Kubernetes Is Not For Everyone: A Look With 20 Years of Experience

The most expensive mistake of my career wasn’t a line of code; it was a ‘yes’. Years ago, when “Let’s use Kubernetes” was suggested for a project, I remember saying “yes” without questioning, swept up in the popularity of the moment. Since that day, I’ve struggled with the operational burden, unexpected costs, and complexity that decision brought. Today, with 20 years of system architecture and operations experience, I believe it’s time to question whether Kubernetes is truly the right solution for everyone.

A Tool in the Shadow of Popular Culture

Today, Kubernetes is seen as the undisputed leader in container orchestration. Its name comes up whenever a new project starts, whenever a technology trend is discussed. But this popularity creates a huge expectation: an perception that Kubernetes is the solution to every problem, the cornerstone of every system. This perception can lead many teams, especially those with simpler scale and needs, down an unnecessarily complex and costly path.

While developing an ERP system for a manufacturing company, we were trying to automate workflows and data management. Initially, a simple PostgreSQL database and backend services written with FastAPI were sufficient. But after a while, driven by the idea of “let’s be more scalable,” we decided to switch to Kubernetes. This transition not only forced us to build an additional team just to manage the infrastructure, but also incredibly slowed down our deployment processes.

Operational Burden Beyond Cost

One of the biggest burdens Kubernetes brings is undoubtedly operational complexity. Its setup, maintenance, updates, and security require significant expertise and time. Even setting up a basic cluster is a project in itself. Then come topics like monitoring, logging, alerting, network policy management, and storage management, all requiring continuous attention and effort. Even if managed Kubernetes services are used to alleviate this burden, these services also have their own costs and limitations.

Once, I managed a few web applications hosted on my own virtual private servers (VPS). With simple Nginx configurations, systemd services, and Docker Compose, everything was running smoothly. I had the comfort of knowing these systems were stable while doing my daily work. But after switching to Kubernetes, midnight alerts, unexpected restarts of pods in the cluster, and hours-long debugging sessions to find the source of errors became a part of my life. This situation negatively affected the motivation of not only me but everyone on my team.

When Should You Consider Kubernetes?

So, when does Kubernetes become a sensible option? The answer, of course, is scale and complexity. If your applications consist of many microservices, receive heavy traffic, and require continuous, rapid deployments, Kubernetes can handle this load. Its capabilities like dynamic scaling, self-healing features, and advanced service discovery can be invaluable for large-scale distributed systems.

For example, imagine I’m managing the operations of a large e-commerce platform or a global SaaS product. In a system serving millions of users and consisting of hundreds of microservices, it would be almost impossible to stay afloat without the flexibility and automation capabilities offered by Kubernetes. In such scenarios, the initial cost and operational burden brought by Kubernetes are balanced by the benefits it provides.

Conclusion: Pragmatism is Key

Based on my 20 years of experience, I can say that in technology choices, it is vital to consider the required scale, complexity, and most importantly, the cost, rather than blindly following popular trends. Kubernetes is a powerful tool, but it is not a panacea for every problem. In my own projects and in places I’ve consulted, I have always tried to choose the “most suitable” technology rather than the “best” technology. This often means less complex, less costly, and more sustainable solutions.

Don’t you agree that Kubernetes is an unnecessarily complex solution in many cases? What have you observed on this topic in your own experiences?

Frequently Asked Questions

Common questions readers have about this article.

What should be considered before choosing Kubernetes?

Before choosing Kubernetes, I evaluated the scale, complexity, and actual needs of my project. A simple PostgreSQL database and backend services written with FastAPI were sufficient, but we had to switch to Kubernetes due to scalability concerns. Now I understand that we should have thoroughly evaluated the operational burden and costs this decision would bring.

What strategies can you use to reduce the operational burden of Kubernetes?

To reduce the operational burden of Kubernetes, I use automation tools and continuous integration/deployment tools. Additionally, working with small and agile teams, avoiding unnecessary complexity, and continuous monitoring and updating also help reduce the operational burden.

What are the advantages and disadvantages of Kubernetes?

I believe the advantages of Kubernetes include scalability, flexibility, and high availability. However, I see its disadvantages as operational complexity, high cost, and the need for specialized expertise. When evaluating the real needs of my project, sometimes the disadvantages of Kubernetes can outweigh its advantages.

How can you learn from mistakes made using Kubernetes?

I learned from mistakes made using Kubernetes, especially from unnecessarily moving to a complex system due to scalability concerns. Now, I try to evaluate the real needs of my project and avoid unnecessary complexity. Also, I try to reduce the operational burden by using continuous monitoring, updating, and automation tools.