By Shibu Paul- Vice President– International Sales, Array Networks
High availability, performance, and scalability are perhaps the biggest concerns of today’s digital landscape. Load balancers can be considered intelligent gatekeepers who optimize service functionality. They offer a seamless experience to the clients. However, to get maximum ROI with the load balancers, we need to ensure that it is operating at peak performance levels, and for this purpose, load balancing metrics are your key to success.
Load balancing metrics are crucial in giving insight into the performance and health of your load balancers. They measure where there is a need for adjustments to ensure optimal service delivery. Let’s have a look at 11 very significant load balancing metrics, why they need to be measured, and how you can achieve maximum benefit for your business.
Why measuring load balancer performance is significant
Load balancers distribute incoming traffic evenly across a set of servers so that not just a single server is overwhelmed. It also plays an important role in protecting applications and customer data by identifying and mitigating cyber threats. Due to this critical role, it is required to monitor and optimise their performance.
Measuring the performance of load balancing enables you to:
⦁ Identify network or system problems: Quickly diagnose issues that could impact service delivery.
⦁ Enhance user experience: Ensure service is uninterrupted for your users
⦁ Prevent backend bottlenecks: Keep all processes running smoothly throughout your server infrastructure
⦁ Improve system health: Keep all components at their best and functioning
⦁ Improve efficiency and accuracy: Streamline operations for better performance.
Here are the 11 most important load-balancing metrics you need to track.
1. Active connections
Active connections are the number of active and connected clients to target servers. It indicates whether the load is well-distributed over your cluster of servers. Active connections help you know whether your load balancers are operating efficiently and whether your system can handle the surge during peak traffic.
2. Failed connection count
For inactive connections, the count of failed connections typically measures the number of tries on your server to deny an accepted connection. This can provide insight into overwhelmed servers, unhealthy load balancers, or unevenly distributed loads. Through analyzing reasons for failures, you can identify whether your applications are scaling adequately or whether anomalies need addressing.
3. Request count
The count of requests is the total number of requests coming to your load balancers over a given period. On a per-minute basis, tracking requests can help determine if the load balancers are efficient and if there is some specific issue with the routing or the network. This metric can also tell you usage patterns and whether your infrastructure will handle the demand properly.
4. Latency
Latency refers to the time taken before returning the request of connecting to the client. It’s a very fundamental measure because it affects the user directly relating to the experience of the system. More latent systems can cause a loss in business and even lead to irritation of customers due to delays and waiting around for responses. Latency monitoring per load balancer, over time, helps indicate areas that may need improvement and ensures optimisation is applied in ways to guarantee the response times are improved in a manner whereby your client’s resources are accessed with minimal delay.
5. Error rate
This error rate monitored gives insight into how the load balancers are performing. Error rate might be measured on a per-load basis or averaged over time, which indicates the requests made on the connection that were returned with errors. This high error rate can indicate an error of misconfiguration on the front end and communication misalignment between the load balancer and the server on the backend.
6. Healthy/unhealthy hosts
Knowing the number of healthy versus unhealthy hosts is important to maintain service availability. This metric helps you know how fit your servers are and perform maintenance in advance to prevent latency or even less severe downtime. It is also very important to the state of the hosts, as understanding this will help ensure a stable environment for client interactions.
7. Fault tolerance
Fault tolerance measures the degree to which one or more faulty servers can still allow the system to function. This is a metric that lets you know how successfully your load balancers distribute traffic behind backend servers, such that chances of service disruption due to hardware failure become as small as possible. That is, high fault tolerance means high resilience and robustness.
8. Throughput
Throughput refers to how many successful requests are executed per unit of time. If throughput is high, then the load balancer is well-operational, and hence, the overall infrastructure is at peak performance levels. Monitoring through the throughput will alert you to such bottlenecks; thus, whether your load balancers are performing well in controlling incoming traffic or not is shown through this measure.
9. Migration time
Migration time is the time it takes for a request to migrate from one machine to another. The time spent migrating should be reduced for an improvement in load balancer efficiency. This would help you to maintain a fast response time, and thus a better experience for the users, along with low migration times.
10. Reliability
Reliability is one of the other necessary performance characteristics of the load balancer. This means its uptime and overtime performances have to be consistent. It means accessing services without any kind of interruption, and this is very much required for the maintenance of customer trust and satisfaction.
11. Response time
Response time is the total time taken by algorithms to respond to a request. Waiting time, transmission time, and service time make up the total time taken, which is considered response time. Optimising performance means that there should be a minimum response time. Response time determines the speed at which users receive information and services.
Conclusion
These 11 load-balancing metrics are essential for maintaining traffic stability, proper server health, and excellent client service. They are crucial for performance assessment, the health status of the infrastructure, and overall efficiency, because a well-implemented measurement strategy is good to start early, so you witness problems as they come along, providing a seamless quality of service while maximising ROI for your business.
As in the age of digitisation, knowing and measuring the load balancing metrics is not only useful but also a necessity for success.
