From Warm-Up Act to Headliner: The Rise of Kubernetes
In the world of entertainment, yesterday’s warm up band can become the headliner for the biggest stages across the globe. Kubernetes 1.0 was launched in July of 2015. That release began the transformation from the traditional approach of an application running on each virtual server to the concept of containerization in which multiple applications can run on the same host OS, reducing overhead and increasing flexibility.
Containers are lightweight, portable, and scalable, often hosted on virtualization infrastructure in enterprise environments. Virtualization in a container environment shifts from hardware-level to OS-level virtualization. Though enterprises still utilize virtualization infrastructure to host containers, virtualization now shares the stage with Kubernetes, which has become the de facto standard for container orchestration. Kubernetes plays a pivotal role in defining how applications are developed and deployed today and offers numerous benefits:
- Reliability and performance to meet the specific needs of applications
- Multi-cloud & hybrid support that allows seamless app deployment across different environments
- Flexibility to run workloads across multiple cloud providers to minimize vendor lock in
- Automated scaling that enables applications to efficiently handle varying workload demands
- Enhanced security through built-in isolation and network policy controls
AI and Microservices: A Perfect Match for Kubernetes
Don’t think about Kubernetes as a one-hit wonder, however. In fact, we haven’t even witnessed the best work of Kubernetes. While Kubernetes wasn’t originally designed for AI, its strengths align perfectly with modern AI applications, which are often built using microservices architecture and thrive in containerized, clustered environments. This makes Kubernetes a natural fit for existing and future AI development.
AI applications increasingly rely on distributed, containerized ecosystems, and Kubernetes delivers exactly that. Deploying AI without orchestration like Kubernetes can lead to fragmented infrastructure, manual scaling headaches, and wasted resources. With Kubernetes, AI/ML workloads scale dynamically based on demand, ensuring efficient resource use. It allocates CPU, RAM, and GPUs based on workload needs, optimizing performance while minimizing overspending on infrastructure.
AI Anywhere with Kubernetes
AI workloads often span diverse environments, from on-premises data centers to cloud platforms and edge computing setups.
Kubernetes simplifies multi-cloud and hybrid deployments with a consistent API across these infrastructure types. Like VMware’s agnostic approach, where virtual machines deploy seamlessly onto any compatible host, Kubernetes offers a unified abstraction layer—enabling AI applications to run on on-premises servers, Google Cloud, Azure, or AWS. Wherever Kubernetes operates, your AI can follow, delivering flexibility to meet nearly any deployment need.
Kubernetes Means Faster Iteration and Deployment
You want developers doing what they do best – developing —not slowed down by deployment hurdles. By standardizing on Kubernetes, organizations can ensure that their developers can deploy applications without worrying about the underlying infrastructure, while developers continue working in a familiar environment. This consistent platform simplifies the process and speeds up time-to-market for new applications, keeping developers productive in a streamlined environment. There are other accelerators too:
- GPU acceleration by letting developers request GPU resources for pod
- Flexible resource allocation through predefined cluster resources, avoiding manual VM requests
- Rapid experimentation, enabling developers to test various AI models, configurations, and parameters
How to Find Kubernetes Expertise
Successfully implementing Kubernetes goes beyond mastering the platform—it requires a deep understanding of the infrastructure, integrations, and systems it supports. A holistic approach is essential, encompassing resilient cluster design, secure architecture, and seamless integration with your existing environment.
At Evolving Solutions and Keyva, our Kubernetes expertise extends past the platform to your broader IT and business needs. While Kubernetes outperforms traditional virtual machine environments in flexibility and efficiency, its complexity can be daunting. That’s where we shine—whether architecting your infrastructure from the ground up, managing the project end-to-end, or partnering with your team to tackle challenges and fill knowledge gaps. We optimize Kubernetes for performance, security, and scalability.
Over the past decade, Kubernetes has grown from a container orchestration tool into the backbone of modern application management. It’s about enabling an efficient, scalable, and secure IT ecosystem—a transformation we can help you achieve.
Want to see how Kubernetes can keep you ahead of the competition? Let’s talk!
