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6 hours ago
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Picture this: you’ve built a simple web application-maybe just a “Hello World” API that returns a JSON response. It’s literally 50 lines of code (oh, and and 45 of those are “code comments”. Look at you earning that gold star from your fellow reviewers!). You’re excited to deploy it and show the world your creation. Then you decide to do it “the right way” with Kubernetes because, hey, that’s what all the cool kids are doing these days. Plus…er…resume.
Three hours later, you’re staring at a monthly cloud bill that could fund a small startup, and your simple app is still not accessible from the internet. Welcome to the beautiful, complex, and ridiculously expensive world of Kubernetes.
The Kubernetes Tax: What You’re Really Paying For
Let’s be brutally honest about what happens when you decide to deploy that simple web app on Kubernetes. You’re not just running your application, you’re running an entire orchestration platform that was designed to manage thousands of containers across hundreds of machines.
Here’s what you actually need to get that simple “Hello World” app running on Kubernetes:
Control Plane Components (running 24/7 whether you have traffic or not):
· kube-apiserver: The front door to your cluster, handling all API requests
· etcd: A distributed database storing your entire cluster state
· kube-scheduler: Constantly figuring out where to place your workloads
· kube-controller-manager: Running multiple controllers to maintain desired state
· cloud-controller-manager: Integrating with your cloud provider’s services
Per-Node Components (running on every worker machine):
· kubelet: The agent that actually runs your containers
· kube-proxy: Managing network routing and load balancing
· Container runtime: Docker or containerd to actually run containers
Networking Layer:
· CNI plugin: Providing network connectivity between pods
· DNS: Service discovery within the cluster
· Ingress controller: Routing external traffic to your services
Additional Services:
· Load balancers: Exposing your services to the internet
· Persistent storage: Managing data that survives pod restarts
· Monitoring and logging: Because you need to know what’s happening
All of this infrastructure runs continuously, consuming resources and costing money, even when your simple app has zero users. It’s like keeping a Formula 1 pit crew on standby to change the tires on a bicycle.
The Cost of “Hello World”
Let me break down what it actually costs to run a simple web application on managed Kubernetes services:
AWS EKS: $160/month
· Control plane: $72/month ($0.10/hour)
· 2 worker nodes: $60/month (t3.medium instances)
· Load balancer: $18/month
· Basic storage: $10/month
Google GKE: $155/month
· Control plane: $72/month (after free tier exhausted)
· 2 worker nodes: $55/month
· Load balancer: $18/month
· Storage: $10/month
Azure AKS: $160/month
· Control plane: $72/month (Standard tier)
· 2 worker nodes: $60/month
· Load balancer: $18/month
· Storage: $10/month
That’s right-your “Hello World” application is costing you $150+ per month before you serve a single user. And here’s the kicker: studies show that up to 80% of CPU resources in Kubernetes environments remain idle.
A Simple App Deployment Reveals the Absurdity
Let’s look at what a basic deployment actually requires. Here’s the YAML for a simple web application:
apiVersion: apps/v1kind: Deployment
metadata:
name: hello-world-app
spec:
replicas: 2
selector:
matchLabels:
app: hello-world
template:
metadata:
labels:
app: hello-world
spec:
containers:
- name: hello-world
image: nginx:alpine
resources:
requests:
memory: "64Mi"
cpu: "100m"
limits:
memory: "128Mi"
cpu: "200m"
ports:
- containerPort: 80
- -
apiVersion: v1
kind: Service
metadata:
name: hello-world-service
spec:
selector:
app: hello-world
ports:
- port: 80
targetPort: 80
type: LoadBalancer
This simple configuration creates a deployment that requests a mere 200 millicores of CPU and 128MB of memory per pod. Yet to run this in a production-ready Kubernetes cluster, you need all the infrastructure components I mentioned earlier, running 24/7, consuming gigabytes of memory and multiple CPU cores just for the platform itself.
The minimum system requirements tell the story:
· Control plane: 2GB RAM, 2 CPU cores minimum
· Worker nodes: 2GB RAM, 2 CPU cores each
· etcd: Additional dedicated storage and compute resources
· Networking: CNI plugins, DNS, ingress controllers
Your tiny app might need 100 millicores, but the platform running it needs several full CPU cores just to exist.
The k8s nail requires a Rackspace Spot hammer
I’d be mistaken to assume that k8s will change its ways at this point. It is (rightfully) built for scale, so the problem of how to manage costs before the scale shows up is always going to be left to the user. I stumbled upon something that fixed it trivially: Rackspace Spot.
On the surface, Rackspace Spot offers a well-known open market auction model for cloud servers, delivered as fully managed Kubernetes clusters. Instead of paying fixed hyperscaler prices, you bid on compute capacity, and market forces determine the actual cost.
Here’s what makes it different :
Insanely low prices: Current market prices start as low as $0.001/hour per server. That’s not a typo. One-tenth of a cent per hour!
Free Control Plane: Unlike the major cloud providers that charge $72/month just for the control plane, Rackspace Spot includes it for free. Your cluster management overhead drops to zero.
Turnkey Managed Clusters: You’re not just getting raw compute-you get fully configured Kubernetes clusters with all the bells and whistles included out of the box.
Let’s run the numbers for that same simple app:
Rackspace Spot: $37.88/month
· Control plane: $0 (free)
· 2 worker nodes: $17.28/month (based on current market rates)
· 2 load balancers: $20/month
· Storage: $0.60/month (5GB)
That’s a 76% savings compared to AWS EKS. Suddenly, Kubernetes doesn’t feel like financial suicide anymore.
The Bigger Picture: Why This Matters
The traditional cloud pricing model for Kubernetes has created a barrier to entry that pushes smaller teams and startups away from modern container orchestration. When your infrastructure costs more than your engineering team’s coffee budget, something is fundamentally broken. Managed Kubernetes services have become 3x the cost of running equivalent VMs, and that’s before you factor in the hidden costs like data egress, storage operations, and the army of specialized engineers you need to keep everything running.
Rackspace Spot changes this equation entirely. By eliminating the control plane costs and using market-based pricing for compute, it makes Kubernetes accessible to teams that previously couldn’t justify the expense. You can finally use the orchestration platform that the industry considers best practice without mortgaging your future.
What’s Coming Next
In the upcoming posts in this series, I’ll dive deep into practical examples of migrating real applications to Rackspace Spot. I hope to cover:
· Migrating a Node.js API: Step-by-step guide from traditional cloud to Spot
· Running data services on Spot: PostgreSQL, Redis, ES, and persistent storage strategies
· CI/CD pipelines: How to integrate Spot clusters into your deployment workflow
· Scaling strategies: Making the most of Spot pricing for variable workloads
· Monitoring and observability: Keeping track of costs and performance
The cloud pricing model is broken, but solutions like Rackspace Spot prove that it doesn’t have to stay that way. Sometimes the best way to love Kubernetes is to stop paying hyperscaler prices and start paying microscaler prices.
Stay tuned for the next post where I’ll walk through migrating some real applications to Rackspace Spot, complete with cost breakdowns and performance comparisons.
