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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Service Mesh | 16% | - Ingress and Gateway API - Traffic Encryption and Service Mesh Architectures |
| Topic 2: Cluster Mesh | 10% | - Multi-Cluster Connectivity - Service Discovery and Load Balancing |
| Topic 3: Network Observability | 10% | - Hubble and Layer 7 Visibility - Hubble CLI and UI |
| Topic 4: BGP and External Networking | 6% | - Connecting Cilium Clusters to External Networks - Egress Connectivity |
| Topic 5: Installation and Configuration | 10% | - Cilium CLI and Configuration - Installation and Connectivity Testing |
| Topic 6: eBPF | 10% | - eBPF Role and Benefits - eBPF and iptables-Based Networking |
| Topic 7: Network Policy | 18% | - Policy Rules and Enforcement - Identity-Based Network Security |
| Topic 8: Architecture | 20% | - IP Address Management and Datapath Models - Cilium Architecture and Components |
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NEW QUESTION # 12
Which question does Hubble provide the information to answer?
Answer: B
Explanation:
Technical explanation
Hubble provides network and security flow observability derived from Cilium's datapath. Its flow records include source and destination workloads, namespaces, identities, ports, protocols, forwarding verdicts, and drop reasons. Hubble can therefore identify services or workloads whose connections were rejected by network policy. The Hubble CLI supports filtering by verdict, such as --verdict DROPPED , and official examples show events labeled Policy denied DROPPED . These capabilities directly answer the question posed in option D.
Option B, which is marked as correct in the supplied bank, is not supported by the stated functionality.
Hubble may expose network-layer or supported application-layer metadata, including DNS and HTTP information when Layer 7 visibility is configured, but it is not a database query profiler and cannot determine which internal SQL statement ran longest merely from ordinary Hubble flows. Similarly, CPU utilization is a workload-resource metric normally obtained through Kubernetes metrics, Prometheus, or another monitoring system. Cilium BGP configuration is examined through Cilium configuration and BGP status commands rather than inferred from Hubble network flows.
The supplied answer key should therefore be corrected from B to D.
Official references
Inspecting Network Flows with the Hubble CLI ; Hubble internals .
Study Guide topic: Network Observability.
NEW QUESTION # 13 
Cilium status exhibit
Based on the cilium status output above, what is correct about the Cilium deployment?
For accessibility, the output of the command has been edited.
Answer: C
Explanation:
Technical explanation
The status output reports Operator: OK , followed by Deployment cilium-operator Desired: 1, Ready: 1/1, Available: 1/1 . This establishes that the Cilium Operator is deployed and healthy, making B the intended answer. Cilium uses Kubernetes CustomResourceDefinitions as its default mechanism for storing and propagating cluster state, while the operator performs cluster-wide duties that should be handled once centrally rather than independently on every node.
Option A is contradicted by the exhibit: both hubble-ui and hubble-relay appear as ready deployments and running containers. Option C is incorrect because the resource is explicitly identified as a Deployment ; the cilium agents, by contrast, are shown as a DaemonSet . Option D incorrectly treats the displayed desired replica count as a permanent restriction. A desired count of one describes this installation's current configuration, not a universal maximum.
The exhibit also shows embedded Envoy mode and three healthy Cilium agent instances, but neither detail changes the operator conclusion.
Official references
Cilium Component Overview , Setting up Hubble Observability
Study Guide topic: Cilium components, Cilium Operator, CRD-backed state, and status interpretation.
NEW QUESTION # 14
Which one of the following service mesh features and use cases is natively supported by Cilium?
Answer: C
Explanation:
Technical explanation
The intended answer is A because API request limiting corresponds to rate limiting, which Cilium identifies as a core Layer 7 traffic-management capability. Cilium combines its eBPF datapath with Envoy for application-layer processing. The official Service Mesh documentation expressly includes rate limiting among the functions that must understand protocols such as HTTP, REST, gRPC, and WebSocket. It is therefore not merely packet-rate policing at Layer 3 or Layer 4; it can be applied with application-protocol context.
However, this question is no longer valid as a strict single-answer item. Current Cilium documentation also describes proxy-based Layer 7 load balancing as useful for gRPC and provides an Envoy-backed implementation for Kubernetes Services. Consequently, option C is also supportable under the current product documentation, although the feature is identified as beta. API authorization and fault-delay injection are not presented as equivalent first-class Cilium Service Mesh use cases in the cited feature overview.
For certification-bank purposes, retain A as the intended answer, but revise option C or qualify it to restore a unique correct choice.
Official references
Service Mesh ; Proxy Load Balancing for Kubernetes Services .
Study Guide topic: Service Mesh.
NEW QUESTION # 15
What is NOT a valid description of the sidecar-based model?
Answer: A
Explanation:
Technical explanation
C is not a valid description. A service-mesh sidecar externalizes networking functions into a proxy container running beside the application; it does not force the instrumentation logic into the application's source code.
In fact, a core service-mesh objective is to provide connectivity, security, traffic management, and observability transparently without requiring application-code changes.
The operational concerns in the other choices are characteristic of sidecar implementations. A proxy must be injected into each workload pod, increasing container count and potentially affecting pod initialization, resource consumption, ordering, and readiness. Adding a sidecar to an existing pod template normally requires the pods to be recreated because Kubernetes cannot dynamically add a new container to an already- running pod.
Traffic interception also directs application traffic through the sidecar proxy and its network namespace paths, adding network-stack traversal and proxy-processing overhead. Cilium's service-mesh design can instead use node-level Envoy proxies together with eBPF traffic redirection, avoiding one proxy container in every application pod. This preserves transparent application behavior while reducing the per-workload operational burden.
Official references
Cilium Service Mesh , Cilium Ingress and Network Policy Example
Study Guide topic: Sidecar-based and sidecar-free service-mesh architectures.
NEW QUESTION # 16
Which component is embedded in the Cilium Agent and retrieves eBPF-based visibility from Cilium?
Answer: D
Explanation:
Technical explanation
The Hubble Server is embedded in each Cilium agent and consumes the eBPF-derived visibility data produced on that node. It exposes gRPC services through which clients can retrieve flow events, node and namespace information, server status, and related observability data. Embedding the server in the agent enables high-performance collection with comparatively low overhead.
Hubble Relay has a different role. It is a standalone component that discovers and connects to the Hubble Server instances running across the cluster. Relay aggregates their individual APIs to provide multi-node or cluster-wide visibility to clients such as the Hubble CLI and Hubble UI. It is therefore not the component embedded in the agent.
The Cilium CNI plugin is invoked when Kubernetes creates or removes pods and asks the local agent to configure their networking and datapath. The Cilium Operator performs cluster-wide management duties such as selected IPAM and shared-state operations. Neither component is responsible for exposing eBPF flow visibility.
This server-relay distinction is central to understanding Hubble's distributed architecture: Server provides node-local visibility, while Relay combines multiple servers into a cluster-wide view.
Official references
Hubble Internals , Cilium Component Overview
Study Guide topic: Hubble Server, Hubble Relay, and distributed flow observability.
NEW QUESTION # 17
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