The 2024 Data on Kubernetes (DoK) Report has been released, revealing significant shifts in how organizations are leveraging Kubernetes beyond its traditional container orchestration role. Based on a survey of 150 technology leaders, the report shows Kubernetes is increasingly becoming foundational infrastructure for AI/ML workloads while continuing to excel at traditional data workloads.
Key Findings
Production Maturity Reaches New Heights
Nearly half of organizations now run 50% or more of their data workloads on Kubernetes in production, with leading organizations pushing past 75%. This represents a significant shift from experimental to production deployments, particularly for mission-critical database workloads which remain the most common use case for the third consecutive year.
AI/ML Emerges as Strategic Priority
Organizations are increasingly leveraging Kubernetes as their AI infrastructure foundation. Teams report improved resource utilization through advanced scheduling mechanisms, particularly for GPU workloads, while calling for enhanced capabilities in batch scheduling, preemption, and gang scheduling to better support AI/ML workloads.
Technical Challenges Remain
While adoption grows, teams still face hurdles with open source feature maturity and integration with existing tools. For AI/ML workloads specifically, organizations cite high compute costs and insufficient Kubernetes expertise within data teams as key challenges to address.
Get the Full Report
Download the complete report including detailed analysis of workload trends, technical requirements, and future outlook.
Download it to learn:
- Detailed breakdown of workload types and their evolution since 2021
- Specific technical capabilities needed for AI/ML workloads
- Key benefits organizations are achieving with DoK
- Future technical priorities and areas of investment