Kubernetes Operators Advanced Cognitive Class Exam Quiz Answers

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Enroll Here: Kubernetes Operators Advanced Cognitive Class Exam Quiz Answers

Kubernetes Operators Advanced Cognitive Class Certification Answers

Module 1 – Reconciliation Loops Quiz Answers – Cognitive Class

Question 1: What are the results that can be returned from a single iteration of a reconcile loop?

• Requeue, Exit without requeuing
• Return and requeue, Return an error and requeue, Exit without requeuing
• Exit, Exit with error
• Return and requeue, Return an error, Exit without requeuing

Question 2: The reconciliation loop is where the actual behavior of an operator is defined.

• True
• False

Question 3: Why is it a good idea to build a reconciliation loop out of small, iterative steps?

• The desired state of the cluster can change during reconciliation
• The actual state of the cluster can change during reconciliation
• The reconciliation request might be picked up by multiple controllers
• All of the above

Question 4: What do the Kubebuilder markers we put above the Reconcile method declaration do?

• The reconciliation request might be picked up by multiple controllers
• Create the RBAC for the controller to access the specified resources
• Scaffold the custom resource types for the operator
• Scaffold the reconcile loops for the specified resource

Question 5: It is possible for the object you are reconciling to no longer exist by the time the request is being processed.

• True
• False

Module 2 – Operator Lifecycle Manager Quiz Answers – Cognitive Class

Question 1: What are the three main components of a bundle?

• Sample, Config, and Image
• Manifests, Metadata, and a Dockerfile
• Config, an Operator image, and a bundle image
• Data, Metadata, and a Dockerfile

Question 2: A conversion webhook is a special kind of admission webhook.

• True
• False

Question 3: Why is it important to include a conversion webhook when upgrading the API version of an operator?

• To convert running instances to the new version of Memcached
• To migrate requests from users and controllers to the new version
• To migrate the database records to the new version
• To convert pre-existing instances of the resource to the new version

Question 4: Kubernetes conversion logic is based on what kind of model?

• Many to Many
• Hub and Spoke
• Up and Down
• Wheel and Deal

Question 5: Although the underlying custom resources that OLM uses may change, the format of an operator bundle should stay the same moving forward.

• True
• False

Module 3 – Scorecard Quiz Answers – Cognitive Class

Question 1: In the config file, each Scorecard test consists of what three components?

• Operator image, Test image, Test command
• Image, Entrypoint, Labels
• Test file, Commands, Bundle
• Dockerfile, Entrypoint, Name

Question 2: Scorecard tests execute from your local machine targeting the cluster.

• True
• False

Question 3: Why did we have to cross compile our Scorecard test?

• To include our Scorecard config
• It’s executed in a container on the cluter, which is a 64-bit Linux environment
• To include our operator’s bundle
• To ensure all the dependencies were included

Question 4: Why did we run our Scorecard test with our operator’s Service Account?

• To give Scorecard the RBAC permissions to run the test container
• To give it the RBAC permissions needed to manipulate the Memcached and dependant types
• To give it the RBAC permissions to manipulate our operator’s controller
• To tell it which operator to test

Question 5: The Scorecard config is part of your operator’s bundle.

• True
• False

Kubernetes Operators Advanced Final Exam Answers – Cognitive Class

Question 1: Your Scorecard config is automatically generated as part of your operator’s bundle.

• True
• False

Question 2: Why is it important to include a conversion webhook when upgrading the API version of an operator?

• To convert running instances to the new version of Memcached
• To migrate requests from users and controllers to the new version
• To migrate the database records to the new version
• To convert pre-existing instances of the resource to the new version

Question 3: Your bundle starts with some automatically generated Scorecard tests that test what features of your operator?

• Regression tests to test upgrading your operator
• Basic best practices like descriptors and validators for your custom resource types
• Benchmarks to stress-test your operator
• Basic unit tests that test your custom resource types

Question 4: What are the results that can be returned from a single iteration of a reconcile loop?

• Requeue, Exit without requeuing
• Return and requeue, Return an error and requeue, Exit without requeuing
• Exit, Exit with error
• Return and requeue, Return an error, Exit without requeuing

Question 5: Conversion between different API versions of the same resource is based on a Hub-and-Spoke model.

• True
• False

Question 6: Why should you start a reconciliation loop by fetching the object you’re reconciling?

• To get the most recent API version of the object
• The object may have been deleted, updated, or otherwise invalidated in the meantime
• To fetch the object’s schema
• The object object isn’t included in the reconciliation request

Question 7: A conversion webhook is a special type of which kind of default Kubernetes resource?

• Controller webhook
• Mutating webhook
• Upgrade webhook
• Admission webhook

Question 8: Why is it a good idea to build a reconciliation loop out of small, iterative steps?

• The desired state of the cluster can change during reconciliation
• The actual state of the cluster can change during reconciliation
• The reconciliation request might be picked up by multiple controllers
• All of the above

Question 9: What are the three main components of a bundle?

• Sample, Config, and Image
• Manifests, Metadata, and a Dockerfile
• Config, an Operator image, and a bundle image
• Data, Metadata, and a Dockerfile

Question 10: A Scorecard test requires a Service Account with permissions to access your custom resource types.

• True
• False

Introduction to Kubernetes Operators Advanced

With the strong idea of Kubernetes Operators, complicated services and applications may be managed using the Kubernetes API as if they were native resources. They capture best practices for managing stateful applications and automate operations related to deployment, scaling, and maintenance. More advanced features and capabilities are frequently utilized by Advanced Kubernetes Operators. Here are some key components and concepts:

1. Understanding Kubernetes Operators:
   • Kubernetes Operators are software extensions to Kubernetes that make use of custom resources to manage applications and their components. They encapsulate operational knowledge for specific applications, automating their deployment, scaling, and management.
2. Custom Resources (CRs):
   • CRs are extensions of the Kubernetes API that allow you to define your own custom objects. Operators use CRs to represent the state and desired configurations of the applications they manage. For example, a database operator might define custom resources like MySQLCluster or PostgreSQLInstance.
3. Operator Frameworks:
   • Several frameworks like Operator SDK, Kubebuilder, and Metacontroller simplify the development of Kubernetes Operators. These frameworks provide scaffolding, libraries, and best practices for building reliable and scalable Operators.
4. Controller Pattern:
   • Operators are built using the controller pattern. Controllers watch for changes to custom resources and reconcile the actual state with the desired state specified in these resources. This reconciliation loop ensures that the application stays in the desired state.
5. CRD (Custom Resource Definition):
   • CRDs define the structure and validation rules for custom resources. They specify the API schema for custom resources and are installed in a Kubernetes cluster to extend its capabilities.
6. Operator Lifecycle Management (OLM):
   • OLM is a methodology for installing, updating, and managing Kubernetes Operators. It provides features like dependency resolution, versioning, and automated upgrades to ensure the smooth operation of Operators in a cluster.
7. Operator Maturity Model:
   • The Operator Maturity Model defines different levels of maturity for Kubernetes Operators, ranging from basic automation to full self-driving systems. Advancing through these levels involves improving reliability, scalability, and automation capabilities.
8. Advanced Operator Patterns:
   • Operators can implement advanced patterns like leader election, multi-cluster management, and complex application lifecycle management. These patterns enable Operators to handle more sophisticated use cases and operate effectively at scale.
9. Operator Best Practices:
   • Following best practices such as idempotent reconciliation, declarative configuration, and observability ensures the reliability and maintainability of Kubernetes Operators. Testing, monitoring, and documenting Operators are also crucial aspects of their development lifecycle.

By mastering these advanced concepts and techniques, you can leverage Kubernetes Operators to automate the deployment and management of sophisticated applications in Kubernetes clusters, leading to improved efficiency, reliability, and scalability.