Yes, it can be done and it has been done.
BTW, we are thinking about devoting the next best practice webinar to Network Capacity Management. Stay tuned.
Nice the Network Capacity webinar
We would also be very interested in a Network webinar
late is better than ever, sorry for the delay
Yes, Load Balancer are quite interesting and their analysis can show good use of correlation of parameters.
According to my personal experience, the following metrics are useful
- CPU Utilization: complex forwarding and balancing rules stress the CPU of these dedicated devices
- Number of connections: this metric defines the actual throughput and can be used for discussions with Application Developers
- Input or Output Bandwidth usage: as the number of connections, we can estimate the maximum bandwidth of information a device can manage. This number changes according to different types of worload
While each packet or request or connection can be different, using the published 'maximum number of connections' or 'maximum bitrate' of a device can be misleading.
The actual maximum sustainable rate of connections or bitrate can vary and the following technique helps understanding values under the current workload.
The following analysis shows that CPU behaves like the workload, memory is flat: so we'll focus on CPU.
One possible correlation is with the output bitrate
Or another type of correlation is with number of connections, for example one load balancer in the application was changed and it's CPU utilization dropped significantly:
But what about the actual workload?
The extrapolation model allowed to estimate that
- old capacity = 10k conn/s
- new capacity > 30k conn/s
As usual, depending on the type of worload your bottleneck may shift.
In any case, given the extremely high physical interface bandwidth of modern devices and ever increasing complexity of balancing/forwarding rules, one could expect the CPU to still be the limiting factor.