Industry executives and experts share their predictions for 2025.  Read them in this 17th annual VMblog.com series exclusive.

By Itiel Shwartz, the CTO and co-founder of Komodor

Here are several predictions for Kubernetes management in 2025, along with the implications for organizations:

• Prediction: The growing reliance on Kubernetes add-ons for functionality such as service mesh, CI/CD pipelines, and security will lead to unmanageable complexity. Organizations will struggle to keep up with upgrades, interdependencies, and troubleshooting multiple add-ons.

• Implications: Platform engineers and DevOps teams will need to invest in more sophisticated management tools to maintain control. Additionally, roles will evolve to require deeper expertise in managing add-on ecosystems to prevent cascading failures.

• Prediction: As more organizations deploy AI/ML workloads on Kubernetes, inefficiencies in resource allocation (e.g., underutilized GPUs or memory bottlenecks) will become more pronounced, causing operational and financial strain.

• Implications: AI/ML engineers will need to collaborate closely with Kubernetes administrators to set up guardrails that optimize resource use while preventing overprovisioning. Continuous performance tuning will become essential to ensure that workloads are running efficiently.

• Prediction: Generative AI (GenAI) will play a larger role in Kubernetes management, but building trust in AI recommendations and managing data privacy will remain challenges. Concerns around AI "hallucinations" and noisy signals could limit adoption.

• Implications: Platform and SRE engineers will need to adopt practices to validate and explain GenAI outputs before taking action, increasing operational workload. Data scientists will also have to ensure models meet stringent data privacy and regulatory requirements​.

• Prediction: The tool sprawl for managing Kubernetes environments will continue, with organizations using multiple overlapping tools for observability, security, and automation. Managing these tools will require dedicated personnel and increased budget allocations.

• Implications: Operations teams will prioritize centralizing management and observability platforms to reduce complexity and cost. Developers may find their workflows disrupted by tool-related inefficiencies, slowing down innovation​.

• Prediction: Security governance will evolve, with more organizations integrating policy-as-code solutions to enforce security standards at scale. Misconfigurations and policy violations will be frequent sources of security breaches.

• Implications: Security engineers will become key players in Kubernetes management, enforcing guardrails through tools like Open Policy Agent (OPA) and Kyverno. This will necessitate closer collaboration between security, DevOps, and compliance teams to minimize risk​.

• Prediction: As organizations increasingly bring databases and other stateful applications into Kubernetes, the trend is shifting away from relying solely on cloud providers' managed services. Running stateful applications within Kubernetes introduces new demands, particularly for managing data persistence, which Kubernetes wasn't originally designed to handle.

• Implications: This shift presents significant challenges for database administrators unfamiliar with Kubernetes, requiring either new skills or cross-functional roles that blend database and Kubernetes expertise. Additionally, Kubernetes storage and performance limitations could become bottlenecks, prompting teams to explore advanced configurations or specialized tools to ensure reliable, scalable data management.

• Explanation: As Kubernetes becomes an essential component for application deployment and infrastructure management, it risks slowing developers down, creating a need for platform engineering teams to streamline access and interactions. Developer portals will centralize tools, documentation, and resources, making it easier for engineers to work without requiring deep Kubernetes expertise.

• Implications: This trend will enable developers to work autonomously, reducing operational overhead and fostering collaboration between development and operations teams. As platform engineering matures, organizations will alleviate Kubernetes bottlenecks, driving innovation and creating a more developer-friendly environment for application deployment and management.

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ABOUT THE AUTHOR

Itiel Shwartz, the CTO and co-founder of Komodor, is an expert in Kubernetes, cloud-native technologies and infrastructure. He has served in technical leadership roles at eBay, Forter, and Rookout.