[PDF] Data on Kubernetes 2025

security enhancements, and scaling initiatives. This is particularly acute for organizations running AI/ML workloads, where storage costs (50%) have become the primary concern — reflecting the enormous data requirements of training datasets, model checkpoints, and inference results for large-scale AI deployments. 2. The AI/ML Revolution Accelerates: While databases maintain their #1 … 4. Performance Gaps Reveal Optimization Opportunities: Despite widespread adoption, performance bottlenecks persist. Storage I/O performance is cited as the primary concern, followed closely by model/ data loading times. These gaps represent both challenges and opportunities for the ecosystem to deliver better tooling, practices, and infrastructure. … revenue to these deployments. However, maturity brings new challenges. The top operational concerns are no longer about basic adoption but about optimization: performance optimization (46%), security and compliance (42%), and talent/skills gaps (40%). The skills gap is particularly acute — organizations need practitioners who understand both Kubernetes operations AND data workload optimization. … performance bottleneck (24%), followed closely by model/data loading times (23%), indicating that data access patterns are the primary constraint for DoK workloads • Organizations implement numerous storage strategies: Object storage integration (43%), local SSDs for performance (43%), caching layers (42%), block storage (42%) … Performance Bottlenecks Biggest Performance Bottlenecks What is your biggest performance bottleneck with data workloads on Kubernetes? Storage and data movement dominate the bottleneck list, validating the focus on storage acceleration techniques. 0 10 20 30 40 50 Object storage (S3, GCS, Azure Blob, etc.) … 16 Data on Kubernetes Report 2025 AI/ML Top Cost Concerns The cost landscape has shifted dramatically: Primary Cost Concerns (AI/ML Workloads) If you use AI/ML: What is your biggest cost concern with AI/ML workloads on Kubernetes? (Select top THREE) Storage costs have emerged as the dominant concern, reflecting: … 17 Data on Kubernetes Report 2025 Operational Challenges and Governance Top Operational Challenges The nature of challenges has evolved from adoption to optimization: Top 3 Operational Challenges What are your TOP 3 operational challenges with DoK today? (Select up to THREE) Performance optimization has emerged as the #1 challenge, displacing earlier concerns about basic … Top Concerns What’s your biggest concern about DoK in the next year? Security has emerged as the #1 concern, likely driven by: • High-profile Kubernetes security incidents • Complexity of securing distributed data workloads • Regulatory compliance requirements • AI/ML data sensitivity 0 10 20