What is Load Balancing in Cloud Computing?
A load balancer in cloud computing acts as a virtual traffic cop, sitting between client devices and backend servers. It evenly distributes incoming network traffic across multiple resources, preventing any single server from becoming overwhelmed, maximizing application availability, and minimizing downtime.
How cloud load balancing works:
- Request management: It receives incoming client queries and determines which server is best equipped to handle them.
- Health checks: It continuously tests the availability of backend instances. If a server goes offline, it automatically reroutes traffic to healthy instances.
- Horizontal scaling: When integrated with cloud auto-scaling, it seamlessly routes traffic to newly spun-up virtual machines or containers.
Major cloud load balancer types:
- Application load balancers (ALB): Operates at Layer 7. Inspects the content of the request (e.g., HTTP headers, paths) to intelligently route traffic.
- Network load balancers (NLB): Operates at Layer 4. Highly performant for routing transport-level traffic based purely on IP data and TCP/UDP ports.
- Gateway load balancers (GLB): Used to deploy, scale, and manage virtual networking appliances like firewalls and intrusion detection systems.
- Global load balancing: Distributes traffic across multiple geographic regions or data centers to improve availability, disaster recovery, and user performance.
- Internal load balancing: Routes traffic between private resources within a cloud network or VPC without exposing services to the public internet.
- External/public load balancing: Distributes internet-facing traffic to public applications and services while providing a secure entry point for users.
In this article:
Load balancing provides advantages for cloud-based applications and services. By distributing traffic across multiple resources, it improves performance, reliability, and scalability while reducing the risk of service disruptions:
- Improved application performance: Distributes requests across multiple servers, preventing individual resources from becoming overloaded and reducing response times.
- High availability: Routes traffic away from failed or unhealthy servers to available resources.
- Better scalability: Spreads traffic across additional servers as resources are added.
- Enhanced fault tolerance: Reduces reliance on a single server.
- Efficient resource utilization: Balances workloads across available infrastructure.
- Reduced downtime: Detects service interruptions and redirects traffic to healthy instances.
- Improved user experience: Maintains consistent performance during traffic spikes.
- Cost optimization: Scales resources based on demand.
1. Request Management
Cloud load balancers act as the entry point for incoming client requests, receiving connections before forwarding them to backend resources such as virtual machines or containers. They use algorithms such as round robin, least connections, or weighted distribution to determine which server handles each request. This approach helps prevent resource overload.
Request management also supports traffic handling such as SSL termination, content-based routing, and request prioritization. By offloading these tasks from backend servers, the load balancer reduces backend processing overhead and improves performance. This is important in cloud environments, where workloads can shift rapidly and require real-time adjustments.
2. Health Checks
Health checks enable load balancers to monitor backend resources. The load balancer sends test requests or pings to each server to verify health and responsiveness. If a server fails these checks, it is removed from the pool so requests are routed only to healthy resources.
Health checks help reduce downtime and service degradation by isolating problematic servers. Configurations can be customized based on application requirements, allowing organizations to define thresholds and recovery actions.
3. Horizontal Scaling
Horizontal scaling is the process of adding or removing backend resources, such as virtual machines or containers, in response to changing demand. Cloud load balancers integrate with auto scaling mechanisms and redistribute traffic as new instances are added or removed. This scaling helps maintain performance during peak usage without manual intervention.
By using horizontal scaling, organizations can avoid overprovisioning resources and adjust capacity based on actual demand. This elasticity is a core benefit of cloud computing and supports efficient resource usage.
Prakash Sinha
Prakash Sinha is a technology executive and evangelist for Radware and brings over 29 years of experience in strategy, product management, product marketing and engineering. Prakash has held leadership positions in architecture, engineering, and product management at leading technology companies such as Cisco, Informatica, and Tandem Computers. Prakash holds a Bachelor in Electrical Engineering from BIT, Mesra and an MBA from Haas School of Business at UC Berkeley.
Tips from the Expert:
In my experience, here are tips that can help you better design, operate, and secure cloud load balancing environments:
1. Separate health checks from user experience checks: A server can respond with HTTP 200 while critical functionality is broken. Create dedicated synthetic transactions that validate login flows, database connectivity, and API dependencies rather than relying solely on simple health endpoints.
2. Load balance based on server capacity, not server count: Many environments distribute traffic equally even when backend instances have different CPU, memory, or hardware profiles. Use weighted balancing to align traffic allocation with actual resource capacity.
3. Protect against load balancer amplification attacks: Attackers often exploit expensive backend operations through a legitimate load balancer. Rate-limit requests to resource-intensive endpoints such as search, report generation, authentication, and file processing rather than treating all traffic equally.
4. Monitor connection distribution, not just request distribution: Traffic may appear evenly balanced while long-lived connections accumulate on a subset of servers. Track active connections, connection duration, and backend resource consumption to identify hidden imbalances.
5. Design for load balancer failure scenarios: Many architectures assume the load balancer is always available. Implement redundant load balancers, DNS failover, and recovery procedures to avoid creating a new single point of failure.
Application Load Balancers
Application load balancers operate at the application layer, Layer 7 of the OSI model, and make routing decisions based on HTTP or HTTPS request content. They can direct traffic based on URL paths, HTTP headers, cookies, or application-specific data. This control supports complex web applications and microservices architectures. Application load balancers also support SSL termination, web application firewall integration, and real-time analytics. They are commonly used in cloud-native applications.
Network Load Balancers
Network load balancers function at the transport layer, Layer 4, routing traffic based on IP address and TCP/UDP port information. They handle large volumes of connections with low latency, making them suitable for high-performance or latency-sensitive applications such as gaming platforms or real-time communications. Network load balancers do not inspect request content and instead focus on connection management. They support horizontal scaling and can handle sudden traffic surges.
Gateway Load Balancers
Gateway load balancers integrate third-party network appliances such as firewalls, intrusion detection systems, or deep packet inspection tools. They operate at the network layer and route traffic to these appliances without major changes to the network topology. By centralizing deployment of security and monitoring tools, gateway load balancers help enforce consistent policies and scale network infrastructure. They are useful in hybrid or multi-cloud environments where traffic must pass through inspection points before reaching workloads.
Global Load Balancing
Global load balancing distributes traffic across multiple geographic locations or data centers, improving performance and availability for users worldwide. It uses DNS-based routing, anycast, or similar techniques to direct requests to the closest or best-performing region, reducing latency and limiting the impact of regional outages. This approach supports organizations with a global user base or data residency requirements. Distributing workloads across regions strengthens disaster recovery and business continuity.
Internal Load Balancing
Internal load balancing manages traffic between resources within a private cloud network or virtual private cloud (VPC). It is used for microservices, backend APIs, and internal applications that are not exposed to the public internet. Internal load balancers support secure and scalable communication between application components. Isolating internal traffic from external networks allows stricter security controls and reduces the attack surface. Internal load balancing supports multi-tier architectures, allowing backend services to scale independently.
External/Public Load Balancing
External or public load balancing routes client requests from the internet to publicly accessible cloud resources such as web servers or APIs. These load balancers provide a secure entry point and often support SSL/TLS termination, DDoS mitigation, and application firewall features. Public load balancers are used for high-traffic websites and SaaS platforms to maintain availability and performance under varying loads. They also support geo-routing, content-based routing, and real-time monitoring.
AWS Elastic Load Balancing
AWS Elastic Load Balancing (ELB) is Amazon's managed load balancing service. It supports Application Load Balancer (ALB), Network Load Balancer (NLB), and Gateway Load Balancer (GWLB). ELB distributes incoming application traffic across targets such as EC2 instances, containers, and IP addresses in one or more availability zones. This supports high availability and fault tolerance for applications running on AWS.
ELB integrates with AWS Auto Scaling, Amazon Route 53 for DNS-based global load balancing, and AWS Web Application Firewall (WAF). It supports advanced routing, SSL offloading, and real-time metrics through Amazon CloudWatch. Pricing follows a pay-as-you-go model and supports scaling for different deployment sizes.
Microsoft Azure Load Balancing
Microsoft Azure provides Azure Load Balancer at Layer 4, Azure Application Gateway at Layer 7, and Azure Traffic Manager for global DNS-based load balancing. Azure Load Balancer distributes inbound and outbound network traffic for internal and public applications and integrates with Azure Virtual Machine Scale Sets.
Azure Application Gateway supports SSL termination, cookie-based session affinity, and web application firewall features. Azure Traffic Manager directs users to the nearest or most available region. These services can be combined to support complex cloud architectures.
Google Cloud Load Balancing
Google Cloud Load Balancing is a distributed, software-defined service that supports HTTP(S), TCP/SSL, and UDP traffic. It offers global load balancing with a single anycast IP address. Google Cloud Load Balancer routes user requests to the closest healthy backend.
The platform integrates with Google Cloud Armor for security, supports auto scaling, and provides monitoring through Google Cloud's operations suite. It supports internal and external load balancing for use cases ranging from global web applications to internal microservices.
Misconfigured Health Checks
Health checks determine whether backend resources can receive traffic. If settings are too strict, healthy servers may be marked as unavailable and removed from the pool. If too lenient, failed or degraded servers may continue receiving requests.
How to address: Organizations should configure health check paths, thresholds, timeouts, and intervals based on application behavior. Regular testing and monitoring help ensure accurate service availability and reliable failover.
Session Persistence Issues
Some applications rely on session data stored on a specific server. When a load balancer distributes requests across multiple instances, users may be routed to different servers, causing session data to be unavailable.
How to address: To address this issue, organizations use session persistence methods such as sticky sessions or external session stores like databases and distributed caches.
Latency Across Regions
Global load balancing improves availability, but routing traffic across regions can increase latency. Network distance and routing paths may increase response times when traffic is directed to distant data centers.
How to address: Reducing latency involves deploying applications closer to users, using content delivery networks (CDNs), and applying routing policies based on performance metrics.
Uneven Traffic Distribution
Load balancers aim to distribute requests evenly, but imbalances can occur due to differences in server capacity, long-lived connections, or algorithm selection. Some resources may become overloaded while others remain underused.
How to address: Organizations can reduce uneven distribution by selecting appropriate load balancing methods, assigning server weights based on capacity, and monitoring backend utilization.
Here are some of the ways that organizations can improve their load balancing strategy in the cloud.
1. Choose the Right Load Balancer Type for the Workload
Different applications have different traffic management requirements. Application load balancers are suited for HTTP and HTTPS traffic that requires content-based routing, while network load balancers are better for high-throughput, low-latency TCP or UDP workloads. Organizations should evaluate protocol support, performance requirements, security needs, and architecture before choosing a load balancing solution.
Action items:
- Match Layer 7 load balancers to web applications that require content-based routing.
- Use Layer 4 load balancers for high-performance TCP/UDP workloads.
- Evaluate security, latency, and scalability requirements before deployment.
- Review application architecture regularly as workloads evolve.
2. Use Health Checks to Route Traffic Only to Healthy Resources
Health checks ensure that traffic is directed only to functioning resources. By monitoring backend instances, load balancers can detect failures and remove unhealthy servers until they recover. Health checks should validate critical application functions rather than only basic network connectivity. Reviewing configurations and thresholds helps reduce false positives and supports reliable failover.
Action items:
- Configure health checks to validate application functionality, not just server reachability.
- Define appropriate timeout, interval, and failure thresholds.
- Monitor health check failures and investigate recurring issues.
- Test failover behavior regularly to verify traffic rerouting.
3. Combine Load Balancing With Auto Scaling
Load balancing works with auto scaling. As traffic increases, auto scaling adds new instances and the load balancer distributes requests across them. When demand decreases, excess resources are removed. This combination allows applications to adjust to changing workloads and maintain performance while controlling infrastructure costs.
Action items:
- Integrate load balancers with cloud auto scaling services.
- Define scaling policies based on CPU, memory, or request volume.
- Test scaling events under realistic traffic conditions.
- Monitor resource utilization to optimize scaling thresholds.
4. Secure the Load Balancing Layer
Because load balancers serve as the entry point for application traffic, they should be protected with security controls such as SSL/TLS termination, web application firewalls, DDoS protection, access control policies, and network segmentation. Protecting the load balancing layer helps block malicious traffic from reaching backend systems and reduces the risk of service disruptions.
Action items:
- Enable SSL/TLS termination and use modern encryption standards.
- Deploy web application firewall (WAF) protections where appropriate.
- Restrict administrative access using least-privilege principles.
- Implement DDoS protection and network segmentation controls.
5. Monitor Performance, Traffic, and SLA Metrics Continuously
Continuous monitoring provides visibility into load balancing performance and helps identify issues early. Key metrics include request rates, response times, backend utilization, error rates, latency, and availability. Organizations should use monitoring and alerting tools to track service-level agreement (SLA) objectives and detect anomalies in real time. Analyzing traffic patterns and performance trends supports capacity planning and infrastructure management.
Action items:
- Track request volume, response times, latency, and error rates.
- Monitor backend resource utilization and availability.
- Configure alerts for SLA breaches and abnormal traffic patterns.
- Review performance trends regularly to support capacity planning.
Radware Alteon is a next-generation application delivery controller (ADC) and network load balancer built to distribute application traffic and guarantee application SLAs across data center, hybrid, and multi-cloud environments. Available as a physical or virtual appliance, Alteon deploys natively in public and private clouds, giving organizations consistent, Layer 7-aware load balancing wherever their applications run, without sacrificing performance, availability, or security.
Key capabilities of Radware Alteon:
- Advanced Layer 7 load balancing: Distributes traffic with full application-layer awareness, intelligent health checks, content and URL filtering, and content rewrites to keep backend resources balanced and responsive.
- Native cloud and hybrid deployment: Runs as Load Balancing as a Service (LBaaS) and supports public and private cloud platforms, including Azure with High Availability and OpenStack, so the same load balancing capabilities extend across on-premises and cloud workloads.
- Global server load balancing: Directs users to the best-performing or closest region to reduce latency, support disaster recovery, and maintain availability for a global user base.
- Application SLA assurance: As the only network load balancer that guarantees application SLA, Alteon allocates resources dynamically to maintain performance during traffic spikes and shifting demand.
- Integrated application security: Combines a Web Application Firewall, authentication gateway, single sign-on, network access control, and hardware-based SSL termination to protect cloud-facing applications at the point of delivery.
- Programmable traffic steering: Lets teams define user-programmable policies and traffic steering logic to route requests based on application-specific needs.
- Elastic capacity and automation: Reassigns capacity automatically as demand changes and offers self-service provisioning and flexible licensing to optimize cost in elastic cloud environments.
Learn more about how Radware Alteon delivers high-performance, secure load balancing for cloud and hybrid applications.