Load Balancing in Cloud Computing Definition
Load balancing in cloud computing distributes traffic and workloads to ensure that no single server or machine is under-loaded, overloaded, or idle. Load balancing optimizes various constrained parameters such as execution time, response time, and system stability to improve overall cloud performance. Load balancing architecture in cloud computing consists of a load balancer that sits between servers and client devices to manage traffic.
Load balancing in cloud computing distributes traffic, workloads and computing resources evenly throughout a cloud environment to deliver greater efficiency and reliability for cloud applications. Cloud load balancing enables enterprises to manage client requests and host resource distribution among multiple computers, application servers, or computer networks.
The overall goal of load balancing in cloud computing is to minimize response time for application users and maximize organizational resources.
Load Balancing in Cloud Computing FAQs
What is Load Balancing in Cloud Computing?
In a public cloud computing environment, a load balancer distributes application and network traffic efficiently and methodically across various servers. This prevents excessive traffic and requests from collecting in one place and enhances application responsiveness by spreading the workload categorically between existing servers.
Load balancers sit between backend servers and client devices, receive server requests, and distribute them to available, capable servers. Cloud load balancing is the process of distributing traffic such as UDP, TCP/SSL, HTTP(s), HTTPS/2 with gRPC, and QUIC to multiple backends to increase security, avoid congestion, and reduce costs and latency.
Load Balancing Techniques in Cloud Computing
Load balancing in cloud computing distributes traffic among cloud servers and manages massive workloads to prevent any one server from becoming overwhelmed. This reduces downtime and latency and enhances performance.
Advanced load balancing in cloud computing distributes traffic across many servers to reduce latency and improve server availability and reliability. Successful cloud load balancing implementations prevent server failure and optimize performance using several different load balancing techniques. For example, a load balancer may evaluate geographical distance or server load before redirecting traffic in the event of failover.
Load balancers may be hardware-based devices on the network or solely software-defined processes. Hardware load balancers are often prohibited from running in vendor-managed cloud environments and are generally inefficient at managing cloud traffic anyway. Software-based load balancers are more suitable for cloud infrastructures and applications and can run in any location and environment.
DNS load balancing in cloud computing is a software-defined approach that distributes client requests to a domain within the Domain Name System (DNS) across various servers. The DNS system sends a different version of the list of IP addresses each time it responds to a new client request to ensure that DNS requests are evenly distributed among servers. DNS load balancing automatically removes non-responsive servers and allows for automatic failover or backup.
Load balancing in cloud computing works a lot like a police officer directing traffic to avoid congestion. Yes, the officer probably has basic, static techniques such as counting out how many cars can get through or how many seconds of traffic can get by at once, but they also have dynamic techniques at their disposal, and can adjust their pace based on the ebb and flow of traffic conditions. Load balancing in cloud computing works in a similar way to prevent the loss of revenue and poor user experience caused by overwhelmed applications and servers.
How to Implement Load Balancing in Cloud Computing
There are various different types of load balancing algorithms in cloud computing, some more popular than others. They differ in how they determine which servers should receive client requests and how they manage and distribute network load. The eight most common load balancing algorithms in cloud computing are:
Round Robin
The Round Robin algorithm for load balancing in cloud computing forwards incoming requests to each server in a simple, repeating cycle. Standard round robin algorithms are among the most common static load balancing algorithms in cloud computing. This is among the most basic techniques to implement but as it assumes equal capacity on the part of all servers, it may not be the most efficient. Two variations of this method adjust for this issue: weighted round robin and dynamic round robin.
IP Hash
This straightforward load balancing method distributes requests based on IP address. This load balancing technique uses an algorithm that allocates client requests to servers based on unique hash keys it generates. The hash keys are an encrypted version of the destination and source and IP address.
Least Connections
One of the more common dynamic load balancing algorithms in cloud computing, the Least Connections method is ideal for scenarios when there are periods of heavy traffic. Least connections diverts traffic to the server with the fewest active connections to evenly distribute traffic among all available servers.
Least Response Time
This is a similar dynamic technique to least connections, but the least response time technique directs traffic to a server based on two conditions: lowest average response time and fewest number of active connections.
Least Bandwidth
Another type of dynamic load balancing in cloud computing, the least bandwidth method sends client requests to the server consuming the least bandwidth during the most recent interval.
Layer 4 Load Balancers
L4 load balancers route traffic packets based on the IP addresses of their destination and source and the UDP or TCP ports they use. As part of a process called Network Address Translation (NAT), L4 load balancers map the IP address to the right servers rather than inspecting actual packet contents.
Layer 7 Load Balancers
Functioning on the application layer of the OSI model, L7 load balancers inspect SSL session IDs, HTTP headers, and other data to determine how to route requests to servers. L7 load balancers are both more efficient and more computationally intensive than L4 load balancers, because they demand additional context to route requests to servers.
Global Server Load Balancing
Global Server Load Balancing (GSLB) extends L4 and L7 load balancer capabilities across data centers to more efficiently distribute massive amounts of traffic without hurting performance. GSLB is particularly helpful for managing geographically distributed application requests.
What is a Load Balancer as a Service in Cloud Computing?
Many cloud providers offer load balancing-as-a-service (LBaaS) to customers who use these services on an as-needed basis in place of on-premises, dedicated traffic routing appliances which demand in-house configuration and maintenance. Among the more popular types of load balancing in cloud computing, LBaaS operates much like traditional load balancing to balance workloads.
However, LBaaS balances workloads across servers in a cloud environment and manages itself as a subscription or on-demand service there, rather than distributing traffic across a cluster of servers in-house in a single data center. Single cloud vendors generate and manage some LBaaS environments, while others distribute traffic between multiple cloud providers, multi-cloud balancers, and hybrid cloud load balancers.
Benefits of LBaaS include:
Scalability: Easily and rapidly scale load balancing services to accommodate traffic spikes without manually configuring additional physical infrastructure.
Availability: Connect to the geographically closest server to minimize latency and guarantee high availability even when a server is down.
Reduced costs: LBaaS is typically less expensive in terms of money, time, effort, and internal resources for both initial investment and maintenance compared to hardware-based appliances.
Advantages of Load Balancing in Cloud Computing
Why use a load balancer in cloud computing? Load balancers are critical to high-performing cloud computing environments. Some of the benefits of load balancing in cloud computing environments, and the importance of load balancing in cloud computing are outlined below.
Simpler Automation
Load balancing in cloud computing enables organizations to use predictive analytic tools to identify traffic bottlenecks far in advance and gain actionable insights into applications in near real-time, influencing business decisions. This is all critical to the automation process.
Seamless Management of Traffic Spikes
Load balancing in cloud computing manages multiple server requests for optimal, high-performing capacity so that IT professionals don’t need to step in to counteract surges in traffic. This smooth and even distribution enables optimum results in minimal response time, even as needs change significantly.
In this way, load balancing helps organizations capitalize on sudden increasing demands and avoid being overwhelmed by spikes in network traffic. The ability to balance loads and scale server capacity can help retain customers and avoid churn.
Emergency and Disaster Recovery
Cloud-based service providers such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform can pinpoint unavailable servers and redirect traffic across geographical regions during times of emergencies or natural disasters like tsunamis, earthquakes, tornadoes, and floods.
They can also often ascertain in advance which servers are more likely to become overburdened based on which load balancing algorithms cloud load balancers in a network support. This kind of “planning” allows some cloud load balancers to redirect server traffic more rapidly to healthier nodes that are better equipped to manage requests, reducing the odds of data loss and services becoming unavailable.
High Performing Applications
Cloud-based load balancing enables the scaling up of services and ensures that efficiency and high performance accompany increased traffic.
Flexibility
The ability to temporarily route traffic to alternative servers allows flexibility for developers who need to perform software updates and patches, maintain faulty servers, and test in a production environment.
Cost-Effective
Load balancing in cloud computing is efficient and delivers better cloud service performance and reliability at a significantly lower cost of ownership. Cloud load balancers are accessible to startups, small businesses, and medium-sized enterprises because they run on the cloud or can be paid for as a service.
DDoS Attack Mitigation
Load balancers inherently defend against distributed denial of service (DDoS) attacks by distributing traffic across multiple servers, rerouting traffic away from a single overloaded server during a DDoS attack, and reducing the attack surface. Load balancing in cloud computing makes the network resilient against such attacks by eliminating single points of failure.
Disadvantages of Load Balancing in Cloud Computing
Load balancing is basically a requirement in the cloud environment, yet there are a few challenges of load balancing in cloud computing.
Although scalability is among the most appealing advantages of both cloud computing and load balancing, scalability is also among the most prominent weaknesses of load balancing. Scalability is hampered for most load balancers by a limited number of nodes for distributing processes. Other challenges include energy consumption, performance monitoring, QoS management, resource scheduling, and service availability in the cloud.
Does Avi Offer Load Balancing Tools in Cloud Computing?
Yes. Avi Vantage delivers multi-cloud application services including a Software Load Balancer, Elastic Service Mesh, and Intelligent Web Application Firewall (iWAF). The Avi Vantage Platform ensures an application experience that is scalable, fast, and secure.
Avi Vantage is 100% software-defined, and unlike legacy load balancers, it delivers:
- Multi-cloud – Central orchestration and management offer a consistent experience across on-premises and cloud environments
- Automation – 100% RESTful APIs enable self-service provisioning and integration into the CI/CD pipeline for application delivery
- Intelligence – Automation is intelligent, autoscaling is seamless, and decision making is easy thanks to built-in analytics that drive actionable insights
Learn about Avi Vantage and load balancing solutions in cloud computing here.