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| Section | Objectives |
|---|---|
| Core Infrastructure Deep Dive | - Best Practices for Database Services - Core Storage Infrastructure Deep Dive - Core Compute Infrastructure Deep Dive |
| Securing Workloads on Alibaba Cloud | - Alibaba Cloud Security Deep Dive |
| Building Enterprise-grade Networks on Alibaba Cloud | - Cloud Networking Deep Dive |
| Building Highly Available, Performant Cloud Architecture | - Leveling up Your Core Infrastructure |
| Delivering Services and Content on Alibaba Cloud | - Delivering Services and Content on Alibaba Cloud |
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With each passing year, there's a slight change in the format of CAP-C01 exam. SurePassExams has put in a lot of effort in bringing to you the latest CAP-C01 questions, all by the current exam standards set by the Alibaba Cloud. All the Alibaba Cloud Certified Professional: Cloud Architect (CAP-C01) questions have been thoroughly checked to check their validity and to make sure we provide our candidates with the updated exam content.
NEW QUESTION # 48
An educational technology company is migrating its learning management system (LMS) to Alibaba Cloud.
The company mainly serves enterprise-grade customers, hence their platform must support automated backups, high availability across multiple zones, and granular access control for sensitive student records.
You have been hired as the lead Cloud Architect to build their architecture on Alibaba Cloud.
Which of the following architectural components will fit their requirements? (Correct answers: 3)
Answer: A,B,C
Explanation:
Each selected option maps directly to one of the stated enterprise requirements.
A multi-zone PolarDB deployment protects the database against availability-zone-level infrastructure failure.
Alibaba Cloud ' s multi-AZ PolarDB architecture keeps replicated data in separate zones and can use standby resources for failover when the primary zone becomes unavailable, resulting in a higher database SLA than a single-zone deployment.
Cloud Backup provides centralized policy-driven backup and recovery for Alibaba Cloud and on-premises resources, including ECS data, databases, NAS, OSS, and other supported workloads. This addresses the requirement for automated application and database protection without building custom backup infrastructure.
RAM roles and associated policies provide fine-grained authorization. RAM policies define allowed actions, affected resources, and optional access conditions, enabling least-privilege access to sensitive student data and administrative services.
Leaving OSS data unencrypted conflicts with the handling of sensitive enterprise information, while manual ACK scaling does not contribute to the stated requirement for high availability or automated operations.
The resulting architecture therefore combines multi-AZ database resilience, managed backup protection, and fine-grained identity authorization.
Study Guide reference: Securing Workloads on Alibaba Cloud - RAM; Building Highly Available, Performant Cloud Architecture - PolarDB HA and Cloud Backup.
NEW QUESTION # 49
A startup is building a serverless backend for their mobile application on Alibaba Cloud. The backend includes APIs for user authentication, data storage, and real-time notifications. The startup expects variable traffic with unpredictable spikes and wants to minimize costs by paying only for actual usage.
Which combination of Alibaba Cloud services should the startup use to achieve this architecture? (Correct answers: 2)
Answer: A,C
Explanation:
Function Compute and Simple Message Queue form an appropriate serverless, event-driven backend for bursty mobile workloads.
Function Compute is fully managed and automatically allocates elastic compute resources when functions are invoked. Alibaba Cloud bills Function Compute primarily according to actual configured resources and execution duration, allowing the startup to avoid maintaining continuously running application servers. This is particularly suitable for APIs and backend handlers experiencing unpredictable request spikes.
SMQ provides managed asynchronous messaging for decoupling backend components. It supports queue- based processing and publish-subscribe topics, making it suitable for notification events, background jobs, workflow messages, and traffic buffering. Alibaba Cloud explicitly identifies load leveling during sudden traffic spikes as an SMQ use case.
SMQ can also directly trigger Function Compute through queue or topic integrations, creating an event-driven design without dedicated message-consumer servers.
ECS requires persistent server resources and management, which conflicts with the requested serverless operating model. MaxCompute is a large-scale data warehouse and batch analytics platform rather than the application ' s transactional API or messaging layer.
Therefore, Function Compute supplies elastic execution while SMQ provides reliable asynchronous communication and notification-event handling.
Study Guide reference: Delivering Services and Content on Alibaba Cloud - Function Compute, serverless architectures, SMQ, event-driven integration, and elastic application services.
NEW QUESTION # 50
A company is designing an application. The application uses a Function Compute function to receive information through API Gateway and to store the information in an ApsaraDB RDS for PostgreSQL database.
During the proof-of-concept stage, the company noticed that the volume and velocity of data is very high, and they had to increase the Function Compute quotas significantly. Even with the increased quotas, they would sometimes lose data. The company has hired Javert, a Cloud Architect, to recommend a new design to improve scalability and minimize the configuration effort.
Which of the following solutions will meet these requirements?
Answer: D
Explanation:
The application needs asynchronous decoupling between high-volume ingestion and database writes. Simple Message Queue provides exactly this load-leveling pattern. The first Function Compute function can acknowledge incoming requests quickly and place each item into SMQ. A second function consumes the queued messages and writes them to RDS at a rate the database can sustain.
SMQ is a distributed managed messaging service specifically designed to decouple producers and consumers.
Alibaba Cloud identifies traffic-spike buffering, asynchronous processing, and independent component scaling as core SMQ use cases. Queue messages are delivered at least once during their validity period, significantly improving durability compared with directly coupling every incoming API request to a database write.
Function Compute also integrates directly with SMQ queues and topics as event sources, reducing custom integration and infrastructure management.
Kafka could also provide durable asynchronous messaging, but it is a more elaborate streaming platform than necessary for this workload and therefore carries additional configuration complexity. Moving to ECS reintroduces server administration, while replacing RDS does not solve the ingestion decoupling problem.
Study Guide reference: Core Infrastructure Deep Dive - Function Compute, messaging architectures, asynchronous processing, and scalable application integration.
NEW QUESTION # 51
An online education company plans to migrate their services to Alibaba Cloud. They want to improve their video streaming quality during peak hours using Alibaba Cloud services. As a Cloud Architect, you are tasked with building a solution to manage traffic spikes without compromising on video quality.
What combination of services would BEST fit their requirements? (Correct answers: 3)
Answer: B,C,D
Explanation:
CDN should form the content-delivery layer for cacheable video assets. Alibaba Cloud CDN distributes content to geographically dispersed edge nodes so viewers retrieve cached objects from nearby POPs rather than repeatedly connecting to a distant origin. Alibaba Cloud explicitly supports video-oriented CDN acceleration and edge delivery, reducing both end-user latency and origin bandwidth demand.
Auto Scaling addresses peak-time compute demand. It monitors workload conditions and automatically increases ECS capacity during traffic spikes, then scales resources back when traffic decreases. Alibaba Cloud specifically identifies streaming platforms with unpredictable demand as a typical Auto Scaling scenario.
Global Accelerator complements CDN and Auto Scaling where viewers or application endpoints are separated by long-distance or cross-border networks. GA routes traffic through Alibaba Cloud ' s optimized global BGP network, reducing latency, jitter, and packet loss. Alibaba documentation explicitly identifies video streaming as a latency-sensitive scenario that benefits from this architecture.
Tair can improve authentication or session performance, but it does not directly address video delivery quality or regional network performance. Therefore, CDN + Auto Scaling + Global Accelerator most directly satisfies the streaming requirement.
Study Guide reference: Delivering Services and Content on Alibaba Cloud - CDN, Global Accelerator, Auto Scaling, video delivery, and global traffic optimization.
NEW QUESTION # 52
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: A
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 # 53
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