Control plane components (API server, scheduler, controller manager, etcd) in Kubernetes - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Role of the Kubernetes API Server

Which statement best describes the primary role of the Kubernetes API server in the control plane?

A It stores all cluster data and state persistently.

B It schedules pods onto nodes based on resource availability.

C It acts as the central management point that exposes the Kubernetes API and processes REST requests.

D It manages the lifecycle of pods and nodes by running controllers.

💡 Hint

Think about which component handles communication and API requests in Kubernetes.

The API server is the central hub that exposes the Kubernetes API and processes REST requests from users and components.

💻 Command Output

intermediate

Output of etcdctl get Command

What is the expected output of the following command if the key 'config/version' exists with value 'v1.20.0' in etcd? etcdctl get config/version

Kubernetes

etcdctl get config/version

A config/version

B

config/version
v1.20.0

C Error: key not found

D v1.20.0

💡 Hint

Remember etcdctl outputs the key and value by default.

By default, etcdctl get outputs the key on one line and the value on the next line.

🔀 Workflow

advanced

Order of Control Plane Components Processing a Pod Creation

Arrange the order in which the Kubernetes control plane components process a pod creation request.

A 1,2,4,3

B 1,2,3,4

C 1,3,2,4

D 1,4,2,3

💡 Hint

Think about when the state is saved and when scheduling happens.

The API server first receives the request and stores it in etcd. Then the scheduler assigns the pod to a node, and finally the controller manager manages the pod lifecycle.

❓ Troubleshoot

advanced

Identifying the Cause of Pod Scheduling Failure

A pod remains in Pending state indefinitely. Which control plane component is most likely responsible for this issue?

A Scheduler is not running or unable to assign the pod to a node.

B API Server is down, so pod creation requests are not processed.

C Controller Manager failed to create the pod on the node.

D etcd has lost cluster state data for the pod.

💡 Hint

Consider which component decides where pods run.

The scheduler assigns pods to nodes. If it is down or stuck, pods remain Pending.

✅ Best Practice

expert

Ensuring High Availability of etcd in Kubernetes

What is the best practice to ensure high availability and data consistency of etcd in a Kubernetes cluster?

A Deploy an odd number of etcd instances in a cluster with quorum-based consensus.

B Run a single etcd instance on the master node with frequent backups.

C Use multiple etcd instances but allow them to run independently without synchronization.

D Store etcd data on local disks of worker nodes for faster access.

💡 Hint

Think about how distributed systems maintain consistency and availability.

Running an odd number of etcd instances in a cluster ensures quorum-based consensus, providing high availability and consistency.

Practice

1. Which component of the Kubernetes control plane acts as the main entry point for all REST commands and handles communication with the cluster?

easy

A. etcd

B. Scheduler

C. API server

D. Controller manager

Solution

1. Step 1: Understand the role of the API server

   The API server is the front door of the Kubernetes control plane. It receives REST requests and processes them.

2. Step 2: Compare with other components

   The scheduler assigns pods to nodes, the controller manager runs controllers, and etcd stores cluster data. None handle REST communication directly.

3. Final Answer:

   API server -> Option C

4. Quick Check:

   API server = main REST entry point [OK]

Hint: API server handles all REST requests to the cluster [OK]

Common Mistakes:

• Confusing scheduler with API server
• Thinking controller manager handles REST calls
• Assuming etcd processes API requests

2. Which of the following is the correct command to check the status of the Kubernetes scheduler component?

easy

A. kubectl get pods -n kube-system | grep scheduler

B. kubectl get nodes --show-scheduler

C. kubectl describe scheduler

D. kubectl get scheduler-status

Solution

1. Step 1: Identify how to check scheduler status

   The scheduler runs as a pod in the kube-system namespace, so checking pods there helps find it.

2. Step 2: Analyze each command

   kubectl get pods -n kube-system | grep scheduler lists pods in kube-system and filters for scheduler, which is correct. The other commands are invalid kubectl commands or do not exist.

3. Final Answer:

   kubectl get pods -n kube-system | grep scheduler -> Option A

4. Quick Check:

   Scheduler runs as pod, check pods in kube-system [OK]

Hint: Scheduler runs as pod; check pods in kube-system namespace [OK]

Common Mistakes:

• Using invalid kubectl commands
• Trying to describe scheduler directly
• Assuming scheduler is a node property

3. Given the following scenario: The Kubernetes scheduler fails to assign pods to nodes. Which control plane component is most likely responsible for detecting and fixing this issue automatically?

medium

A. API server

B. kubelet

C. etcd

D. Controller manager

Solution

1. Step 1: Understand the roles of components

   The controller manager runs controllers that watch cluster state and fix issues like unscheduled pods.

2. Step 2: Identify responsible component for fixing scheduling issues

   When scheduler fails, controller manager detects pods not assigned and may trigger rescheduling or alerts. API server only handles requests, etcd stores data, kubelet runs on nodes.

3. Final Answer:

   Controller manager -> Option D

4. Quick Check:

   Controller manager fixes cluster state issues [OK]

Hint: Controller manager fixes cluster state problems automatically [OK]

Common Mistakes:

• Confusing API server with controller manager
• Thinking etcd fixes issues
• Assuming kubelet manages scheduling

4. You notice that the etcd cluster is not storing new data correctly. Which of the following is the most likely cause and fix?

medium

A. etcd disk is full; free up disk space or increase storage

B. Scheduler is overloaded; scale scheduler pods

C. API server is down; restart the API server pods

D. Controller manager crashed; restart controller manager

Solution

1. Step 1: Identify symptoms related to etcd

   etcd stores cluster data. If it fails to store new data, disk space or storage issues are common causes.

2. Step 2: Match cause and fix

   API server, scheduler, and controller manager issues do not directly cause etcd storage failure. Disk full on etcd node is the likely cause; freeing space or increasing storage fixes it.

3. Final Answer:

   etcd disk is full; free up disk space or increase storage -> Option A

4. Quick Check:

   etcd storage issues = disk full fix [OK]

Hint: etcd storage issues often mean disk full; check storage first [OK]

Common Mistakes:

• Restarting unrelated components
• Ignoring disk space on etcd nodes
• Assuming scheduler affects etcd storage

5. You want to ensure high availability of the Kubernetes control plane. Which combination of components should you deploy in multiple replicas to avoid a single point of failure?

hard

A. Multiple schedulers and controller managers only

B. Multiple API servers and etcd nodes

C. Multiple etcd nodes only

D. Multiple API servers only

Solution

1. Step 1: Understand high availability needs

   High availability means no single point of failure. Both API servers and etcd store critical data and handle requests.

2. Step 2: Identify components to replicate

   API servers can run multiple replicas behind a load balancer. etcd must run as a cluster with multiple nodes for data safety. Scheduler and controller manager can be run as leader election but are less critical to replicate for HA.

3. Final Answer:

   Multiple API servers and etcd nodes -> Option B

4. Quick Check:

   HA = replicate API servers + etcd nodes [OK]

Hint: Replicate API servers and etcd for control plane high availability [OK]

Common Mistakes:

• Replicating only schedulers or controller managers
• Ignoring etcd clustering
• Assuming API server alone is enough