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| Section | Weight | Objectives |
|---|---|---|
| Cloud Native Application Delivery | 8% | - Delivery Models
|
| Kubernetes Fundamentals | 46% | - Containerization Basics
|
| Cloud Native Architecture | 16% | - Cloud Native Principles
|
| Container Orchestration | 22% | - Networking & Storage
|
| Cloud Native Observability | 8% | - Logging & Tracing
|
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NEW QUESTION # 305
Which role is responsible of creating service level indicator 'SLI', service level objective 'SLO', & Service Level Agreements 'SLA'
Answer: B
Explanation:
https://www.atlassian.com/incident-management/kpis/sla-vs-slo-vs-sli
NEW QUESTION # 306
How many different Kubernetes service types can you define?
Answer: A
Explanation:
Kubernetes defines four primary Service types, which is why C (4) is correct. The commonly recognized Service spec.type values are:
ClusterIP: The default type. Exposes the Service on an internal virtual IP reachable only within the cluster. This supports typical east-west traffic between workloads.
NodePort: Exposes the Service on a static port on each node. Traffic to <NodeIP>:<NodePort> is forwarded to the Service endpoints. This is often used for simple external access in environments without load balancers, or as a building block for other systems.
LoadBalancer: Integrates with a cloud provider (or load balancer implementation) to provision an external load balancer and route traffic to the Service. This is common in managed Kubernetes.
ExternalName: Maps the Service name to an external DNS name via a CNAME record, allowing in-cluster clients to use a consistent Service DNS name to reach an external dependency.
Some people also talk about "Headless Services," but headless is not a separate type; it's a behavior achieved by setting clusterIP: None. Headless Services still use the Service API object but change DNS and virtual-IP behavior to return endpoint IPs directly rather than a ClusterIP. That's why the canonical count of "Service types" is four.
This question tests understanding of the Service abstraction: Service type controls how a stable service identity is exposed (internal VIP, node port, external LB, or DNS alias), while selectors/endpoints control where traffic goes (the backend Pods). Different environments will favor different types: ClusterIP for internal microservices, LoadBalancer for external exposure in cloud, NodePort for bare-metal or simple access, ExternalName for bridging to outside services.
Therefore, the verified answer is C (4).
NEW QUESTION # 307
What do Deployments and StatefulSets have in common?
Answer: A
Explanation:
Both Deployments and StatefulSets are Kubernetes workload controllers that manage a set of Pods created from a Pod template, meaning they manage Pods based on an identical container specification (a shared Pod template). That is why A is correct. In both cases, you declare a desired state (replicas, container images, environment variables, volumes, probes, etc.) in spec.template, and the controller ensures the cluster converges toward that state by creating, updating, or replacing Pods.
The differences are what make the other options incorrect. OnDelete update strategy is associated with StatefulSets (it's one of their update strategies), but it is not a shared, defining behavior across both controllers, so B is not "in common." Ordered, graceful deployment and scaling is a hallmark of StatefulSets (ordered pod creation/termination and stable identities) rather than Deployments, so C is not shared. Sticky identity per Pod (stable network identity and stable storage identity per replica, commonly via StatefulSet + headless Service) is specifically a StatefulSet characteristic, not a Deployment feature, so D is not common.
A useful way to think about it is: both controllers manage replicas of a Pod template, but they differ in semantics. Deployments are designed primarily for stateless workloads and typically focus on rolling updates and scalable replicas where any instance is interchangeable. StatefulSets are designed for stateful workloads and add identity and ordering guarantees: each replica gets a stable name (like db-0, db-1) and often stable PersistentVolumeClaims.
So the shared commonality the question is testing is the basic workload-controller pattern: both controllers manage Pods created from a common template (identical container spec). Therefore, A is the verified answer.
NEW QUESTION # 308
What is the practice of bringing financial accountability to the variable spend model of cloud resources?
Answer: B
Explanation:
The practice of bringing financial accountability to cloud spending-where costs are variable and usage- based-is called FinOps, so D is correct. FinOps (Financial Operations) is an operating model and culture that helps organizations manage cloud costs by connecting engineering, finance, and business teams. Because cloud resources can be provisioned quickly and billed dynamically, traditional budgeting approaches often fail to keep pace. FinOps addresses this by introducing shared visibility, governance, and optimization processes that enable teams to make cost-aware decisions while still moving fast.
In Kubernetes and cloud-native architectures, variable spend shows up in many ways: autoscaling node pools, over-provisioned resource requests, idle clusters, persistent volumes, load balancers, egress traffic, managed services, and observability tooling. FinOps practices encourage tagging/labeling for cost attribution, defining cost KPIs, enforcing budget guardrails, and continuously optimizing usage (right-sizing resources, scaling policies, turning off unused environments, and selecting cost-effective architectures).
Why the other options are incorrect: FaaS (Function as a Service) is a compute model (serverless), not a financial accountability practice. DevOps is a cultural and technical practice focused on collaboration and delivery speed, not specifically cloud cost accountability (though it can complement FinOps). CloudCost is not a widely recognized standard term in the way FinOps is.
In practice, FinOps for Kubernetes often involves improving resource efficiency: aligning requests/limits with real usage, using HPA/VPA appropriately, selecting instance types that match workload profiles, managing cluster autoscaler settings, and allocating shared platform costs to teams via labels/namespaces. It also includes forecasting and anomaly detection, because cloud-native spend can spike quickly due to misconfigurations (e.g., runaway autoscaling or excessive log ingestion).
So, the correct term for financial accountability in cloud variable spend is FinOps (D).
=========
NEW QUESTION # 309
What is container runtime?
Answer: D
Explanation:
https://www.aquasec.com/cloud-native-academy/container-security/container-runtime/
NEW QUESTION # 310
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