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| Section | Objectives |
|---|---|
| Topic 1: Cloud Security and Governance | - Security fundamentals in cloud native systems
|
| Topic 2: Cloud Native Application Delivery | - CI/CD and deployment strategies
|
| Topic 3: Container Orchestration | - Container lifecycle and scheduling
|
| Topic 4: Kubernetes Fundamentals | - Core Kubernetes concepts
|
| Topic 5: Cloud Native Architecture | - Microservices and distributed systems
|
| Topic 6: Cloud Native Observability | - Monitoring and logging
|
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NEW QUESTION # 18
What is the difference between a Deployment and a ReplicaSet?
Answer: D
Explanation:
A Deployment is a higher-level controller that manages ReplicaSets and provides rollout/rollback behavior, so D is correct. A ReplicaSet's primary job is to ensure that a specified number of Pod replicas are running at any time, based on a label selector and Pod template. It's a fundamental "keep N Pods alive" controller.
Deployments build on that by managing the lifecycle of ReplicaSets over time. When you update a Deployment (for example, changing the container image tag or environment variables), Kubernetes creates a new ReplicaSet for the new Pod template and gradually shifts replicas from the old ReplicaSet to the new one according to the rollout strategy (RollingUpdate by default). Deployments also retain revision history, making it possible to roll back to a previous ReplicaSet if a rollout fails.
Why the other options are incorrect:
A is false: Deployments absolutely control the number of replicas via spec.replicas and can also be controlled by HPA.
B is false: ReplicaSets do guarantee that a stable number of replicas is running (that is their core purpose).
C is false: a Deployment is not "a ReplicaSet with annotations." It is a distinct API resource with additional controller logic for declarative updates, rollouts, and revision tracking.
Operationally, most teams create Deployments rather than ReplicaSets directly because Deployments are safer and more feature-complete for application delivery. ReplicaSets still appear in real clusters because Deployments create them automatically; you'll commonly see multiple ReplicaSets during rollout transitions. Understanding the hierarchy is crucial for troubleshooting: if Pods aren't behaving as expected, you often trace from Deployment → ReplicaSet → Pod, checking selectors, events, and rollout status.
So the key difference is: ReplicaSet maintains replica count; Deployment manages ReplicaSets and orchestrates updates. Therefore, D is the verified answer.
NEW QUESTION # 19
What is the goal of load balancing?
Answer: D
Explanation:
The goal of load balancing is to distribute incoming requests evenly across multiple instances of an application, improving availability, reliability, and overall system performance by avoiding overload on any single instance.
NEW QUESTION # 20
What is the main purpose of the Ingress in Kubernetes?
Answer: C
Explanation:
D is correct. Ingress is a Kubernetes API object that defines rules for external access to HTTP/HTTPS services in a cluster. The defining capability is Layer 7 routing-commonly host-based and path-based routing-so you can route requests like example.com/app1 to one Service and example.com/app2 to another. While the question mentions "based on their path," that's a classic and correct Ingress use case (and host routing is also common).
Ingress itself is only the specification of routing rules. An Ingress controller (e.g., NGINX Ingress Controller, HAProxy, Traefik, cloud-provider controllers) is what actually implements those rules by configuring a reverse proxy/load balancer. Ingress typically terminates TLS (HTTPS) and forwards traffic to internal Services, giving a more expressive alternative to exposing every service via NodePort/LoadBalancer.
Why the other options are wrong:
A suggests routing by IP address; Ingress is fundamentally about HTTP(S) routing rules (host/path), not direct Service IP access.
B and C describe non-HTTP protocols; Ingress is specifically for HTTP/HTTPS. For TCP/UDP or other protocols, you generally use Services of type LoadBalancer/NodePort, Gateway API implementations, or controller-specific TCP/UDP configuration.
Ingress is a foundational building block for cloud-native application delivery because it centralizes edge routing, enables TLS management, and supports gradual adoption patterns (multiple services under one domain). Therefore, the main purpose described here matches D.
NEW QUESTION # 21
How is application data maintained in containers?
Answer: D
Explanation:
Container filesystems are ephemeral: the writable layer is tied to the container lifecycle and can be lost when containers are recreated. Therefore, maintaining application data correctly means storing it in volumes, making D the correct answer. In Kubernetes, volumes provide durable or shareable storage that is mounted into containers at specific paths. Depending on the volume type, the data can persist across container restarts and even Pod rescheduling.
Kubernetes supports many volume patterns. For transient scratch data you might use emptyDir (ephemeral for the Pod's lifetime). For durable state, you typically use PersistentVolumes consumed by PersistentVolumeClaims (PVCs), backed by storage systems via CSI drivers (cloud disks, SAN/NAS, distributed storage). This decouples the application container image from its state and enables rolling updates, rescheduling, and scaling without losing data.
Options A and B ("folders") are incomplete because folders inside the container filesystem do not guarantee persistence. A folder is only as durable as the underlying storage; without a mounted volume, it lives in the container's writable layer and will disappear when the container is replaced. Option C is incorrect because
"sidecar containers" are not a data durability mechanism; sidecars can help ship logs or sync data, but persistent data should still be stored on volumes (or external services like managed databases).
From an application delivery standpoint, the principle is: containers should be immutable and disposable, and state should be externalized. Volumes (and external managed services) make this possible. In Kubernetes, this is a foundational pattern enabling safe rollouts, self-healing, and portability: the platform can kill and recreate Pods freely because data is maintained independently via volumes.
Therefore, the verified correct choice is D: Store data into volumes.
=========
NEW QUESTION # 22
In Kubernetes, which abstraction defines a logical set of Pods and a policy by which to access them?
Answer: D
Explanation:
A Service in Kubernetes defines a logical set of Pods and a policy to access them, typically providing stable networking and load balancing.
NEW QUESTION # 23
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