Kubernetes is an exciting new technology that many have struggled to define – and yet it is the very thing that will dramatically improve our day-to-day living.
The industry talks much about how managing applications with Kubernetes across multi-cloud infrastructure will reduce cost, improve flexibility and system reliability, etc. That sounds nice in theory, but how does Kubernetes actually enable innovation in the real world?
The answer lies in how cloud native platforms like Kubernetes, according to Gartner, will be the foundation of 95% of new digital initiatives by 2025.They are apps running behind the scenes in the cloud powering digital experiences, including phone apps, and eventually, every product or service we use.
With modern consumers expecting digital products to be always available, responsive, and constantly improving, Kubernetes is the critical infrastructure allowing organisations to deliver on these goals.
What separates smart cloud native apps from other cloud native apps is that they have AI built in, which already surrounds the average user in ways they probably don’t realise, between voice assistants like Siri, embedded in medical devices, recommendation engines, and driver assist.
Today, smart cloud native apps are already the defining attribute of winning products in a number of categories, and this trend will continue in the future. The advent of AI-powered smart cloud native apps will only increase the need for smart cloud native platforms that can automatically manage these complex workloads.
It’s the kind of tech transition that will make the jump from flip phones to the iPhone seem trivial.
How does Kubernetes affect the real world?
Tesla is perhaps one of the more obvious examples of how a company can harness AI. No, Tesla’s cars aren’t truly self-driving yet, but the company is rapidly obtaining new data from its fleet of customer-owned vehicles to continually make their AI better.
If Tesla wants to improve its AI behaviour at a stop sign, they send a command to the fleet to feed back video whenever one of their cars encounters a stop sign. Just days later, they can use new training data to improve their autopilot, release it in the next over-the-air software update, and progress to the next problem. The rapid iteration yields a positive feedback loop of product improvements that puts Tesla years ahead of its competitors that are not leveraging data and AI in this manner.
But it’s not just Tesla cars. With Kubernetes, the opportunity to quickly deploy, scale, and manage multi-cluster environments on an open-source container orchestration system has driven huge change across other sectors like healthcare.
It’s easy to forget that even MRI scanners run on software. But maintaining and upgrading that software has historically been painful, requiring taking down scanners and sending out technicians – ultimately reducing the number of patients seen daily. Kubernetes changed that for medical tech innovator GE Healthcare, allowing them to update MRI scanner software over the air – not too different from how Tesla manages software updates for their cars.
Other technology innovations within healthcare will also benefit immensely. DeepDOF is an AI-powered microscope that turns surgeons into superhuman doctors during operations by answering the all-important question, “did we get all the cancer tissue out?” This and other AI-guided surgical procedures can significantly improve patient outcomes, including combing through massive amounts of medical data at lightning speed to aid in patient diagnosis.
The skills gap elephant in the room
So why isn’t everyone already using Kubernetes then? Well, deploying Kubernetes is frankly hard.
For one, it differs greatly from traditional IT environments, and most organisations lack the necessary DevOps skills. The further you get into an AI-based smart cloud-native journey, the greater the need for advanced IT and automation skills to manage very complex tasks.
That specialism just isn’t in great supply. ESG Research previously found 67% of respondents are looking to hire IT generalists over IT specialists, adding further concerns for the future of application development and deployment, as seen by the over 900,000 misconfigured Kubernetes clusters exposed recently on the internet to potentially malicious scans and data-exposing cyberattacks.
If Kubernetes isn’t configured properly, nefarious actors may seize the opportunity to access internal resources and private assets that weren’t meant to be made public. Organisations will need to devote the time and resources to upskill DevOps staff through dedicated expert training, and ease of DevOps management through platform automation and user-friendly interfaces.
Despite the challenges, we must embrace a cloud-first mentality that includes AI and Kubernetes, without which organisations will inevitably fall behind competitors mastering these technologies. It’s about more than businesses deploying software faster – it’s paving the way for meaningful improvements to our standard of living that we thought unimaginable.