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Microservicessystem_design~12 mins

Why Kubernetes manages microservice deployment in Microservices - Architecture Impact

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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
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  v
Worker Nodes (Pods running microservices)
  |
  v
Container Runtime -> Microservice Containers
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  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
UserLoad Balancer
Load BalancerWorker Nodes
UserKubernetes API Server
Kubernetes API ServerScheduler
SchedulerWorker Nodes
Controller ManagerWorker Nodes
Worker NodesContainer 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
Test your understanding
Which component assigns microservice pods to worker nodes?
AScheduler
BLoad Balancer
CController Manager
DAPI 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.