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| Section | Objectives |
|---|---|
| Building Highly Available, Performant Cloud Architecture | - Leveling up Your Core Infrastructure |
| Building Enterprise-grade Networks on Alibaba Cloud | - Cloud Networking Deep Dive |
| Core Infrastructure Deep Dive | - Core Compute Infrastructure Deep Dive - Best Practices for Database Services - Core Storage Infrastructure Deep Dive |
| Securing Workloads on Alibaba Cloud | - Alibaba Cloud Security Deep Dive |
| Delivering Services and Content on Alibaba Cloud | - Delivering Services and Content on Alibaba Cloud |
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NEW QUESTION # 45
Sam runs a gaming startup, and is launching a real-time, massively multiplayer game on Alibaba Cloud.
Based on presales numbers, the startup predicts that there will be millions of concurrent users at launch. To ensure the experience of the gamers, their architecture must be able to deliver sub-50ms latency, scale automatically in response to sudden player surges, and provide efficient session management for millions of concurrent users.
What Alibaba Cloud services can Sam leverage to meet the requirements for the playerbase? (Correct answers: 3)
Answer: A,B,E
Explanation:
Tair, Auto Scaling, and ALB directly address the three core runtime requirements: session performance, elastic capacity, and distributed traffic handling.
Tair provides an in-memory Redis-compatible data tier that is appropriate for high-frequency session information. Keeping session state outside individual ECS game servers allows requests to be handled by different backend instances without losing player session information and avoids disk/database latency on critical session lookups.
Auto Scaling directly satisfies the requirement to react automatically to sudden player surges. Alibaba Cloud Auto Scaling can monitor metrics such as CPU utilization and automatically add ECS instances when capacity thresholds are exceeded, then remove excess capacity as demand decreases.
ALB distributes client requests across the resulting game-server fleet, performs health checks, and avoids overloading individual ECS instances.
CDN is highly valuable for downloading static assets such as textures, patches, images, and game packages because those objects can be cached at edge POPs. However, standard CDN does not provide the core dynamic scaling mechanism for real-time game sessions. Given that exactly three selections are required, Auto Scaling is essential because the question explicitly requires automatic scaling during player surges.
Study Guide reference: Building Highly Available, Performant Cloud Architecture - Tair, ALB, Auto Scaling, low-latency session architecture, and elastic gaming workloads.
NEW QUESTION # 46
A global consultancy firm needs to ensure that their applications hosted on Alibaba Cloud have low latency for users distributed worldwide. They require a solution that can cache static content and dynamically route user requests to the nearest point-of-presence (PoP).
Which Alibaba Cloud service should the firm implement to achieve this?
Answer: A
Explanation:
Alibaba Cloud CDN is specifically designed to accelerate content delivery by distributing and caching content at geographically distributed points of presence. When a user requests an accelerated resource, CDN DNS scheduling assigns an appropriate PoP. If the resource is cached there, the PoP returns it directly without requiring a round trip to the origin infrastructure. Alibaba Cloud documentation explicitly states that static resources are cached on the nearest PoP to reduce latency and improve access efficiency.
This directly satisfies both key requirements in the question: caching static content and directing users toward edge infrastructure close to their locations. If content is not cached or has expired, the CDN PoP performs an origin fetch and then serves the resource.
GTM can perform DNS-based geographical or latency routing among application endpoints and regions, but it is not itself a distributed static-content caching service. Express Connect provides private dedicated connectivity between enterprise/on-premises networks and Alibaba Cloud. SLB distributes traffic among backend servers but does not provide a worldwide edge caching network.
Therefore, Alibaba Cloud CDN is the only listed service that simultaneously implements PoP-based edge delivery and static-content caching.
Study Guide reference: Delivering Content on Alibaba Cloud; content acceleration and global application- delivery architecture.
NEW QUESTION # 47
Ibrahim manages a large-scale manufacturing plant equipped with state-of-the-art instrumentation and telemetry that collects various information about the machines and products. These sensors collectively generate 1 TB worth of logs each day. Each notification is approximately 2 KB in size. You have been contracted to design a solution to ingest and store these logs for future analysis.
Ibrahim wants a highly available solution, but also wants to minimize costs. Additionally, he does not want to manage additional infrastructure. To meet their business requirements, they need to keep 14 days of data available for immediate analysis, and archive any other data older than 14 days.
What is the MOST operationally efficient solution that meets these requirements?
Answer: C
Explanation:
Simple Log Service (SLS) is a managed log-ingestion, storage, query, analysis, and visualization service, making it the most operationally efficient front-end for this telemetry workload. It eliminates the requirement to provision and manage ECS-based collectors or a separate search cluster simply to ingest and analyze log records.
For longer-term retention, Alibaba Cloud supports automatically shipping SLS data to OSS. This creates a clean hot-to-cold architecture: maintain recent data in SLS for interactive analysis and export older data to OSS for economical retention.
OSS lifecycle management can then automatically transition aging objects to lower-cost storage classes such as Archive. Lifecycle rules are explicitly designed to automate storage-class transitions based on object age, eliminating manual archival administration.
Option A requires additional Elasticsearch retention administration. Option B requires managing ECS infrastructure even though the question explicitly prioritizes reduced operational management. Option D adds Kafka unnecessarily and still specifies manual archival, directly conflicting with the requirement to minimize operational effort.
Thus, SLS for managed ingestion and recent analysis combined with SLS-to-OSS shipping and OSS lifecycle transitions provides the strongest serverless/managed retention architecture.
Study Guide reference: Core Infrastructure Deep Dive; Core Storage Infrastructure; operationally efficient log and data-storage architecture.
NEW QUESTION # 48
Eric is developing a containerized application that will run on an Alibaba Cloud Container Service for Kubernetes (ACK) cluster. This production application will run on a managed ACK cluster that is provisioned with pay-as-you-go instances.
Eric also needs a dedicated ACK cluster for development work. This cluster will be used infrequently to test the resiliency of the application. Due to having a limited workforce and time, Eric hopes that ACK will be able to manage all the nodes in the cluster.
As a Cloud Architect, which of the following solutions will meet these requirements MOST cost-effectively?
Answer: B
Explanation:
The requirements explicitly identify two separate environments: a production ACK cluster using stable pay-as- you-go ECS capacity and a dedicated development cluster that is used only intermittently. Option D satisfies both requirements while preserving ACK-managed node-pool operations.
For the development cluster, preemptible instances-now generally described as spot instances in current Alibaba Cloud documentation-are appropriate because the workload is temporary, interruption-tolerant, and cost-sensitive. Alibaba Cloud states that spot capacity can reduce compute costs substantially compared with ordinary pay-as-you-go instances. ACK node pools can use spot instances and can automatically perform scaling and replacement operations.
The production cluster remains on pay-as-you-go nodes, avoiding the reclamation risk associated with spot capacity. A separate managed development cluster also preserves workload isolation.
Option A does not provide the required second development cluster and imposes subscription commitment.
Option B requires Eric to maintain an external Auto Scaling and bootstrap mechanism, contradicting the desire for ACK to manage nodes. Option C again describes only one cluster and fails to retain the required production environment.
Study Guide reference: Core Infrastructure Deep Dive - ACK managed clusters, node pools, spot
/preemptible ECS, and cloud cost optimization.
NEW QUESTION # 49
Keanu uses Elastic Compute Service (ECS) instances to run batch jobs to process data at 00:00 AM and 04:00 AM every day. An Auto Scaling group manages the ECS instances, which run as pay-as-you-go instances. If a batch job fails on one instance, another instance will reprocess the job.
Which of the following solutions provides the MOST cost-effective way to run these jobs?
Answer: B
Explanation:
The workload is an excellent candidate for preemptible, currently called spot, ECS capacity because it is short- lived, batch-oriented, horizontally scalable, and explicitly tolerant of interruption. The question states that if an instance fails, another instance can reprocess the job. That removes the main architectural objection to using interruptible compute.
Alibaba Cloud describes ECS spot instances as unused ECS capacity offered at substantially reduced prices compared with standard pay-as-you-go instances. The documented recommended scenarios include short- term tasks, data analytics, and applications that are highly fault tolerant and able to tolerate interruption.
Savings Plans and reserved-instance-style commitments can reduce costs for predictable long-term baseline consumption, but this workload runs only at two scheduled times each day. Purchasing committed capacity for a sporadic workload can leave paid capacity economically underutilized. Higher-specification pay-as-you- go instances also do not inherently minimize compute cost.
Using a launch template with preemptible/spot ECS instances allows Auto Scaling to add inexpensive compute when the batch workload requires it, while the application ' s retry mechanism handles interruptions.
Study Guide reference: Core Compute Infrastructure Deep Dive; Scalable Architecture on Alibaba Cloud; cost optimization for elastic compute.
NEW QUESTION # 50
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