Kubernetes Online Test
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About the test
The Kubernetes online test assesses knowledge of automating application deployment, scaling, and management using Kubernetes.
The assessment includes work-sample tasks such as:
- Using Ingress to manage external access to services.
- Creating and managing Pods.
- Configuring load balancing to improve scalability.
A good engineer working with Kubernetes should know how to manage containers with Kubernetes in order to orchestrate automated deployment and scaling.
Sample public questions
A Kubernetes cluster runs a client-app Deployment exposed externally by a LoadBalancer Service app-service at https://app.example.com/. A new backend Deployment with internal Service backend-service is added.
The expected routing based on selectors:
- / - client-app
- /api - backend
The platform team enforces a single public load balancer/IP per environment.
Services currently defined:
apiVersion: v1
kind: Service
metadata:
name: app-service
spec:
type: LoadBalancer
ports:
- name: https
port: 443
targetPort: 8443
selector:
app: client-appapiVersion: v1
kind: Service
metadata:
name: backend-service
spec:
type: ClusterIP
ports:
- name: http
port: 80
targetPort: 8080
selector:
app: backendAnswer the following:
- Can app-service be updated to expose both apps?
- What is the solution to route traffic correctly?
(An answer up to 30 words is sufficient)
Consider the following Ingress resource:
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
name: main-ingress
spec:
rules:
- http:
paths:
- path: /
pathType: Prefix
backend:
service:
name: main-app
port:
number: 80
- path: /files/
pathType: Prefix
backend:
service:
name: file-app
port:
number: 80
- path: /files/default.png
pathType: Exact
backend:
service:
name: default-app
port:
number: 8080Select all the true statements.
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8 more premium Kubernetes questions
Container Switch, Ingress Controller, Obsolete Pods, Tomcat Host, GPU Node, Larger Images, High Memory Job, Metrics Collection Agent.
Skills and topics tested
- Kubernetes
- Ingress
- Load Balancing
- Services
- Command Line Arguments
- Pods
- Server Clustering
- Job
- Taints and Tolerations
- Deployment
- Storage Systems
- Memory Management
- DaemonSet
For job roles
- DevOps Engineer
- System Administrator (Sysadmin)
Sample candidate report
AI-driven cheating detection
Protect against bad hires with automated highlighting of possible cheating attempts. Spend less time reviewing proctoring details and identify cheating in seconds.
What others say
Reliable, AI-ready technical testing
I thought the rise of AI would render it obsolete, BUT, the platform has definitely adapted to the changing times and I find it to be the only reliable way to do our online technical assessments nowadays. With its system proctoring and AI-detection tools, I feel confident that the applicants aren't able to cheat.
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