors.

As traffic increases, the vendor simply adds more load balancing appliances to handle the volume. Software defined load balancers usually run on less-expensive, standard Intel x86 hardware. Installing the software in cloud environments like AWS EC2 eliminates the need for a physical appliance.

DNS load balancing is a software-defined approach to load balancing where client requests to a domain within the Domain Name System DNS are distributed across different server machines.

The DNS system sends a different version of the list of IP addresses each time it responds to a new client request using the round-robin method, therefore distributing the DNS requests evenly to different servers to handle the overall load. This in turn provides DNS load balancing failover protection through automatic removal of non-responsive servers.

DNS load balancing differs from hardware load balancing in a few instances, although both can be a very effective solution for distributing traffic.

One main advantage of DNS level load balancing is the scalability and price. A DNS load balancer distributes traffic to several different IP addresses, whereas the hardware solution uses a single IP address and splits traffic leading to it on multiple servers.

As for pricing, hardware load balancers require a large upfront cost whereas DNS load balancers can be scaled as needed.

A per-app approach to load balancing equips an application with a dedicated set of application services to scale, accelerate, and secure the application. Per app load balancing provides a high degree of application isolation, avoids over-provisioning of load balancers, and eliminates the constraints of supporting numerous applications on one load balancer. Load balancing automation tools deploy, configure, and scale load balancers as needed to maintain performance and availability of applications, eliminating the need to code custom scripts per-app or per-environment.

Per application load balancing offers a cost-efficient, elastic scale based on learned traffic thresholds and is particularly beneficial for applications that have matured beyond the limitations of a traditional, hardware load balancer.

Weighted load balancing is the process of permitting users to set a respective weight for each origin server in a pool. Depending on their respective weights and the load balancing weight priority, traffic will be rebalanced to the remaining accessible origins. An underestimated aspect to weighted load balancing are the nodes.

Nodes that restart begin again with an empty cache, and while the cache is repopulating it makes the node slower, which results in slowing down the entire collection. This is where heat weighted load balancing comes into focus by aiming to have low latency.

The heat of each node is a factor in enhancing the node selection in the coordinator, so as a node is being rebooted, latency remains at a low level. Round robin load balancing has client requests allocated throughout a group of servers that are readily available, then is followed by all requests redirected to each server in turn. In contrast to the weighted load balancing algorithm, the weighted round robin load balancing algorithm is used to schedule data flows and processes in networks.

This process becomes cyclical when the algorithm commands the load balancer to return to the beginning of the list and repeat its procedure again. Reliable and efficient, weighted round robin load balancing is a simple method and the most commonly used load balancing algorithm. Periodically, load balancers will perform a series of health checks to make sure registered instances are being monitored.

Regardless of the instances being in a healthy or unhealthy state, all registered instances will receive load balancer health checks.

An instance health status shows as such:. The load balancer will only send requests to healthy instances, so it will not send requests to an instance with an unhealthy status. Once the instance has returned to a healthy state, the load balancer will continue to route requests to that instance. A stateful load balancer is able to keep track of all current sessions using a session table.

Before picking the right server to handle a request, it is able to look at a number of things using a distributed load balancing algorithm, such as the load of the different servers. Once a session is initiated and the load distribution algorithms have chosen its destination server, it sends all the upcoming packets to the server until the session comes to a close.

Contrary to the process of stateful load balancing, stateless load balancing is a much simpler process. The most common method of a stateless load balancer is by making a hash of the IP address of the client down to a small number. The number is used for the balancer to decide which server to take the request. It also has the ability to pick a server entirely by random, or even go round-robin.

The hashing algorithm is the most basic form of stateless load balancing. Since one client can create a log of requests that will be sent to one server, hashing on source IP will generally not provide a good distribution.

However, a combination of IP and port can create a hash value as a client creates individual requests using a different source pot.

An application load balancer is one of the features of elastic load balancing and allows simpler configuration for developers to route incoming end-user traffic to applications based in the public cloud. As a result, it enhances user experiences, improves application responsiveness and availability, and provides protection from distributed denial-of-service DDoS attacks.

A load balancing router, also known as a failover router, is designed to optimally route internet traffic across two or more broadband connections. Broadband users that are simultaneously accessing internet applications or files will be more likely to have a better experience. Cross data center load balancing, also known as global server load balancing GSLB , distributes traffic across global data centers typically located in different regions.

The cost of purchasing and maintaining requisite hardware for GSLB is considerable— at least one appliance has to be located in each of your data centers, with another central box to manage load distribution between them.

To minimize costs, the central appliance can be replaced by a DNS-based solution. Lastly, scalability becomes an even bigger problem in GSLB appliances and DNS cross data center configurations, due to an increase in possible bottlenecks. Contrast these issues with cloud-based solutions. Cloud GSLB scales on demand, possibly saving your organization tens of thousands dollars in setup and maintenance costs.

The latter also extends to failover and disaster recovery scenarios, in which responsive rerouting is even more crucial and can make a difference between instant recovery and prolonged downtime. Register Now. CAPEX costs for hardware load balancer are considerably higher than for cloud-based alternatives. A single appliance is typically more expensive than a subscription to a cloud service. However, maintenance dramatically increases when multiple data centers and hardware devices are involved.

Among other matters, this opens the door to integration issues, while also hindering your ability to effectively control and monitor load distribution.

Contrast that with cloud-based services, which offer centralized traffic flow control and are often provided as managed services. They require little maintenance, even when used for cross data center load management. Both solution types support basic and advanced algorithms used to manage load distribution.

These typically include:. Network layer load distribution is available on both HLDs and cloud load balancers. A basic inspection of incoming traffic routes it to the correct server. This allows for basic and semi-advanced distribution methods, such as round-robin and least connections.

Hardware load balancers may also contain built-in virtualization, consolidating many instances in the same device. Since they use specialized processors to run the software, they offer fast throughput, while the need for physical access to network or application servers increases the security.

On the downside, hardware load balancers can be costly as it requires purchase of physical machines and paid consultants to configure, program and maintain the hardware. Software-based load balancers on the other hand can deliver the same benefits as hardware load balancers while replacing the expensive hardware. They can run on any standard device and thereby save space and hardware costs. Software load balancers offer more flexibility to adjust for changing requirements and can help you scale capacity by adding more software instances.

They can also easily be used for load balancing on the cloud in a managed, off-site solution or in a hybrid model with in-house hosting as well. DNS load balancing is a software-defined approach to load balancing. Every time the DNS system responds to a new client request, it sends a different version of the list of IP addresses.

This ensures that the DNS requests are distributed evenly to different servers to handle the overall load. With non-responsive servers being automatically removed, DNS load balancing allows for automatic failover or backup to a working server.

There are several methods or techniques that load balancers use to manage and distribute network load. They differ in the algorithms they use to determine which application server should receive each client request. The five most common load balancing methods are:. In this method, an incoming request is forwarded to each server on a cyclical basis.

When it reaches the last server, the cycle is repeated beginning with the first one. It is one of the simplest methods to implement but may not be the most efficient, as it assumes that all servers are of similar capacity. There are two other variants of this method — weighted round robin and dynamic round robin — that can adjust for this assumption.

It uses an algorithm to generate a unique hash key, or an encrypted version of the source and destination IP address. In the Least Connections method, traffic is diverted to the server that has the least amount of active connections. Ideal for scenarios when there are periods of heavy traffic, this method helps distribute the traffic evenly among all available servers.

In the least response time method, traffic is directed to the server that satisfies two conditions — it should have the fewest amount of active connections and lowest average response time. In this method, the load balancer looks at the bandwidth consumption of servers in Mbps for the last fourteen seconds. The one that consumes the least bandwidth is chosen to send client requests to.

At the end of the day, load balancing is about helping businesses effectively manage network traffic and application load in order to give end users a reliable, consistent experience.

In doing this, load balancers provide the following benefits. Load balancing helps businesses stay on top of traffic fluctuations or spikes and increase or decrease servers to meet the changing needs. This helps businesses capitalize on sudden increases in customer demands to increase revenue.