In the year 2022, more database and analytics workloads were run on Kubernetes.

The results of a recent poll by the Data on Kubernetes (DoK) Community show that, compared to the prior year, a staggering 26 percentage points more companies would run their databases on Kubernetes in 2022.

Participants in the most recent survey reported using databases on Kubernetes at a rate of 76%, a significant rise from the 50% number from the previous year. The survey's results indicate that the quantity of work associated with analytics has substantially expanded, rising from 39% to 67%.

Executing stateful apps, which are defined as programs that save data to persistent disk storage, is not in general a very common activity. In the 2021 user survey, which was performed by the Cloud Native Computing Foundation a year ago, 55% of participants had already started doing this. However, based on the results of the DoK research, it appears that the range of application types that require data and run on Kubernetes is growing.

A total of over 500 Kubernetes users that manage data workloads on Kubernetes were questioned in order to assemble the conclusions of the new investigation. Consistency and simplicity of management, both of which are necessary to ensure that widespread production use of containers can be handled, are what drive the running of data workloads on Kubernetes. The best platform for running data workloads is Kubernetes.

It is significant to note that among those that use Kubernetes for data, the use of persistent storage did not rise, and workloads involving streaming or messaging actually decreased.

Data on Kubernetes Is a Day 2 Operations Issue

The DoK report’s other key findings included:

• The majority of respondents (72%) have been managing their data workloads with Kubernetes for more than a year. The study's participants with some prior experience managing Day 2 operations (production) expressed a broad level of satisfaction with the various types of stateful workloads that are currently being run on Kubernetes.
• The majority of people say that the hardest part of managing data workloads on Kubernetes is automating application provisioning and configuration management.
• Operators are being used by 66% of survey respondents to run data on Kubernetes. If the operators can also deal with Day 2 challenges like observability and the management of the storage lifetime, this can help with some of the issues related to data management.

Transformative Impact on Organizations

The survey revealed a consensus that running data workloads on Kubernetes has a transformative impact on organizations. Perception of value is high, yet may overestimate real benefits.

1. One-third of respondents (33%), and another 51%, reported at least a somewhat positive impact on productivity. Running data on Kubernetes is having a revolutionary impact on productivity. The figures were just slightly lower when inquiries concerning the effect on revenue were made.
2. Sixty-seven percent of respondents stated that their companies and/or developers are at least 50% more productive after deploying Kubernetes for data load management. In the DoK research from the previous year, that number increased from 57%. However, at least for the foreseeable future, this cannot be contrasted with actual productivity standards.
3. More than half (54%) of respondents think that more than 10% of the revenue that their firm produces can be directly attributed to its ability to run data on Kubernetes. By taking a step back, we have determined that this relationship between Kubernetes and revenue is, at most, tenuous. According to more than 52 percent of businesses, Kubernetes manages more than 50 percent of their data workloads. Running production workloads on Kubernetes infrastructure, however, is not the same as having these workloads generate revenue for the company.

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