Tag: nutanix

Install a bitnami image to Nutanix AHV cluster.

One of the nice things about using public cloud is the ability to use pre-canned application virtual appliances created by companies like Bitnami.

We can use these same appliance images on Nutanix AHV to easily do a Postgres database benchmark

Step 1. Get the bitnami image

Step 2. Unzip the file and convert the bitnami vmdk images to a single qcow2[1] file.

Put the bitnami.qcow2 image somewhere accessible to a browser, connected to the Prism service, then upload using the “Image Configuration”

Once the image is uploaded, it’s time to create a new VM based on that image

Once booted, you’ll see the bitnami logo and you can configure the bitnami passwords, enable ssh etc. using the console.

Enable/disable ssh in bitnami images
Connecting to Postgres in bitnami images
Note – when you “sudo -c postgres <some-psql-tool> the password it is asking for is the Postgres DB password (stored in ./bitnami-credentials) not any unix user password.

Once connected to the appliance we can use postgres and pgbench to generate simplistic database workload.

[1] Do this on a Linux box somewhere. For some reason the conversion failed using my qemu utilities installed via brew. Importing OVAs direct into AHV should be available in the future.

X-Ray scenario to demonstrate Nutanix ILM behavior.

Specifically a customer wanted to see how performance changes (and how quickly) as data moves from HDD to SSD automatically as data is accessed.  The access pattern is 100% random across the entire disk.

In a hybrid Flash/HDD system – “cold” data (i.e. data that has not been accessed for a long time) is moved from SSD to HDD when the SSD capacity is exhausted.  At some point in the future – that same data may become “hot” again, and so we want to make sure that the “newly hot” data is quickly moved back to the SSD tier.  The duration of the above chart is around 5 minutes – and we see that by, around the 3 minute mark the entire dataset is resident on the SSD tier.

This X-ray test uses a couple of neat tricks to demonstrate ILM behavior.

  • Edit container preferences to send sequential data immediately to HDD
  • Overwriting data with NUL/Zero bytes frees the underlying data on Nutanix filesystem

To demonstrate ILM from HDD to SSD (ad ultimately into the DRAM cache on the CVM) we first have to ensure that we have data on the HDD in the first place.  By default Nutanix OS will always try to write new data to SSD.  To circumvent that behavior we can edit the container preferences.  We use the fact that the “prefill” will be a sequential workload, while the measured workload will be a random workload. To make the change, use “ncli” to change the ” Sequential I/O Pri Order” to be HDD only.

In my case I happened to call my container “xray” since I didn’t want to change the default container. Now, when X-Ray executes the prefill stage, the data will land on HDD. As a second requirement, we want to see what happens when IO with different size blocks are issued so that we can get a chart similar to this: To achieve the desired behavior, we need to make sure that, at the beginning of each test, the data, again resides on HDD.  The problem is that the data is up-migrated during the test. To do this we do an initial overwrite of the entire disk with “NULL” bytes using  a parameter in fio “zero_buffers”.  This causes the data to be freed on the Nutanix filesystem.  Then we issue a normal profile with random data. Once the data is freed, then we know that the new initial writes will go to HDD – because we edited the container to do so. The overall test pattern looks like this

  • Create and clone VMs
  • Prefill with random data (Data will reside on HDD due to container edit)
  • Read disk with 16KB block size
  • Zero out the disks – to remove/free the up-migrated data
  • Prefill the disks with Radom data
  • Read disk with 32KB block size
  • Zero out the disks
  • Prefill with random daa
  • Read disk with 64KB block size

I have uploaded this x-ray test to GitHub : X-Ray Up-Migration test

 

 

HCI Performance testing made easy (Part 4)

What happens when power is lost to all nodes of a HCI Cluster?

Ever wondered what happens when all power is simultaneously lost on a HCI cluster?  One of the core principles of cloud design is that components are expected to fail, but the cluster as a whole should stay “up”.   We wanted to see what happens when all components fail at once, so we designed an X-Ray test to do exactly that.

We start an OLTP workload on every node in the cluster, then X-Ray connects to the IPMI port on each node, and powers off all the hosts while the cluster is under load.  In particular, the cluster is under read/write load (we need write workload, because we want to force the cluster to recover in-flight writes).

After power-off, we wait 10 seconds for everything to spin down, then immediately re-apply the power by connecting to the IPMI ports.

The nodes power up, and immediately start their POST (Power On Self Test) and boot the hypervisor.  The CVM will auto-start, discover the available nodes and form the cluster.

X-Ray polls the cluster manager (either Prism or vCenter) to determine that the cluster is “up” and then restarts the OLTP workload.

Our testing showed that our Nutanix cluster completed POST, and was ready to restart work in around 10 minutes.  Moreover, the time to achieve the recovery had very little variability. The chart below shows three separate runs on the same cluster.

This is the YAML file which defines the workload.  The full specification is on github.  The key part of the YAML is the nodes.PowerOff which connects to the IMPI ports of each node and vm_group.WaitForPowerOn which connects to either Nutanix Prism or vmware vCenter and determines that the cluster is formed, and ready to accept new work.