When discussing metrics for traffic routing in the context of load balancing, several key metrics can be considered to ensure optimal performance, reliability, and efficiency. Here are some important metrics:
Latency:
Measures the time it takes for a request to travel from the client to the server and back. Lower latency indicates better performance. For example, Cloudflare provides latency metrics to identify regions with unhealthy or slow pools[3].
Throughput:
Refers to the amount of data transferred over a network in a given period. High throughput indicates efficient data transfer. Metrics like ProcessedBytes and ProcessedPackets are used to measure throughput in AWS Network Load Balancers[12].
Request Count:
The total number of requests handled by the load balancer. This helps in understanding the load and traffic patterns. AWS CloudWatch metrics like NewFlowCount and RequestCount are examples[12][14].
Error Rates:
The number of failed requests or errors encountered. This includes metrics like 4xx Client Error and 5xx Server Error response codes, which indicate client-side and server-side errors, respectively[8].
Health Status:
The number of healthy versus unhealthy targets. Metrics like HealthyHostCount help in monitoring the health of the instances behind the load balancer[12].
Connection Metrics:
Metrics such as TCP_Client_Reset_Count, TCP_ELB_Reset_Count, and TCP_Target_Reset_Count track the number of reset packets, which can indicate issues with connections[12].
Load Distribution:
Metrics that show how traffic is distributed across different instances or zones. For example, PeakPacketsPerSecond measures the highest average packet rate, which helps in understanding load distribution[12].
CPU and Memory Usage:
Monitoring the CPU and memory usage of load balancers to ensure they are no...
