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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Application Observability and Maintenance | 15% | - Understand API deprecation policies - Use built-in CLI tools to monitor Kubernetes applications - Utilize container logs - Debugging in Kubernetes - Implement probes and health checks |
| Topic 2: Application Environment, Configuration and Security | 25% | - Understand authentication, authorization and admission control - ConfigMaps and Secrets - Understanding and defining resource requirements, limits and quotas - Discover and use resources that extend Kubernetes (CRD, Operators) - ServiceAccounts - SecurityContexts |
| Topic 3: Application Design and Build | 20% | - Understand multi-container Pod design patterns (e.g., sidecar, init and others) - Define, build and modify container images - Choose and use the right workload resource (Deployment, DaemonSet, CronJob, etc.) - Utilize persistent and ephemeral volumes |
| Topic 4: Services and Networking | 20% | - Demonstrate basic understanding of NetworkPolicies - Provide and troubleshoot access to applications via services - Use Ingress rules to expose applications |
| Topic 5: Application Deployment | 20% | - Kustomize - Use the Helm package manager to deploy existing packages - Use Kubernetes primitives to implement common deployment strategies (e.g., blue/green or canary) - Understand Deployments and how to perform rolling updates |
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NEW QUESTION # 180
You are building a microservice that relies on a third-party API for its functionality_ To ensure the reliability and performance of your microservice, you need to implement a robust strategy tor handling API calls. Design a deployment strategy that addresses potential issues with the third-pany API and ensures the stability of your microservice.
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
I). Use a Deployment:
- Deploy your microservice using a Deployment. Deployments provide a robust mechanism for managing and scaling your microservices, making it easy to update and manage your application.
2. Secure API Credentials: - Store API credentials (like API keys or tokens) securely using a Kubernetes Secret. This prevents credentials from being exposed in plain text within your deployments.
3. Implement Retry Mechanisms: - Add retry logic to your code to handle transient errors (like network hiccups or temporary service outages) during API calls. This helps ensure that your microservice can recover from temporary issues and continue functioning. 4. Utilize Rate Limiting: - Implement rate limiting to prevent your microservice from ovenvhelming the third-party API. This helps protect both your microservice and the API from performance degradation- 5. Use a Circuit Breaker Pattern: - Integrate a circuit breaker pattern into your API call handling. This pattern helps prevent cascading failures by automatically stopping requests to the third-party API it it is experiencing prolonged outages or errors- 6. Consider a Proxy or Gateway: - Implement a proxy or gateway layer between your microservice and the third-party API. This layer can help with request routing, load balancing, security, and performance optimization. 7. Monitor API Calls: - Implement monitoring and logging to track API call performance and identify potential issues. This allows you to proactively identify and address problems before they impact your microservice's reliability 8. Utilize Caching: - Consider caching API responses to reduce the load on the third-party API and improve the response time of your microservice. 9. Implement Fallbacks: - Have fallback mechanisms in place if the third-party API is unavailable. This could involve returning default data or using alternative data sources to provide a degraded but functional experience. 10. Consider Using a Service Mesh: - For complex microservice architectures, consider implementing a service mesh like Istio. Service meshes provide features like traffic management, security, observability, and resilience, which can be very beneficial for managing interactions with third-party APIs.,
NEW QUESTION # 181
You are running a Deployment for a database service with 3 replicas. You want to ensure that only one pod is updated at a time, but you need to guarantee that the database service remains available throughout tne update process. How would you configure the Deployment to achieve this?
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Update the Deployment YAMLI
- Update the 'replicas' to 3.
- Define 'maxiJnavailable: 1 ' and 'maxSurge: O' in the 'strategy-rollingupdate' section to control the rolling update process.
- Use a 'readiness probe' within your container definition to ensure that the pod is considered ready only when tne database is successfully started and connected.
- Configure a 'strategy-type' to 'RollingUpdate' to trigger a rolling update when the deployment is updated.
2. Create the Deployment: - Apply the updated YAML file using 'kubectl apply -f database-deployment-yamp 3. Verify the Deployment - Check the status of the deployment using 'kubectl get deployments database-deployment to confirm the rollout and updated replica count. 4. Trigger the Automatic Update: - Pusn a new image to the Docker Hub repository. 5. Monitor the Deployment - Use 'kubectl get pods -l to monitor the pod updates during the rolling update process. You will observe that only one pod is terminated at a time. The readiness probe will ensure that a new pod is only considered ready when it's successfully connected to the database. 6. Check for Successful Update: - Once the deployment is complete, use 'kubectl describe deployment database-deployment to see that the 'updatedReplicas' field matches the 'replicas' field, indicating a successful update.,
NEW QUESTION # 182 
Task
A Deployment named backend-deployment in namespace staging runs a web application on port 8081.
Answer:
Explanation:
See the solution below.
Explanation:
Solution:
NEW QUESTION # 183
You have a Kubernetes deployment named 'wordpress-deployment' running multiple instances of a WordPress application. You want to implement a rolling update strategy with a 'maxSurge' of 1 and 'maxi-Jnavailable' of O. Additionally, you need to ensure that the update process is automatically triggered when a new image is pushed to the Docker Hub repository 'wordpress-image:latests. Implement a Kustomization file to achieve this.
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Create a 'kustomization.yamr file in your desired directory.
2. Create a 'deployment-yamr file (or use an existing one) with the following structure.
3. Create a 'patch.yamr file with the following content to configure rolling update and automatic updates:
4. Apply the Kustomization: bash kubectl apply -k - The 'kustomization.yaml file defines the resources (the 'deployment.yamr file) and the patches to apply. - The 'deployment.yamr file contains the base configuration for the deployment. - The 'patch.yamr file applies a strategic merge patch to the deployment, configuring rolling updates and automatic updates triggered by new images. - The 'maxSurgew and 'maxunavailable' settings in the 'patch.yamr define the maximum number ot pods that can be added or removed during the update process. - The 'imagePullPolicy: AlwayS ensures that the new image is pulled from Docker Hub even if it exists in the pod's local cache, triggering the update.
NEW QUESTION # 184
You have a Kubernetes deployment named 'my-app' that runs an application with a specific configuration defined in a ConfigMap named 'my-config'. You need to implement a strategy to automatically update tne deployment wnen tne ConfigMap is changed.
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Create a 'ConfigMap' named 'my-configs with the following contents:
2. Create a 'Deployment' named 'my-app' that mounts the 'my-config' ConfigMap as a volume:
3. Apply the ConfigMap and Deployment bash kubectl apply -f configmap.yaml kubectl apply -f deployment.yaml 4. Update the ConfigMap with new values:
5. Apply the updated ConfigMap: bash kubectl apply -f configmap.yaml - The 'kustomization.yamr file defines the resources (the 'deployment_yamr file) and the patches to apply. - The 'deployment_yamr file contains the base configuration for the deployment. - The patch.yamr tile applies a strategic merge patch to the deployment, configuring rolling updates and automatic updates triggered by new images. - The 'maxSurge' and 'maxunavailable' settings in the 'patch_yaml' define the maximum number of pods that can be added or removed during the update process. - The 'imagePullPolicy: Always' ensures that the new image is pulled from Docker Hub even if it exists in the pod's local cache, triggering the update.
NEW QUESTION # 185
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