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A platform team wants to let developers provision cloud services like S3 buckets and databases using Kubernetes-native APIs, without exposing cloud-specific details. Which tool is best suited for this?
A. OpenTofu
B. Cluster API
C. Helm
D. Crossplane
Answer: D
Explanation:
Crossplane is the CNCF project designed to extend Kubernetes with the ability to provision and manage cloud resources via Kubernetes-native APIs. Option B is correct because Crossplane lets developers use familiar Kubernetes manifests to request resources like S3 buckets, databases, or VPCs while abstracting provider-specific implementation details. Platform teams can define compositions and abstractions, providing developers with golden paths that include organizational guardrails.
Option A (Cluster API) is focused on provisioning Kubernetes clusters themselves, not cloud services. Option C (Helm) manages Kubernetes application deployments but does not provision external infrastructure. Option D (OpenTofu) is a Terraform fork that provides IaC but is not Kubernetes-native.
By leveraging Crossplane, platform teams achieve infrastructure as data and full GitOps integration, empowering developers to provision services declaratively while ensuring governance and compliance.
References:- CNCF Crossplane Project Documentation- CNCF Platforms Whitepaper- Cloud Native Platform Engineering Study Guide
NEW QUESTION # 35
What does the latest tag usually represent in a container image registry?
A. A signed image that has passed all security validations.
B. The only image tag that can be deployed to production systems.
C. A system-generated version number based on Git history.
D. The most recently built image unless otherwise specified.
Answer: D
Explanation:
In most container registries, the latest tag is simply an alias pointing to whichever image was most recently built and pushed, unless explicitly overridden. Option A is correct because the latest tag does not carry any semantic guarantee beyond being the most recently tagged version.
Option B is incorrect-latest does not imply security validation or attestation. Option C is false because production systems should not rely on latest; instead, immutable, versioned tags or digests should be used for reproducibility. Option D is misleading, as latest is not tied to Git history but rather to tag assignment during the build/push process.
While convenient for testing or local development, relying on latest in production pipelines is discouraged.
Platform engineering best practices emphasize explicit versioning and image immutability to ensure consistency, reproducibility, and traceability. Using signed images with SBOM attestation is recommended for security and compliance, while latest should only be used in controlled, non-production workflows.
References:- CNCF Supply Chain Security Whitepaper- CNCF Platforms Whitepaper- Cloud Native Platform Engineering Study Guide
NEW QUESTION # 36
Which key observability signal helps detect real-time performance bottlenecks in a Kubernetes cluster?
A. Metrics
B. Traces
C. Events
D. Logs
Answer: A
Explanation:
Metrics are the observability signal most effective at detecting real-time performance bottlenecks in Kubernetes. Option C is correct because metrics provide numerical, time-series data (e.g., CPU usage, memory consumption, request latency, pod restarts) that can be aggregated and monitored continuously. This makes them the best fit for identifying performance degradation and bottlenecks before they escalate into outages.
Option A (logs) capture detailed events but are better for debugging after issues occur. Option B (traces) provide request-level insights across distributed systems but focus on transaction flow rather than cluster-wide performance. Option D (events) record discrete system changes but are not designed for continuous performance monitoring.
Metrics integrate with tools like Prometheus and Grafana, enabling SLO/SLI monitoring and alerting. They allow proactive capacity planning, scaling decisions, and real-time issue detection-critical aspects of cloud native observability.
References:- CNCF Observability Whitepaper- Prometheus CNCF Documentation- Cloud Native Platform Engineering Study Guide
NEW QUESTION # 37
In a multi-cluster Kubernetes setup, which approach effectively manages the deployment of multiple interdependent applications together as a unit?
A. Using Helm for application packaging with manual deployments.
B. Employing a declarative application deployment definition.
C. Direct deployments from CI/CD with Git configuration.
D. Creating separate Git repositories per application.
Answer: B
Explanation:
In multi-cluster Kubernetes environments, the challenge lies in consistently deploying interdependent applications across clusters while ensuring reliability and repeatability. The Cloud Native Platform Engineering guidance stresses the importance of a declarative approach to define applications as code, which enables teams to describe the entire application system-including dependencies, configuration, and policies-in a single manifest. This ensures that applications are treated as a cohesive unit rather than isolated workloads.
Option A is correct because declarative application deployment definitions (often managed through GitOps practices) allow for consistent and automated reconciliation of desired state versus actual state across multiple clusters. This approach supports scalability, disaster recovery, and compliance by ensuring identical deployments across environments.
Option B (separate repos per application) increases fragmentation and does not inherently manage interdependencies. Option C (direct deployments from CI/CD) bypasses the GitOps model, which reduces auditability and consistency. Option D (Helm with manual deployments) partially addresses packaging but lacks the automation and governance needed in a multi-cluster setup.
References:- CNCF GitOps Principles for Platforms- CNCF Platforms Whitepaper- Cloud Native Platform Engineering Study Guide
NEW QUESTION # 38
Development teams frequently raise support tickets for short-term access to staging clusters, creating a growing burden on the platform team. What's the best long-term solution to balance control, efficiency, and developer experience?
A. Set up scheduled access windows and batch all requests into specific time slots managed by the platform team.
B. Provide pre-approved kubeconfigs to trusted developers so they can access staging clusters without platform intervention.
C. Use GitOps to manage RBAC roles and allow teams to request access via pull requests with automatic approval for non-sensitive environments.
D. Dedicate one Cloud Native Platform Engineer to triage and fulfill all access requests to maintain fast turnaround times.
Answer: C
Explanation:
The most sustainable solution for managing developer access while balancing governance and self-service is to adopt GitOps-based RBAC management. Option A is correct because it leverages Git as the source of truth for access permissions, allowing developers to request access through pull requests. For non-sensitive environments such as staging, approvals can be automated, ensuring efficiency while still maintaining auditability. This approach aligns with platform engineering principles of self-service, automation, and compliance.
Option B places the burden entirely on one engineer, which does not scale. Option C introduces bottlenecks, delays, and reduces developer experience. Option D bypasses governance and auditability, potentially creating security risks.
GitOps for RBAC not only improves developer experience but also ensures all changes are versioned, reviewed, and auditable. This model supports compliance while reducing manual intervention from the platform team, thus enhancing efficiency.
References:- CNCF GitOps Principles- CNCF Platforms Whitepaper- Cloud Native Platform Engineering Study Guide
NEW QUESTION # 39
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