Deploying workloads on EKS in AWS - Time & Space Complexity

Time Complexity: Deploying workloads on EKS

O(n)

Understanding Time Complexity

When deploying workloads on EKS, it is important to understand how the time to deploy grows as you add more workloads.

We want to know how the number of deployments affects the total time and operations needed.

Scenario Under Consideration

Analyze the time complexity of the following operation sequence.

aws eks create-cluster --name my-cluster --role-arn role-arn --resources-vpc-config subnetIds=subnet-123,subnet-456
aws eks create-nodegroup --cluster-name my-cluster --nodegroup-name nodegroup1 --subnets subnet-123 subnet-456 --instance-types t3.medium
aws eks update-kubeconfig --name my-cluster
kubectl apply -f workload1.yaml
kubectl apply -f workload2.yaml
kubectl apply -f workloadN.yaml
    

This sequence creates an EKS cluster, adds a node group, configures access, and deploys multiple workloads.

Identify Repeating Operations

Identify the API calls, resource provisioning, data transfers that repeat.

• Primary operation: Applying each workload manifest with kubectl apply.
• How many times: Once per workload, so it repeats for each workload deployed.

How Execution Grows With Input

Each workload requires a separate apply operation, so as you add more workloads, the number of operations grows directly with the number of workloads.

Input Size (n)	Approx. Api Calls/Operations
10	10 apply operations
100	100 apply operations
1000	1000 apply operations

Pattern observation: The total operations increase in a straight line as workloads increase.

Final Time Complexity

Time Complexity: O(n)

This means the time to deploy grows directly in proportion to the number of workloads you deploy.

Common Mistake

[X] Wrong: "Deploying multiple workloads happens all at once, so time stays the same no matter how many workloads."

[OK] Correct: Each workload requires its own deployment step, so more workloads mean more steps and more time.

Interview Connect

Understanding how deployment time grows with workload count helps you plan and explain scaling in cloud environments confidently.

Self-Check

"What if we deployed all workloads using a single combined manifest file? How would the time complexity change?"

Practice

1. What is the main purpose of Amazon EKS when deploying workloads?

easy

A. To run containerized applications using Kubernetes without managing servers

B. To store large amounts of data in the cloud

C. To create virtual machines for running applications

D. To manage user access and permissions

Solution

1. Step 1: Understand EKS functionality

   Amazon EKS is a managed Kubernetes service that lets you run containers without managing the underlying servers.

2. Step 2: Compare options

   Storing data relates to services like S3, creating VMs to EC2, and managing permissions to IAM--none of which is EKS's core purpose.

3. Final Answer:

   To run containerized applications using Kubernetes without managing servers -> Option A

4. Quick Check:

   EKS = Managed Kubernetes for containers [OK]

Hint: EKS = Kubernetes service for containers, not storage or VMs [OK]

Common Mistakes:

• Confusing EKS with storage services like S3
• Thinking EKS manages virtual machines directly
• Mixing EKS with IAM user management

2. Which of the following is the correct command to deploy an application using a YAML file named app-deployment.yaml on EKS?

easy

A. kubectl run app-deployment.yaml

B. eksctl create app app-deployment.yaml

C. aws eks deploy app-deployment.yaml

D. kubectl apply -f app-deployment.yaml

Solution

1. Step 1: Identify the kubectl command for applying YAML

   The correct command to deploy resources defined in a YAML file is kubectl apply -f filename.

2. Step 2: Evaluate other options

   kubectl run app-deployment.yaml is for running individual pods, not applying YAML manifests. eksctl create app app-deployment.yaml misuses eksctl, which is primarily for EKS cluster creation. aws eks deploy app-deployment.yaml is not a valid AWS CLI command.

3. Final Answer:

   kubectl apply -f app-deployment.yaml -> Option D

4. Quick Check:

   Deploy YAML with kubectl apply -f [OK]

Hint: Use kubectl apply -f for YAML deployment files [OK]

Common Mistakes:

• Using eksctl for direct YAML deployment
• Confusing kubectl run with apply
• Trying AWS CLI commands that don't exist

3. Given this YAML snippet for a Deployment on EKS:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: myapp
spec:
  replicas: 3
  selector:
    matchLabels:
      app: myapp
  template:
    metadata:
      labels:
        app: myapp
    spec:
      containers:
      - name: myapp-container
        image: nginx:latest

What will be the number of running pods after applying this deployment?

medium

A. 1

B. 3

C. 0

D. Depends on the node capacity

Solution

1. Step 1: Read the replicas field in the Deployment spec

   The YAML specifies replicas: 3, which means Kubernetes will create 3 pods for this deployment.

2. Step 2: Understand pod creation behavior

   Unless there is a scheduling issue, Kubernetes will run 3 pods as requested.

3. Final Answer:

   3 -> Option B

4. Quick Check:

   replicas = number of pods running [OK]

Hint: replicas field sets pod count in Deployment spec [OK]

Common Mistakes:

• Assuming only 1 pod runs by default
• Thinking pods depend on node capacity without error
• Confusing selector labels with pod count

4. You tried to deploy a workload on EKS using kubectl apply -f deployment.yaml, but got an error: error: unable to recognize "deployment.yaml": no matches for kind "Deploy". What is the likely cause?

medium

A. The cluster is not running

B. kubectl is not installed

C. The YAML file has a typo in the kind field; it should be 'Deployment' not 'Deploy'

D. The image name in the YAML is incorrect

Solution

1. Step 1: Analyze the error message

   The error says no matches for kind "Deploy", which means Kubernetes does not recognize this resource kind.

2. Step 2: Check the YAML kind field

   The correct kind for workload deployment is "Deployment", not "Deploy". This typo causes the error.

3. Final Answer:

   The YAML file has a typo in the kind field; it should be 'Deployment' not 'Deploy' -> Option C

4. Quick Check:

   Kind field must be exact Kubernetes resource name [OK]

Hint: Check resource kind spelling in YAML for errors [OK]

Common Mistakes:

• Ignoring error details about resource kind
• Assuming cluster or kubectl issues without checking YAML
• Blaming image name for syntax errors

5. You want to deploy a stateless web app on EKS that automatically scales between 2 and 5 pods based on CPU usage. Which combination of Kubernetes resources should you define in your YAML files?

hard

A. A Deployment with replicas set to 2 and a Horizontal Pod Autoscaler targeting CPU usage with max replicas 5

B. A StatefulSet with replicas 5 and a LoadBalancer service

C. A DaemonSet to run pods on every node and a Cluster Autoscaler

D. A Deployment with replicas fixed at 5 and a NodePort service

Solution

1. Step 1: Identify resource for managing pod replicas with scaling

   A Deployment manages stateless pods and can be combined with a Horizontal Pod Autoscaler (HPA) to scale pods based on CPU.

2. Step 2: Understand autoscaling setup

   Set Deployment replicas to minimum 2, and HPA to scale up to max 5 pods based on CPU usage.

3. Step 3: Evaluate other options

   StatefulSet is for stateful apps, DaemonSet runs pods on all nodes (not scaling pods), fixed replicas do not autoscale.

4. Final Answer:

   A Deployment with replicas set to 2 and a Horizontal Pod Autoscaler targeting CPU usage with max replicas 5 -> Option A

5. Quick Check:

   Deployment + HPA = autoscaling pods [OK]

Hint: Use Deployment + HPA for CPU-based pod autoscaling [OK]

Common Mistakes:

• Using StatefulSet for stateless apps
• Confusing DaemonSet with autoscaling pods
• Setting fixed replicas without autoscaler