If you land into this Part 8 directly, I’d recommend that you at least review from Part 5 first. If you want to review from the conceptual stage, then go to Part 1. This is a series of blog post on Capacity Management in SDDC.
Tier 2 and 3 (lowest)
To recap, you need to create line charts showing the following:
- The maximum CPU contention and average CPU contention for all VMs in the cluster
- The Maximum RAM contention and average RAM contention for all VMs
- Total number of VM left in the cluster.
- Maximum storage latency and average storage latency for all VMs
- Disk capacity left in the datastore cluster.
The screenshot below shows the super metric formula to get the Maximum CPU Contention of all the VMs in the cluster. To create the Average CPU Contention super metric, you just need to replace the string Max with Avg in the formula.
The screenshot below shows the super metric formula to get the Maximum Memory Contention of all the VMs in the cluster. To create the Average RAM Contention super metric, you just need to replace the string Max with Avg in the formula.
Copy-paste each of the formula below, to create 4 super metrics:
- Max(${adapterkind=VMWARE, resourcekind=VirtualMachine, attribute=cpu|capacity_contentionPct, depth=2})
- Max(${adapterkind=VMWARE, resourcekind=VirtualMachine, attribute=mem|host_contentionPct, depth=2})
- Avg(${adapterkind=VMWARE, resourcekind=VirtualMachine, attribute=cpu|capacity_contentionPct, depth=2})
- Avg(${adapterkind=VMWARE, resourcekind=VirtualMachine, attribute=mem|host_contentionPct, depth=2})
That’s all you need to the get the first 2 line charts, out of the 5 that you need.
To get the “Total number of VM left in the cluster”, refer to Part 7, as it is the same formula. You just have a different threshold.
The above covers CPU and RAM. For Disk, refer to Part 7, as it is the same formula.
In Part 9 of this Capacity Management in SDDC (scheduled for late June), I will cover Network. It applies to all tiers, as you should not have drop packets in any tier, and your network utilization should in healthy ranges. As network is normally shared, it’s also easier to monitor per physical data center.
