D2iQ Survey Sees Increased Enterprise K8s Deployments

Kubernetes adoption in production environments has reached critical mass in the enterprise, with a D2iQ survey of 300 IT professionals finding more than half of respondents (53%) currently running Kubernetes in a production environment.

The survey, conducted by Vanson Bourne on behalf of D2iQ, a provider of a platform for managing Kubernetes clusters, also finds more than three-quarters of organizations (77%) reporting it required six months or less to deploy Kubernetes in a production environment. The average time that it took to deploy Kubernetes in a production environment was four and a half months, the survey finds.

Overall, the study finds three-quarters of organizations (75%) are using Kubernetes in production or pre-production environments. However, only 42% of respondents claim that all applications running on Kubernetes have been successfully deployed.

Overall, the survey finds well over a third of respondents (36%) that are now successfully running Kubernetes say it is critical to the long-term success of their company, with 43% of respondents citing data analytics or machine learning as the most popular Kubernetes workload. Artificial intelligence (AI) and machine learning (ML) workloads are the most widely deployed workloads on Kubernetes (40%).

A full 88% of respondents also identified Kubernetes as the platform of choice for running AI and ML workloads within the next two years. Rounding out the top three most popular Kubernetes workloads were Windows containers (34%) and distributed data services (33%), according to the survey.

D2iQ CEO Tobi Knaup says that as more applications become infused with ML algorithms, the more likely it is that organizations will need a platform capable of orchestrating the massive number of containers required to build those applications.

Ultimately, Knaup says most organizations will find themselves running fleets of Kubernetes clusters rather than a small number of clusters hosting multiple applications. Application owners generally prefer to have their own dedicated infrastructure whenever possible versus being required to share a cluster with another team.

The D2iQ survey also suggests that developers are finally warming up to Kubernetes, with 41% of the developers that responded to the survey saying they are excited to come to work every day. However, nearly a quarter of developers (23%) noted that Kubernetes makes them feel extremely burned out.

Regardless of how organizations approach Kubernetes management, it’s certain that in 2022 more IT teams will be exposed to Kubernetes than ever before. The challenge—both now and in the future—is finding a way to make all those Kubernetes pods and clusters a lot simpler to deploy and manage. The simple fact is there are not enough site reliability engineers (SREs) available to manage all the Kubernetes clusters that an enterprise IT organization might need to deploy. There’s a need for higher levels of abstraction to make Kubernetes clusters more accessible to the average IT administrator. In effect, managing Kubernetes clusters is becoming a team sport requiring varying levels of IT expertise depending on the nature of the task at hand.