here’s a popular belief in tech circles today:
If you’re not running Kubernetes, you’re falling behind.
It sounds convincing. Kubernetes is everywhere — conference talks, blog posts, job descriptions. It has become the shorthand for “modern infrastructure.”
But here’s the myth:
Kubernetes is required for modern infrastructure.
The truth is simpler: for many workloads, you don’t need Kubernetes at all. Managed services and simpler PaaS offerings are often cheaper, faster, and less stressful.
The Startup That Lost Six Months
A friend once told me about his startup’s early days. They had a small SaaS product — nothing too fancy, just a web app with a database and some background jobs.
The founders decided they wanted to “do it right” from the start. They spun up a Kubernetes cluster, spent weeks learning YAML, configured an ingress controller, set up monitoring, wrestled with RBAC, and automated upgrades.
It took six months before they had a stable setup. Six months of engineering effort before customers could reliably use the product.
The irony? Their workload could have run on a single managed service like Cloud Run or App Engine in less than a week. No nodes, no clusters, no patching — just focus on code and customers.
Eventually, they scrapped the cluster and migrated to Cloud Run. Their cloud bill dropped, uptime improved, and their developers finally got back to shipping features instead of debugging Kubernetes.
Why Kubernetes Feels Like a Requirement
Kubernetes became the standard because it solved real problems at scale:
- Orchestrating thousands of containers across fleets of servers.
- Providing consistent abstractions for deployment, scaling, and failover.
- Enabling multi-cloud and hybrid strategies.
If you’re Netflix, Shopify, or a global enterprise with complex systems and hundreds of engineers, Kubernetes is a lifesaver. It standardizes chaos.
That’s why it feels like the default answer for everyone.
When Kubernetes Is Overkill
But most teams aren’t Netflix. Many workloads don’t justify the operational overhead of Kubernetes. Consider these scenarios:
- A small SaaS app. Running on Google Cloud Run, AWS App Runner, or Heroku might cover 100% of your needs with a fraction of the complexity.
- Internal tools. If only a few dozen people will ever use it, spinning up a managed service (Cloud Run, App Engine, Azure Web Apps) is faster and often cheaper than running a full cluster.
- Data processing jobs. Cloud-native services like AWS Lambda, GCP Cloud Functions, or managed Spark remove the need for cluster administration.
- Steady-state services. If your workload rarely changes, a simple VM with auto-healing and a managed database might be all you need.
In these cases, Kubernetes introduces unnecessary moving parts: YAML, networking policies, ingress controllers, monitoring stacks, and constant cluster upgrades. That’s not modernization — that’s overhead.
The Illusion of “Modern”
Kubernetes often gets equated with “modern,” but modernization isn’t about tools. It’s about outcomes: reliability, speed, security, and scalability.
If you can achieve those outcomes faster with a managed service, then that’s the modern choice for you.
A single Cloud Run deployment that scales to zero might be far more “modern” than a half-baked Kubernetes setup that burns engineering cycles just to stay alive.
Myth vs Reality
- Myth: Every serious team needs Kubernetes.
- Reality: Many teams benefit more from managed PaaS offerings, which free developers to focus on business logic instead of infrastructure plumbing.
Kubernetes is powerful, but it is not a universal requirement. It’s one option on a broad spectrum of modern infrastructure.
Part of the “Infrastructure Myths” Series
This post continues our series busting oversimplified infrastructure truths:
- Terraform is Always Better Than ClickOps
- More Microservices ≠ More Scalability
- Containers Solve All Deployment Problems
- Serverless Is Always Cheaper
- And now: Kubernetes Is Required for Modern Infrastructure
Because “modern” isn’t about copying Silicon Valley — it’s about making the right trade-offs for your workload.
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