Understanding VMware Capacity - Cluster Memory ( 8 of 10)

Today we'll look at measuring memory capacity in the cluster, just a reminder that in Friday's blog  we discussed where ballooning is persistent (rather than an occasional spike), and that changes should be made in order to ensure there is enough RAM available for the VMs in the cluster.

I explained that ballooning itself has an overhead on the hypervisor and as such there is the potential to impact performance for the host. Changes don’t necessarily have to be more RAM installed. The very first thing to consider is if any VMs have been created and “forgotten” about.If we look the cluster as a whole we can see a significant event at the same time the previous VM saw the balloon inflate in memory.

Shared memory plummets, this causes an increase in the demand on memory and, in turn this causes the balloon driver (memory control), to consume more memory, and the swapped memory to increase.

Then, shared memory slowly recovers. The process to identify shares pages only checks a set number of pages each interval. So it takes a while to identify all the shared pages and free up the space taken by duplicates. 

What caused the shared memory to drop so much? Windows updates and a reboot. When a VM starts every page is unique until a duplicate is identified, which takes a short while.

The question we tend to be asked is: How can we model what will happen to our VMware clusters? Typically the underlying questions are more like:

When do I need to buy more hosts?  As in: I need to figure out my budget for the next 12 months, and I’ve no idea if there needs to be any money set aside for hardware purchases.

Will planned projects fit?  I know we have new things planned but I don’t know if they are going to impact our forecasts for the hardware we may need.

How many more VMs can we provision?  I’m used to talking about rack space and space in the datacenter, so give me something I can understand to determine how much space is left.

I've run a webinar on VMware Cluster Planning and you can listen to the recording here

https://attendee.gotowebinar.com/recording/4370618472757209089

On Wednesday I'll be looking at measuring Disk Storage Latency and I'll also be broadcasting live with our 'Top 5 VMware Tips for Performance and Capacity', if you haven't registered for this event then you've still got time to do so.

https://www.metron-athene.com/services/webinars/capacity-management-webinars.html

Phil Bell

Consultant

5 Top Performance and Capacity Concerns for VMware - Cluster Trending.

I tend to trend on Clusters the most.

VMs and Resource Pools have soft limits so they are the easiest and quickest to change.

Want to know when you’ll run out of capacity?

–       The hardware is the limit

–       Trend hardware utilization

The graph below shows a trend on 5 minute data for average CPU and shows a nice flat trend.

If I take the same data and trend on the peak hour then I see a difference.

You can see that the trend has a steady increase, the peaks are getting larger.

When trending ensure that you trend to cope with the peaks, to deliver immediate value, as these are what you will need to deal with.

Aggregating the Data

Next let’s look at aggregating the data. Previously we looked at Ready Time and as I said Ready Time is accumulated against a virtual machine but you can aggregate this data to see what is going on in the Cluster as a whole.

In the example below CPU utilization is not that busy but there is a steady increase in Ready Time.

The dynamic may be changing and new VM’s that are being created have more CPU’s, which could eventually cause a problem.

I hope you've enjoyed the series and for more VMware white papers and on-demand webinars join our Community and get free access to some great resources.

http://www.metron-athene.com/_resources/login.asp

Phil Bell

Consultant

5 Top Performance and Capacity Concerns for VMware - Cluster Memory

As I mentioned on Monday the next place to look at for memory issues is at the Cluster.

It is useful to look at:

–       Average memory usage of total memory available

–       Average amount of memory used by memory control

–       Average memory shared across the VM’s

–       Average swap space in use

In the graph below we can see that when the shared memory drops the individual memory usage increases.

In addition to that swapping and memory control increased at the same time.

If it isn’t memory that people are talking to us about then it's storage and that's what we'll take a look at on Friday.

Phil Bell

Consultant