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| Section | Objectives |
|---|---|
| Topic 1: Compute and Storage Services | - Elastic Cloud Server (ECS) and container services
|
| Topic 2: Database and Middleware Services | - Cloud database services
|
| Topic 3: Solution Design and Migration | - Solution architecture design
|
| Topic 4: Cloud Architecture Design Principles | - Huawei Cloud architecture overview
|
| Topic 5: Operations and Monitoring | - Cloud monitoring and O&M
|
| Topic 6: Network and Security Design | - Cloud network architecture
|
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NEW QUESTION # 30
When you create a cluster in Cloud Container Engine (CCE), which of the following container network models can you select?
Select all that apply.
Answer: A,C
Explanation:
"CCE supports the following container network models: container tunnel network, VPC network, and Cloud Native Network 2.0."
"The container tunnel network is constructed on but independent of the node network through tunnel encapsulation. This network model uses VXLAN to encapsulate Ethernet packets into UDP packets and transmits them in tunnels. Open vSwitch serves as the backend virtual switch." Huawei source: Training PDF pp. 456-457 Technical Deep Dive Huawei Cloud CCE supports three container-network models in the V3.5 course: container tunnel network, VPC network and Cloud Native Network 2.0. Option B is correct because the tunnel model uses encapsulation-VXLAN over UDP in the documented implementation-to carry pod traffic across an underlying node network. Open vSwitch acts as a virtual switching component in the tunnel architecture.
Option D is correct because Cloud Native Network 2.0 integrates pod networking with VPC resources. Pod IP addresses can be allocated from the VPC CIDR range, using the applicable enhanced networking and network-interface mechanisms. This reduces encapsulation overhead and supports demanding throughput and latency requirements. Option A is incorrect because a VPN is a service for encrypted connectivity between separate networks, not a named CCE pod-network model. Option C is incorrect because the Kubernetes Service network allocates virtual addresses for Service access; it does not describe the underlying pod- network implementation selected when creating the cluster.
The omitted third legitimate model is VPC network. The question does not offer that option, but its absence does not make the listed choices ambiguous. Architects should select networking based on throughput, latency, IP consumption, integration with security groups, number of nodes and workload scale. Networking performance also depends on underlying ECS specifications and routes. Check container and service CIDRs carefully to avoid overlap with existing VPC or on-premises ranges. Huawei's official model list supports B and D.
NEW QUESTION # 31
A Kubernetes cluster is made up of master nodes and worker nodes. A master node manages the whole cluster. Which of the following components run on a master node?
Select all that apply.
Answer: A,B
Explanation:
"A master node is the machine where the control plane components run, including API server, scheduler, controller manager, and etcd. In a production environment, multiple master nodes are deployed to ensure high cluster availability."
"A worker node is a compute node for running containerized applications in a cluster. Kubelet, kube-proxy, and container runtime are running on each worker node." Huawei source: Training PDF p. 415 Technical Deep Dive Huawei's Kubernetes architecture places the API server, scheduler, controller manager and etcd in the control plane. Option A is correct because kube-apiserver exposes the Kubernetes API and receives administrative and controller requests. Option D is correct because the scheduler chooses suitable nodes for pending pods based on available capacity and scheduling constraints.
Option B , Docker, is not a Kubernetes control-plane component. Docker is a container platform/runtime technology. Modern Kubernetes typically uses a compatible container runtime such as containerd, and the runtime is associated with workload execution rather than the API/scheduling control functions. Option C , kubelet, is primarily described by Huawei's diagram as a worker-node agent that manages containers and pods according to control-plane instructions.
There is a technical ambiguity: real Kubernetes control-plane hosts can also run kubelet to manage static pods and other node-local components. Therefore it would be inaccurate to claim kubelet never runs on a master.
The examination should ask which are control-plane components instead of which components merely run on a master host. Production Kubernetes commonly uses multiple control-plane nodes to avoid a single point of management failure, though application availability also depends on workers and data services. Useful validation commands include kubectl get nodes -o wide, kubectl cluster-info and kubectl get pods -n kube- system. Under the course's architectural classification, A and D are the defensible answers.
Technical commands / calculations from the reviewed batch
kubectl get nodes -o wide
kubectl get pods -n kube-system
kubectl cluster-info
NEW QUESTION # 32
Cloud Eye server monitoring includes basic metrics, operating systems, and processes. Which of the following statements about server monitoring is incorrect?
Answer: B
Explanation:
"Automatic Monitoring: Cloud Eye activates automatically upon resource creation (e.g., ECSs). Users can view resource status and create alarm rules through the console."
"Server Monitoring: After Agent installation, minute-level real-time monitoring data is collected from ECSs and BMSs."
[The full Agent and basic-memory metric behavior requires official Cloud Eye product documentation. ] Huawei source: Training PDF p. 589; official Cloud Eye Agent documentation A repair could change B to 'Some basic ECS metrics, including CPU usage, are reported automatically; detailed memory metrics may require an Agent' and then make A the single false option. Alternatively, correct A and test B. Until repaired, the item should not be represented as having one unambiguously valid letter. The defensible warning is A and B both contain inaccurate claims.
Technical commands / calculations from the reviewed batch
# Example Agent-service operations; verify installed Agent version.
service telescoped status
service telescoped stop
service telescoped restart
NEW QUESTION # 33
What does Cloud Eye alerting for monitoring metrics allow you to do?
Select all that apply.
Answer: B,C,D
Explanation:
"Users can create alarm rules for key metrics of cloud services. When the conditions in the alarm rule are met, Cloud Eye reports the alarms using emails, SMS, or HTTP/HTTPS requests, enabling users to quickly respond to resource changes."
[The slide lists] flexible policies, varied notifications through HTTP/HTTPS/FunctionGraph/SMS/email, Auto Scaling integration, and default or custom alarm templates.
Huawei source: Training PDF p. 591; official Cloud Eye documentation
Technical Deep Dive
Cloud Eye alarm management allows administrators to define resource- and metric-specific thresholds, triggering rules, notification routes and operational responses. Option A is true because alarm policies can be tailored to individual monitored objects, metrics and events. Option B is true because Huawei supplies standard and customizable templates that can be applied across resources in batches, reducing repetitive configuration and improving policy consistency.
Option D is true. The Huawei V3.5 alarm slide lists HTTP/HTTPS, SMS, email, FunctionGraph and Auto Scaling integration, while related official documentation confirms voice notification channels where supported. A Cloud Eye threshold can notify an operator, invoke an automated function or participate in a scaling policy. For instance, sustained CPU utilization above an agreed threshold can initiate capacity scaling while the operations team receives an alert.
Option C is false because Huawei supports monitoring integration with external observability systems. Cloud Eye metrics can be exposed through suitable exporter and API mechanisms to Prometheus-compatible environments, and those metrics can be visualized in Grafana as part of a broader monitoring architecture.
The claim that such interconnection is categorically unsupported is therefore wrong. Operationally, alarm thresholds must account for duration, evaluation periods, retry behavior, resource scale and alert fatigue. Too- sensitive alerts can generate noise, while overly broad thresholds can miss failures. Automatic scaling requires sensible minimum and maximum capacities, cooldown settings and health checks. A, B and D are the supported capabilities; C is the inaccurate denial of integration.
NEW QUESTION # 34
A customer purchased a general computing-plus Elastic Cloud Server (ECS) with the c9.xlarge.2 flavor on Huawei Cloud. This indicates that the ECS has 4 vCPUs and 16 GiB of memory.
Answer: B
Explanation:
"A flavor name usually consists of the instance family and generation, instance size, and memory/vCPU ratio."
[The naming slide] The xlarge designation represents four vCPUs, and the suffix .2 specifies a memory-to- vCPU ratio of two GiB per vCPU.
Huawei source: Training PDF p. 57
Technical Deep Dive
The flavor c9.xlarge.2 follows Huawei's naming convention. The c9 prefix identifies a general computing- plus ECS family, xlarge denotes four vCPUs, and the final .2 specifies two GiB of memory per vCPU. The instance therefore has four vCPUs and eight GiB of RAM, not 16 GiB. The correct answer is FALSE, option B.
An ECS with four vCPUs and 16 GiB would need a ratio of four GiB per vCPU, commonly indicated by a .4 suffix if a corresponding flavor is offered. Failing to interpret the suffix leads to predictable capacity mistakes.
For example, a Java application with a 12 GiB heap plus operating-system overhead cannot safely fit in an instance with only eight GiB of memory, even if its CPU requirement is within four vCPUs.
Huawei Cloud architects must check more than the core and memory totals: memory working sets, CPU peaks, network packet rates, EIP limits, disk IOPS and throughput can all determine application performance.
Correct flavor selection also depends on regional availability and the workload's operating system. General computing-plus infrastructure may offer high-performance virtualized I/O, but hardware optimizations do not increase the memory stated by the flavor naming rule. The question's arithmetic is unambiguous: four multiplied by two equals eight GiB, so the claim of 16 GiB is false.
Technical commands / calculations from the reviewed batch
4 vCPUs × 2 GiB/vCPU = 8 GiB RAM
NEW QUESTION # 35
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