Why Kubernetes manages microservice deployment in Microservices - Architecture Impact

System Overview - Why Kubernetes manages microservice deployment

This system explains why Kubernetes is used to manage microservice deployments. Kubernetes helps automate deployment, scaling, and management of microservices, ensuring they run reliably and efficiently across many servers.

Architecture Diagram

User
  |
  v
Load Balancer
  |
  v
Kubernetes API Server
  |
  v
Scheduler -> Controller Manager
  |
  v
Worker Nodes (Pods running microservices)
  |
  v
Container Runtime -> Microservice Containers
  |
  v
Persistent Storage / Config Maps / Secrets

Components

User

client

Sends requests to microservices

Load Balancer

load_balancer

Distributes incoming requests to Kubernetes API Server or services

Kubernetes API Server

api_gateway

Receives deployment commands and manages cluster state

Scheduler

scheduler

Assigns microservice pods to worker nodes based on resource availability

Controller Manager

controller

Ensures desired state of microservices is maintained (e.g., number of replicas)

Worker Nodes

compute_node

Run microservice containers inside pods

Container Runtime

runtime

Runs and manages container lifecycle on worker nodes

Persistent Storage / Config Maps / Secrets

storage

Stores data, configuration, and sensitive information for microservices

Request Flow - 7 Hops

User → Load Balancer

Load Balancer → Worker Nodes

User → Kubernetes API Server

Kubernetes API Server → Scheduler

Scheduler → Worker Nodes

Controller Manager → Worker Nodes

Worker Nodes → Container Runtime

Failure Scenario

Component Fails:Worker Nodes

Impact:Microservice pods on failed nodes become unavailable, causing service disruption

Mitigation:Kubernetes reschedules pods to healthy nodes automatically to restore service

Architecture Quiz - 3 Questions

Which component assigns microservice pods to worker nodes?

A Scheduler

B Load Balancer

C Controller Manager

D API Server

Design Principle

Kubernetes manages microservice deployment by automating pod scheduling, scaling, and health monitoring. This ensures microservices run reliably across many nodes, improving availability and simplifying operations.

Practice

1. Why does Kubernetes manage microservice deployment instead of manually running each service?

easy

A. Because it replaces the need for any servers

B. Because it automates starting, stopping, and scaling services reliably

C. Because it writes the code for microservices automatically

D. Because it only works with one service at a time

Solution

1. Step 1: Understand manual deployment challenges

   Manually running many microservices is hard to keep track of and scale.

2. Step 2: Role of Kubernetes in deployment

   Kubernetes automates managing service lifecycles, scaling, and recovery to keep apps running smoothly.

3. Final Answer:

   Because it automates starting, stopping, and scaling services reliably -> Option B

4. Quick Check:

   Automation of service management = B [OK]

Hint: Kubernetes automates service control, not replaces servers or code [OK]

Common Mistakes:

• Thinking Kubernetes replaces servers
• Believing Kubernetes writes app code
• Assuming Kubernetes handles only one service

2. Which of the following is the correct Kubernetes command to deploy a microservice from a YAML file named service.yaml?

easy

A. kubectl apply -f service.yaml

B. kubectl run service.yaml

C. kubectl start service.yaml

D. kubectl create service.yaml

Solution

1. Step 1: Identify the command to apply configuration files

   The kubectl apply -f command applies changes from a YAML file to the cluster.

2. Step 2: Check other options for correctness

   kubectl run is for running pods directly, kubectl start and kubectl create do not accept YAML files directly.

3. Final Answer:

   kubectl apply -f service.yaml -> Option A

4. Quick Check:

   Apply YAML file = kubectl apply -f [OK]

Hint: Use 'kubectl apply -f' to deploy YAML files [OK]

Common Mistakes:

• Using 'kubectl run' to deploy YAML files
• Trying 'kubectl start' which is invalid
• Confusing 'kubectl create' with applying configs

3. Given this Kubernetes YAML snippet for a microservice pod:

apiVersion: v1
kind: Pod
metadata:
  name: myservice
spec:
  containers:
  - name: app
    image: myapp:v1
    ports:
    - containerPort: 80

What will happen if the pod crashes unexpectedly?

medium

A. The pod will restart only if the image is updated

B. The pod will stay crashed until manually restarted

C. Kubernetes will automatically restart the pod to keep the service running

D. Kubernetes will delete the pod and not recreate it

Solution

1. Step 1: Understand pod restart policy default

   By default, Kubernetes restarts pods automatically if they crash to maintain service availability.

2. Step 2: Check other options for correctness

   Pods do not stay crashed without restart, nor are they deleted permanently without recreation, and restarts are not tied to image updates.

3. Final Answer:

   Kubernetes will automatically restart the pod to keep the service running -> Option C

4. Quick Check:

   Pod auto-restart on crash = D [OK]

Hint: Pods auto-restart by default to keep services alive [OK]

Common Mistakes:

• Thinking pods stay crashed until manual restart
• Believing pods delete permanently on crash
• Assuming restart depends on image updates

4. You deployed a microservice with Kubernetes, but it keeps crashing. The YAML file has this snippet:

spec:
  containers:
  - name: app
    image: myapp:v1
    ports:
    - containerPort: 80
  restartPolicy: Never

What is the problem and how to fix it?

medium

A. The pod name is missing; add metadata name

B. The containerPort is wrong; change it to 8080

C. The image version is invalid; update to 'v2'

D. The restartPolicy 'Never' stops restarts; change it to 'Always' to fix

Solution

1. Step 1: Identify restartPolicy effect

   Setting restartPolicy: Never means Kubernetes will not restart the pod if it crashes.

2. Step 2: Fix by changing restartPolicy

   Changing restartPolicy to Always lets Kubernetes restart the pod automatically to keep it running.

3. Final Answer:

   The restartPolicy 'Never' stops restarts; change it to 'Always' to fix -> Option D

4. Quick Check:

   restartPolicy 'Always' enables auto-restart [OK]

Hint: Use restartPolicy 'Always' to auto-restart pods [OK]

Common Mistakes:

• Changing port without checking crash cause
• Updating image version without error info
• Ignoring restartPolicy effect

5. You want to deploy a microservice that must always be available, even if some pods fail. Which Kubernetes feature helps achieve this and how?

hard

A. Use a Deployment with replicas to run multiple pod copies for high availability

B. Use a single Pod with restartPolicy set to Never

C. Use a ConfigMap to store pod data for recovery

D. Use a ServiceAccount to control pod permissions

Solution

1. Step 1: Understand high availability needs

   Running multiple copies of a microservice ensures it stays available if some pods fail.

2. Step 2: Use Kubernetes Deployment with replicas

   A Deployment manages multiple pod replicas and automatically replaces failed pods to maintain availability.

3. Final Answer:

   Use a Deployment with replicas to run multiple pod copies for high availability -> Option A

4. Quick Check:

   Deployment + replicas = high availability [OK]

Hint: Deploy replicas with Deployment for service uptime [OK]

Common Mistakes:

• Using single pod with no replicas
• Confusing ConfigMap with availability
• Mixing permissions with availability