The Donkey has a well know reputation for stubbornness,
a strong sense of self-preservation, means it’s difficult to force a donkey into doing something it perceives to be dangerous.
Yet, Donkeys can be very dependable, although cautious they are also, intelligent, friendly, playful, and eager to learn. (Ref: wikipedia.org/wiki/Donkey)
The Managed Service Model
One of the terrifying ideas that crystalized for me during VMworld Europe was that the industry is going down a road that will take many of us way out of our comfort zones.
Here are a couple of samples…
Amazon RDS on VMware; I’ve been deploying RDS databases in AWS over the last 18 months, it’s a great service, making it super simple to provision SQL databases. Now VMware are going to offer a service where Amazon automate the provisioning of your databases on-premises. No need to worry about operating systems, this is a managed service, database patching, and a point-in-time restore service comes included. You will be able to deploy RDS on premises with a high-availability/recovery to AWS cloud. The simplicity of Amazon RDS for your on-premises deployments.
Another example of a managed service is the Dell EMC VxRack SDDC, by integrating DELL HCI hardware with VMware Cloud Foundation, pre-defined automation will stand up a complete VMware based cloud environment following best practice VMware validated designs. Once you are up and running patching and management is done by vendor support.
So how do you feel about that? public cloud in my data center. You can try and argue it’s insecure, but really start checking and these guys have better security than most.
Undifferentiated heavy lifting
This is a term frequently used to describe the boring, tedious repetitive work we have come to love, whether it’s checking the hardware compatibility lists, patching firmware or kernels, configuring networking, even setting up vCenter, really it’s donkey work and none of it adds differentiating value to the business.
The joke I am hearing is that nobody ever got praised for doing a good job of keeping systems patched. Don’t take it personally but it doesn’t make any difference to your CEO who does this work.
These leads on to the technical debt argument, IT departments spend too much time on keeping everything running and not enough time on innovation.
So lets start with a question, why did you get into IT? because you like patching firmware or you love the innovation, do you have passion for how technology can improve so much of what we do.
Here is where the good news starts, technology is increasingly a major differentiator of success organisations.
New stuff that adds value
The best people to implement change in an organisation are those that know it. As IT moves from being a cost center to a fundamental driver of innovation, we will need to pivot, learn new skills and help the organisations that employee us.
Here is a list (far from complete, and certainly not authoritative) on career pivots.
- vSphere/Systems administrators – Security spend is set to increase, learn compliance and security. If you like scripting then automation is a natural progression. Network virtualization looks as if it might do for networks what ESXi did for servers. Get on the devops bandwagon with containers, or push the limits with serverless. Public cloud is a tsunami that no one will stop, it will soon be essential to know at least the basics. Other areas to investigate are EUC, IoT and Edge Computing.
- Storage administrator – Converged infrastructure is going to eat a big chunk of traditional storage, but anyone who understand how to work with large sets of data is going to be worth a lot, Diane Greene (CEO at Google Cloud) recently said “data is the new oil”, for Machine Learning/Artificial Intelligence to work, lots of data needs to be stored, big data, massive data, so learning how to feed data lakes, efficiently store and clean and ship data is going to be really important. Security, IoT and Edge Computing skill will probably combine in this space.
- Database administrator – It’s been said only 1% of unstructured data and 50% of structured data is being used in ML/AI, now is a great time to start on the learning path. Similar to the storage admin, folks who know how to work with and query large data sets, are going to be in demand. Other areas are no-sql databases and working closely with developers to improve application design.
Of course, learning about new technologies is an effort, maybe at first there won’t even be support or understanding of what you are trying to do. There are challenges ahead, even the risk that you make a career pivot in the wrong direction.
It’s the business that will decide on managed services, we can try and resist, but it’s in everyones best interest if we take a step forward.