How will we manage the data center in 2030? The history of tech tells us that a lot can happen in 12 years. For example, lets look at what has happened in the past 12 years beginning in 20016. Technology has changed significantly with advances that have included the iPhone, Facebook, Twitter, Flash storage drives, and cloud computing.

During the 12 years before that (1994 2006), the introduction of many technologies we take for granted today came to fruition. Tech, such as jpegs, Apache Web Server, Boewolf Clusters, flash scripting, Google, texting, extensible markup language, Wi-FI, Napster, YouTube, VMware (virtualization), and multi-core processers came to market between 1994 and 2006.

Each of the afore-mentioned technologies has had an impact on data center operations. If we look forward to the data center in 2030, what will we see?

Vendor-supplied collaboration software packages will be delivered via SaaS

Data centers of 2030 will move away from expending time and on supporting collaboration software packages like Skype, email, and chat. If the application doesn’t directly do something that impacts a company’s mission, they will feel comfortable allowing the vendor to manage the software in a SaaS application.

What does this mean for IT admins? Your responsibilities are to your organizations data, and not all of that data is going to live inside the onsite datacenters that you physically manage today. Take time to learn and understand the the contracts you have with SaaS companies when it comes to the security and portability of your companys data. This will allow you to transform to modern technology and make a transition to architecting with policies instead of some of the traditional methods of the past.

The Data Center of 2030 will run Big data/HPC/ML/DL/AI workloads as the common app

Artificial Intelligence (AI) has been around since the 1950s, went through an AI winter for several years when research was defunded, and no one really paid attention to it. As machine power has increased, not to mention the amount of digital data available, AI is making a comeback. Part of the reason is because of Machine Learning (ML) and Deep Learning (DL). ML takes a human to write the provide the training data that teaches a program to learn from a data set. DL can skip the human intervention, using a neural network that requires an incredible amount of computational power. But NVidia realized that GPUs could be used for more than video games, and it has enabled this field. They have an excellent blog post on the differences of AI/ML/DL.

There are a few technology trends converging to make this a perfect storm:

  • Faster processing speeds
  • Accelerator technologies (e.g. GPUs)
  • The ability to store and access larger quantities of data
  • The ability to collect data from machines and sensors

The main that that differentiates an organization is their data. What if a communications company could instantly translate the content they produced? What if a department store could create the perfect shopping experience for you (in their store or online) based on the content they collect about you? Or what if a training organization wanted to use virtual reality to build training for jobs that are difficult to train for, surgery for example?

Consider an example of a company that is collecting data from customers based on how they interact with devices in their homes (Alexa, cell phone apps, smart appliances and devices). All of this data can be collected in a big data lake. Then HPC/ML/DL can be used to make sense from all of the data that is just sitting there. Coaxing the data to give up its secrets will become the secret sauce of organizations in 2030.

These applications are dependent on specialized ideas, or data that has been collected by an individual company. They are not things that will be trusted to the cloud. Organizations may want to go server-less, so that the data scientists are spending all of their energy on creating opportunities from data that they have gathered, but someone will still need to manage that data from the platform being presented to developers down to the metal.

Will you be up for the challenge and be ready for the transitions we will see in the data center of 2030?