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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Cloud Native Architecture | 16% | - Ecosystem & Landscape
|
| Topic 2: Cloud Native Application Delivery | 8% | - Deployment Strategies
|
| Topic 3: Container Orchestration | 22% | - Security & Troubleshooting
|
| Topic 4: Cloud Native Observability | 8% | - Logging & Tracing
|
| Topic 5: Kubernetes Fundamentals | 46% | - Kubernetes Core Concepts
|
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NEW QUESTION # 58
In a cloud native environment, who is usually responsible for maintaining the workloads running across the different platforms?
Answer: C
Explanation:
B (the Site Reliability Engineering team) is correct. In cloud-native organizations, SREs are commonly responsible for the reliability, availability, and operational health of workloads across platforms (multiple clusters, regions, clouds, and supporting services). While responsibilities vary by company, the classic SRE charter is to apply software engineering to operations: build automation, standardize runbooks, manage incident response, define SLOs/SLIs, and continuously improve system reliability.
Maintaining workloads "across different platforms" implies cross-cutting operational ownership: deployments need to behave consistently, rollouts must be safe, monitoring and alerting must be uniform, and incident practices must work across environments. SRE teams typically own or heavily influence the observability stack (metrics/logs/traces), operational readiness, capacity planning, and reliability guardrails (error budgets, progressive delivery, automated rollback triggers). They also collaborate closely with platform engineering and application teams, but SRE is often the group that ensures production workloads meet reliability targets.
Why other options are less correct:
The cloud provider (A) maintains the underlying cloud services, but not your application workloads' correctness, SLOs, or operational processes.
Developers (C) do maintain application code and may own on-call in some models, but the question asks "usually" in cloud-native environments; SRE is the widely recognized function for workload reliability across platforms.
Support Engineering (D) typically focuses on customer support and troubleshooting from a user perspective, not maintaining platform workload reliability at scale.
So, the best and verified answer is B: SRE teams commonly maintain and ensure reliability of workloads across cloud-native platforms.
NEW QUESTION # 59
What is the order of 4C's in Cloud Native Security, starting with the layer that a user has the most control over?
Answer: D
NEW QUESTION # 60
What is Flux constructed with?
Answer: D
Explanation:
The correct answer is B: GitOps Toolkit. Flux is a GitOps solution for Kubernetes, and in Flux v2 the project is built as a set of Kubernetes controllers and supporting components collectively referred to as the GitOps Toolkit. This toolkit provides the building blocks for implementing GitOps reconciliation: sourcing artifacts (Git repositories, Helm repositories, OCI artifacts), applying manifests (Kustomize/Helm), and continuously reconciling cluster state to match the desired state declared in Git.
This construction matters because it reflects Flux's modular architecture. Instead of being a single monolithic daemon, Flux is composed of controllers that each handle a part of the GitOps workflow: fetching sources, rendering configuration, and applying changes. This makes it more Kubernetes-native: everything is declarative, runs in the cluster, and can be managed like other workloads (RBAC, namespaces, upgrades, observability).
Why the other options are wrong:
* "GitLab Environment Toolkit" and "GitHub Actions Toolkit" are not what Flux is built from. Flux can integrate with many SCM providers and CI systems, but it is not "constructed with" those.
* "Helm Toolkit" is not the named foundational set Flux is built upon. Flux can deploy Helm charts, but that's a capability, not its underlying construction.
In cloud-native delivery, Flux implements the key GitOps control loop: detect changes in Git (or other declared sources), compute desired Kubernetes state, and apply it while continuously checking for drift. The GitOps Toolkit is the set of controllers enabling that loop.
Therefore, the verified correct answer is B.
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NEW QUESTION # 61
Which of the following is a lightweight tool that manages traffic flows between services, enforces access policies, and aggregates telemetry data, all without requiring changes to application code?
Answer: D
Explanation:
Linkerd is a lightweight service mesh that manages service-to-service traffic, security policies, and telemetry without requiring application code changes-so B is correct. A service mesh introduces a dedicated layer for east-west traffic (internal service calls) and typically provides features like mutual TLS (mTLS), retries/timeouts, traffic shaping, and consistent metrics/tracing signals. Linkerd is known for being simpler and resource-efficient relative to some alternatives, which aligns with the "lightweight tool" phrasing.
Why this matches the description: In a service mesh, workload traffic is intercepted by a proxy layer (often as a sidecar or node-level/ambient proxy) and managed centrally by mesh control components. This allows security and traffic policy to be applied uniformly without modifying each microservice. Telemetry is also generated consistently because the proxies observe traffic directly and emit metrics and traces about request rates, latency, and errors.
The other choices don't fit. NetworkPolicy is a Kubernetes resource that controls allowed network flows (L3/L4) but does not provide L7 traffic management, retries, identity-based mTLS, or automatic telemetry aggregation. kube-proxy implements Service networking rules (ClusterIP/NodePort forwarding) but does not enforce access policies at the service identity level and is not a telemetry system. Nginx can be used as an ingress controller or reverse proxy, but it is not inherently a full service mesh spanning all service-to-service communication and policy/telemetry across the mesh by default.
In cloud native architecture, service meshes help address cross-cutting concerns-security, observability, and traffic management-without embedding that logic into every application. The question's combination of "traffic flows," "access policies," and "aggregates telemetry" maps directly to a mesh, and the lightweight mesh option provided is Linkerd.
NEW QUESTION # 62
You are running a multi-cluster Kubernetes environment with Istio deployed. You want to enable mutual TLS authentication between services across different clusters. You have already configured Istio's 'mutualTLS' setting in the control plane. What additional step is required to enforce this security measure for inter-cluster communication?
Answer: D
Explanation:
While configuring 'mutualTLS' in the Istio control plane enables the security feature, you need to explicitly enable it for individual services by applying the 'istio.io/auth' annotation with 'peerAuthentication: mutualTLS: { mode. STRICT Y to each service. This ensures that services in both clusters will only communicate with each other over encrypted channels- Options B, C, D, and E are not directly related to enforcing mutual TLS authentication for inter-cluster communication.
NEW QUESTION # 63
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