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Kubernetes in the Enterprise

Optimizing the Scale, Speed, and Intelligence of Cloud Operations

Over a decade in, Kubernetes is the central force in modern application delivery. However, as its adoption has matured, so have its challenges: sprawling toolchains, complex cluster architectures, escalating costs, and the balancing act between developer agility and operational control. Beyond running Kubernetes at scale, organizations must also tackle the cultural and strategic shifts needed to make it work for their teams.

As the industry pushes toward more intelligent and integrated operations, platform engineering and internal developer platforms are helping teams address issues like Kubernetes tool sprawl, while AI continues cementing its usefulness for optimizing cluster management, observability, and release pipelines.

DZone’s 2025 Kubernetes in the Enterprise Trend Report examines the realities of building and running Kubernetes in production today. Our research and expert-written articles explore how teams are streamlining workflows, modernizing legacy systems, and using Kubernetes as the foundation for the next wave of intelligent, scalable applications. Whether you’re on your first prod cluster or refining a globally distributed platform, this report delivers the data, perspectives, and practical takeaways you need to meet Kubernetes’ demands head-on.

Published: Sep. 18, 2025

Table of Contents

3
Welcome Letter
4
Key Research Findings: An Analysis of Results from DZone's 2025 Kubernetes Survey
28
Death by a Thousand YAMLs: Surviving Kubernetes Tool Sprawl
33
Boosting Developer Productivity in Kubernetes-Driven Workflows: A Practical Checklist
38
Running AI/ML on Kubernetes: From Prototype to Production: Use MLflow, KServe, and vLLM on Kubernetes to Ship Models With Confidence
45
Solutions Directory

Featured Authors

Boris Zaikin
Lead Solution Architect, CloudAstro GmBH
Yitaek Hwang
Software Engineer, NYDIG
Louis-Guillaume Morand
Cloud Solution Architect, Microsoft
G. Ryan Spain
Automation Advocate, Poet, Machine Learning Enthusiast
Lucy Marcum
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