Kubernetes gets mentioned in almost every conversation about modern infrastructure, usually as if skipping it were a mistake. Our view is more cautious. It's an excellent tool for a certain size of problem. For many projects it's a heavy answer to a question nobody asked.
What it does
Once you have containers, you need something to run them: start them, restart them when they crash, spread them across several machines, route traffic to them, and roll out new versions without downtime. Kubernetes (often written K8s) does exactly that. You describe what you want ("run five copies of this app") and it works to keep reality matching your description.
It came out of Google's experience running huge systems, and it shows. It handles scale and failure very well.
What it costs you
The price isn't the software, which is free. It's everything around it.
Learning. There's a lot of vocabulary: pods, deployments, services, ingress, config maps, namespaces. A team new to it usually needs weeks to feel comfortable and much longer to feel confident.
Running it. Even with a managed offering from a cloud provider, someone has to understand upgrades, networking, security settings and what to do at 2 a.m. when something is stuck.
Money. Clusters have a baseline cost before your app does anything. A small app can cost far more to run on Kubernetes than on a single modest server.
Complexity in debugging. When something fails, the cause may be in your code, the container, the cluster network, a resource limit or a misconfigured setting. More layers means more places to look.
Signs you may be ready
Kubernetes tends to make sense when several of these are true at once:
- You run many services, and they need to scale independently.
- Traffic swings a lot, and you want capacity to grow and shrink automatically.
- You have a team, or can hire someone, who can own the platform.
- You need releases without downtime and quick rollbacks across many services.
- You manage several environments and want them to behave the same way.
Signs you're probably not
If you have one or two applications, modest traffic and a small team, the honest answer is usually no. A common sign of over-engineering is a team of three spending more time on the cluster than on the product.
Simpler options to try first
A single server with Docker Compose. It's surprising how far this goes. A decent virtual machine can serve a lot of traffic, and the setup is easy to understand.
A managed platform. Services where you hand over your code or container and they handle the servers, scaling and certificates. You trade some control for a lot less work.
Serverless functions for spiky or event-driven parts of the system, as we covered in our piece on serverless.
Managed container services from the big cloud providers, which run your containers without making you operate a full cluster.
Each of these can be a stepping stone. Start simple, and move up when you hit a real limit, such as needing finer control or running into scale problems. Moving later is much easier than undoing a premature migration.
If you do go for it
Use a managed Kubernetes service rather than running the control plane yourself. Start with one small, non-critical workload. Put your configuration in version control. Set resource limits so one runaway app can't starve the rest. Add monitoring and logging from day one. And keep your team's skills in step: training takes time, so plan for it.
The honest summary
Ask what problem you're solving. If the answer is "we need to run many services reliably at changing scale," Kubernetes may be exactly right. If the answer is "everybody else uses it," keep looking. The best infrastructure is the simplest one that meets your needs today and doesn't block you tomorrow.
