Stay out of my way Nutanix

After being a specialist at Nutanix for 6 months, the difference in the way I spend my time is significant. I spend more time focused on application platforms and able to dive into a Hadoop distro or Elasticsearch and their associated tools with customers any time I want. I don’t spend much time in Prism or working with storage. In fact, I spend as little amount of time touching any Nutanix settings except to spin up new batches of apps.

Prism and the AHV stays out of my way. I spend what little time in Prism that I do cloning from a couple templates and then I’m done. I spend a little bit more time in Chef (it’s where I cut my teeth) and Saltstack (personal preference and speed). That I have more time to do this means I deploy platforms fast and can switch up my environment mix quickly and relatively easy. When it’s not easy, it means I’m learning something new about the application environment; which is great.

Besides things like Hadoop and Elasticsearch, I spend time working on platforms like Cloud Foundry and Kubernetes and Mesos. The nuanced differences as well as similarities in these are really fascinating to watch and work with customers. This is what I want to spend my time on. With all the time I spend speaking with customers, this is where customer admins would rather spend their time as well. These are the platforms their developers and line-of-business owners are staking their companies on when they say, “We need to do something with all of this data” or “We need to change our apps faster”. It’s integral to their jobs that they understand what’s going on here and how these are evolving.

I don’t spend a lot of time worrying about vm-centric management interfaces. The granularity is wrong for what I work on now and I don’t need to account for any features in a virtualization layer. Of course, if you string enough artificial management and automation layers together, you can build apps. I know that. I’ve done that, but it takes away time I could be spending directly in my platform workflow.

I don’t worry about storage provisioning or allocation like luns or RAID groups or arbitrary constructs like vSphere clusters or resource pools. I do however think about storage performance a lot differently. I can focus on scaling and sharding. I can focus on using intrinsic performance tools that help me actually have a performance dialogue with customers vs just performance confrontations. I can ask more intelligent questions about the workload, the data, and how the data transformation pipeline works.

For example, one of the arguments I’ve heard a lot is whether separating compute and storage so that they can be scaled independently is beneficial. One of the problems there is that usually means you are always dealing with one or the other being a bottleneck since it’s exceedingly rare that we can do capacity planning without any constraints. Also, when was the last time a workload didn’t need to actually pull or push any IO? The rate and variability is key to differentiating how data flows through any useful system. However, I would not have been as familiar with this in my specific areas of focus had I not been working for Nutanix. I can spend time in the application stack, looking at scaling, looking at the working set and better understanding where exactly any given IO is landing because I have that time. I’m not worrying about the virtualization layer or virtual infrastructure management that doesn’t help me learn more about the app platforms customers really care about.

In all, I feel well-rewarded working with Nutanix and the customers I speak with every day, around the world. I am reminded of working on AWS instances as AWS could also care less about forcing you to understand its virtualization layer, if you even know it has one. I use AWS or Nutanix and focus on what I need to build and what I want to learn about today, instead of saying, I’d love to learn more about something like Spark machine learning or Kubernetes 1.1, but only after I am done getting all of this virtual infrastructure patched up properly. I can also trace how this works and contrast something I did in AWS vs a Nutanix cluster because the management approach of both is very similar. Don’t bog me down with hardware management or virtual machine management. Let me build and learn and stay out of my way.