Does your startup need Kubernetes? When it pays off, and what to use until then

Most early-stage startups don't need Kubernetes yet. If your product is a web app, an API and a database, a managed container platform such as Google Cloud Run, AWS Fargate or Azure Container Apps runs the same containers with no cluster to look after. Kubernetes starts to pay off when you run many services that depend on each other, need control the simpler platforms don't give you, and have someone who can own the cluster every month. This guide covers what Kubernetes does, what a cluster costs, the upkeep nobody budgets for, and a checklist for deciding.

What Kubernetes does, and what it leaves to you

The project describes itself as "a portable, extensible, open source platform for managing containerized workloads and services". In practice it gives you a set of building blocks that are hard to get right by hand:

• Service discovery and load balancing: each service gets a stable name, and traffic is spread across healthy copies.
• Rollouts and rollbacks: you describe the version you want, and Kubernetes moves to it at a controlled rate.
• Self-healing: it restarts containers that fail and stops sending traffic to ones that don't pass their health check.
• Secrets and configuration: passwords and settings change without rebuilding images.
• Horizontal scaling: more copies when CPU use rises, fewer when it drops.

The same page is just as clear about what Kubernetes is not. It does not build your application or deploy source code, does not provide databases or message queues as built-in services, and does not dictate your logging, monitoring or alerting. A cluster is a foundation: your build pipeline, monitoring, alerts and database backups still sit on top of it, and someone has to choose, set up and run each of them.

What a managed cluster costs

Few small teams run the Kubernetes control plane themselves: the three large clouds sell it as a managed service. Their list prices for the control plane alone:

• Amazon EKS: $0.10 per cluster per hour on standard support. At 730 hours a month, that is about $73 per cluster before a single server. Once a version's first 14 months of standard support on EKS are over, the cluster moves to extended support at $0.60 per hour, about $438 a month. Servers (EC2), disks, public IP addresses and some network traffic are billed separately.
• Google Kubernetes Engine: the same $0.10 per cluster per hour, but the free tier gives $74.40 in monthly credits per billing account, "equivalent to one free Autopilot or zonal Standard cluster per month". Compute is billed on top.
• Azure Kubernetes Service: the Free tier has free cluster management but no financially backed uptime SLA, and Microsoft recommends it for development, testing and clusters with fewer than 10 nodes. Microsoft positions the Standard tier, which has its own per-cluster price, for production workloads that need an uptime SLA: 99.95% API server availability with availability zones, or 99.9% without.

Most teams want a staging environment next to production. With one cluster each, the fixed fees double: about $146 a month on EKS before any servers, for two clusters that may be mostly idle. That is not a large number for a funded company, but it is money spent before your product serves a single user, and it is the smaller of the two costs.

The cost nobody budgets for: keeping the cluster current

Kubernetes moves quickly. The project ships a new minor version about three times a year, maintains only the three most recent minor releases, and gives each one about a year of patch support. A cluster you set up today has to be upgraded at least once a year, and in practice more often, to keep receiving security fixes. On EKS, falling behind is also visible on the bill, because an old version moves to the $0.60 hourly rate.

Each upgrade is real work: reading the release notes, checking that your manifests and add-ons still use supported APIs, upgrading in staging first, then rolling production. Add the routine around it, from patching vulnerable images to watching dashboards and answering alerts, and a cluster becomes a recurring job, not a one-time setup.

The industry data points the same way. In the CNCF's 2025 survey, 82% of container users run Kubernetes in production, up from 66% in 2023. So Kubernetes is mainstream. The top challenge was "cultural changes with the development team" (47%); lack of training (36%), security (36%) and complexity (34%) ranked lower than in previous years. The obstacles are about people and practice more than installation.

What to use until you need it

Each large cloud has a container platform that runs your images without a cluster to manage:

• Google Cloud Run is "a fully managed application platform": "You don't have to create a cluster or manage infrastructure." When there are no requests, even the last instance is removed, and without minimum instances you're not charged while the service is unused. This website runs on Cloud Run; for a PHP app, the steps are in the guide to deploying a Laravel app on Cloud Run.
• AWS Fargate is "serverless compute for containers": you pay only for the compute resources used, and it works with Amazon ECS as well as EKS.
• Azure Container Apps is "a serverless platform for running containerized applications without managing the underlying infrastructure", with HTTPS ingress, scheduled jobs and traffic splitting between versions built in. Most applications can scale to zero; apps that scale on CPU or memory load can't.

If you do want Kubernetes but not the node work, there is a middle step. In GKE Autopilot, Google manages the nodes, scaling and security settings and starts upgrades automatically, while you still deploy with standard Kubernetes manifests. Azure recommends AKS Automatic as its production default.

Starting simple doesn't lock you in. All of these platforms run ordinary container images, so moving to a cluster later reuses the images you already build. What changes is the configuration around them: services, networking, secrets and the deploy pipeline.

A checklist: are you ready for Kubernetes?

Kubernetes is worth it when most of these are true:

• You run more than a handful of services that call each other, and keeping them deployed and in step by hand is causing incidents.
• You need something the managed platforms don't offer: custom networking between services, long-running background workers with special scheduling, or GPUs for models you host yourself.
• Your compute bill is large enough that packing workloads tightly onto your own nodes saves more than the fixed fees and the hours spent running the cluster.
• A customer contract or a compliance requirement asks for a specific setup you can only get with your own cluster.
• Someone, on your team or a partner you trust, owns upgrades, monitoring and security patches every month.

And you can safely wait if your product is one application and a database, your developers' time is better spent on features, or nobody would own the cluster after launch. If you're still shaping the first version, our guides on how to scope an MVP and what an MVP costs matter more than your orchestrator.

Frequently asked questions

Is Kubernetes free?

The software is open source, but a managed cluster isn't. EKS and GKE charge $0.10 per cluster per hour for the control plane (GKE's free tier credit covers one zonal or Autopilot cluster), and AKS has a free tier without an SLA, while its Standard tier for production has its own per-cluster price. Servers, storage and traffic are billed on top everywhere.

Can I move from Cloud Run or Container Apps to Kubernetes later?

Yes. They run standard container images, so the same images run on a cluster. The work is in rewriting the deployment configuration and setting up networking, secrets and monitoring on the cluster side.

How often does a Kubernetes cluster need upgrading?

Kubernetes releases a minor version about three times a year, and each gets about a year of patch support. Plan for at least one upgrade a year, usually more, to stay on a supported version.

Do I need Kubernetes to add AI features?

Not to call a hosted model through an API. It becomes relevant if you host models yourself: the CNCF survey found that 66% of organisations hosting generative AI models use Kubernetes for some or all of their inference.

Sources

1. Overview, Kubernetes documentation, 2026
2. Releases, Kubernetes, 2026
3. Kubernetes Release Cycle, Kubernetes, 2026
4. Amazon EKS pricing, Amazon Web Services, 2026
5. Google Kubernetes Engine pricing, Google Cloud, 2026
6. AKS Free, Standard, and Premium pricing tiers, Microsoft Learn, July 2026
7. Autopilot overview, Google Cloud, October 2026
8. What is Cloud Run, Google Cloud, October 2026
9. AWS Fargate, Amazon Web Services, 2026
10. Azure Container Apps overview, Microsoft Learn, July 2026
11. Kubernetes established as the de facto operating system for AI as production use hits 82% in 2025 CNCF Annual Cloud Native Survey, CNCF, January 2026