Kubernetes is maturing, and the teams that have been using it since its infancy are maturing as well. Those early adopters are now coming into their own, able to augment Kubernetes basic capabilities in new ways based on their expertise and the expansion of the cloud-native ecosystem.
Businesses are continuing to scale and expand their Kubernetes deployments to meet their hybrid, multi-cloud needs. As businesses look to the future, Kubernetes’ declarative API and robust reconciliation loop will be crucial in unifying and bringing a more consistent approach to how they define, manage, and secure our digital capabilities across public and private cloud environments.
According to a 2020 survey by Gartner, more than 75% of worldwide enterprises will operate containerized apps in production by 2022, up from fewer than 30% in 2020.
With that in mind, here are a few major Kubernetes trends to keep an eye on as the New Year begins.
Kubernetes as an all-purpose platform?
Containers and Kubernetes go hand in hand. That hasn’t changed, and it won’t change in 2022. The types of apps that teams manage with their Kubernetes-based platform will continue to evolve in 2022 and beyond.
Users in the early days of Kubernetes often constructed their own on-premises platforms and deployed a smaller collection of applications. However, as Kubernetes has become more stable, usage patterns have evolved substantially.
Most early Kubernetes apps were stateless, for example, but the earlier notion that Kubernetes wasn’t good with state, no longer holds true.
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While enterprises have already seen a wide range of applications operate in containers, Kubernetes is starting to see more firms migrate their mission-critical, stateful applications. Databases, event-driven messaging, and mission-critical applications are expected to migrate to Kubernetes in order to benefit from its scalability, security, and portability.
Kubernetes with AI/ML have become a power couple
In AI and machine learning, Kubernetes’ maturity and ability to handle more complicated use cases are likely most evident. Kubernetes is quickly becoming the platform of choice for serving AI and machine learning workloads in production. It’s a potent combination that will have significant business ramifications in the coming years.
One area that sticks out among all the applications running on Kubernetes is AI/ML. The ability to improve and enhance various sorts of applications grows as data science becomes a crucial position within practically every organization. AI/ML is influencing practically every element of modern business, from improving customer interactions to making better data-driven decisions to things like modeling autonomous vehicles.
Just as containerization’s benefits necessitated a more efficient way to manage everything in production, AI/huge ML’s promise necessitates a rock-solid IT basis to realize.
The only thing hotter than Kubernetes is Kubernetes talent
For the foreseeable future, Kubernetes skills and cloud-native talents, in general, will be in high demand. At the present, it’s difficult to locate a reliable source and in 2022, demand will almost probably outstrip supply once more.
Kubernetes and cloud-native in general – adoption shows no signs of slowing. More companies are expected to continue their shift to the cloud and grow their usage of micro services, serverless, and other cloud-native technologies, according to analysts. Most importantly, more enterprises are anticipated to recognize the critical interplay between Kubernetes, Linux, and DevOps.
The globally diversified and open technical community that has contributed to the development of a thriving cloud-native ecosystem will continue to grow. The need for enterprises of all sizes to onboard engineers with these abilities to allow vital transformational work will continue to grow, as will the number of people looking to gain knowledge and skills related to Kubernetes and the cloud-native ecosystem.