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Alibaba Cloud CAP-C01 Exam Syllabus Topics:

SectionObjectives
Topic 1: Building Highly Available, Performant Cloud Architecture- Leveling up Your Core Infrastructure
Topic 2: Core Infrastructure Deep Dive- Core Compute Infrastructure Deep Dive
- Core Storage Infrastructure Deep Dive
- Best Practices for Database Services
Topic 3: Building Enterprise-grade Networks on Alibaba Cloud- Cloud Networking Deep Dive
Topic 4: Delivering Services and Content on Alibaba Cloud- Delivering Services and Content on Alibaba Cloud
Topic 5: Securing Workloads on Alibaba Cloud- Alibaba Cloud Security Deep Dive

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Alibaba Cloud Certified Professional: Cloud Architect Sample Questions (Q27-Q32):

NEW QUESTION # 27
Clash for Victory is a popular online game that is hosted on Alibaba Cloud. As latency can have a huge impact on gameplay, the developers for the game want to implement a mechanism to route all requests to the closest access point, monitor the health of the game, and redirect traffic to healthy backend servers.
The game is deployed in multiple regions on Elastic Compute Service (ECS) instances that are part of Auto Scaling groups configured behind Application Load Balancers (ALBs).
As a Cloud Architect, what course of action would you take?

Answer: C

Explanation:
Global Accelerator is designed for precisely this class of global interactive application. Clients connect through Alibaba Cloud ' s nearby acceleration access points, after which traffic traverses Alibaba Cloud ' s optimized global network toward the most appropriate backend region. This reduces Internet routing variability and improves end-to-end latency for latency-sensitive workloads such as gaming.
GA listeners define the application protocol and ports, while endpoint groups represent backend deployments in different regions. With intelligent routing, GA can select a nearby healthy endpoint group and forward requests accordingly. Alibaba Cloud also provides endpoint health checks; when an endpoint becomes unhealthy, new requests can automatically be directed to healthy endpoints.
CDN is highly effective for static cacheable content but is not the correct primary mechanism for arbitrary real-time game traffic and regional backend health-based routing. RDS and Tair improve application data performance but do not solve global network acceleration.
Therefore, GA in front of regional ALBs provides the correct architecture: nearest-entry acceleration, Alibaba Cloud backbone transport, regional endpoint groups, health monitoring, and failover.
Study Guide reference: Delivering Services and Content on Alibaba Cloud - Global Accelerator, ALB, multi-region traffic management, and high availability.


NEW QUESTION # 28
A retail chain is utilizing Alibaba Cloud ' s PolarDB to manage its inventory and sales databases. They need to ensure that their SQL queries have minimal impact on their production workload while enabling data analysts to run complex analytical queries.
How can the retail chain optimize their database operations for both transactional and analytical workloads?
(Correct answers: 2)

Answer: B,D

Explanation:
Option B reduces interference between transaction processing and read-heavy workloads inside PolarDB.
PolarDB ' s read/write splitting automatically routes writes to the primary node while distributing eligible reads across read-only nodes. This allows reporting and ordinary SELECT traffic to consume separate compute capacity instead of competing with critical transactional writes on the primary node. Alibaba Cloud specifically identifies reporting, analytics, and read-heavy applications as appropriate read/write-splitting scenarios.
Option D provides stronger isolation for computationally expensive analytics. DTS can continuously synchronize PolarDB for MySQL data into MaxCompute using initial full synchronization followed by ongoing incremental change capture. Analysts can then execute large-scale analytical workloads against MaxCompute without placing those queries on the production transactional database.
Running queries on ECS does not inherently remove load from PolarDB because the SQL operations would still execute against the database. Introducing MongoDB merely to execute analytical queries creates a second database technology without an appropriate replication or analytical architecture.
Together, PolarDB read/write splitting optimizes operational read traffic while DTS-to-MaxCompute isolates heavyweight analytical processing, producing an effective HTAP-style separation of concerns.
Study Guide reference: Core Infrastructure Deep Dive - PolarDB, read/write splitting, DTS, MaxCompute, and analytical workload offloading.


NEW QUESTION # 29
Paul runs a successful online game. The game is deployed as a three-tier architecture in a VPC with ApsaraDB RDS for MySQL at the database layer. The game allows players to compete in real-time, and Paul wants to display a top-10 scoreboard in near-real time.
As a Cloud Architect, which of the following solutions would you propose for Paul ' s use case?

Answer: C

Explanation:
Tair is the appropriate architecture for a frequently changing game leaderboard because Redis-compatible sorted data structures are optimized for high-throughput score updates and ranking operations. Instead of repeatedly executing expensive aggregation and sorting queries against the relational database, the application can maintain player scores in Tair and retrieve the highest-ranked members directly.
Alibaba Cloud specifically documents leaderboard implementations based on Tair ' s sorted-set capabilities.
Tair ' s enhanced exZset functionality supports scalable ranking use cases and can distribute large leaderboards across multiple internal structures while preserving rank calculation.
This also protects RDS from high-frequency scoreboard queries. RDS remains the durable transactional database, while Tair operates as the low-latency serving and ranking layer for frequently accessed score data.
CDN caching is unsuitable because the leaderboard changes continually and requires near-real-time freshness.
A second relational PostgreSQL database would duplicate database infrastructure without providing the specialized in-memory ranking semantics required. An RDS read replica can reduce pressure on the primary database, but calculating and sorting rankings through SQL for every refresh remains less efficient than maintaining rankings directly in an in-memory sorted structure.
Study Guide reference: Building Highly Available, Performant Cloud Architecture - Tair, caching, low- latency architectures, and database performance optimization.


NEW QUESTION # 30
A telecommunications company is expanding its backend architecture on Alibaba Cloud to add new services but needs to consolidate security management. They use multiple VPCs and want to streamline authorization management across their services.
What strategy should they adopt to simplify security group management across VPCs?

Answer: C


NEW QUESTION # 31
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: C

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 # 32
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