Alibaba Cloud CAP-C01 Dumps Questions Answers

Alibaba Cloud CDN addresses the front-end performance problem by caching static resources at edge Points of Presence close to users. Instead of every image, JavaScript file, stylesheet, or other cacheable object being retrieved from the origin application, CDN returns cached copies from nearby edge nodes. This reduces network latency and decreases load on the original application servers. Alibaba Cloud specifically identifies reduced latency and lower origin workload as primary benefits of CDN.

Read/write splitting addresses database-side pressure. ApsaraDB RDS for MySQL can use database proxy functionality to direct write operations to the primary instance and distribute eligible read operations to read-only instances. This is especially effective for read-heavy web applications because it reduces CPU and I/O load on the primary database and increases aggregate read throughput.

A multi-zone database improves availability rather than directly solving page-load latency. AnalyticDB is an analytical database and should not replace RDS simply to handle transactional data. OSS is optimized for static objects; hosting dynamic application content there does not fit its object-storage model.

Study Guide reference: Building Highly Available, Performant Cloud Architecture — CDN acceleration, RDS read scaling, database proxies, and application performance optimization.

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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.

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The core problem is durability during transient processing or network failures. A topic provides publish/subscribe notification delivery, but placing an SMQ queue behind the topic creates a persistent buffer between the notification producer and the Function Compute consumer. Alibaba Cloud supports subscribing a queue to an SMQ topic so that every message published to the topic is copied into the queue and retained for consumption.

Function Compute should then process records from the queue. Queue semantics provide the required failure recovery: after a consumer receives a message, it becomes temporarily invisible. The consumer deletes the message only after successful processing. If processing fails—for example because of a temporary connectivity problem—the message is not deleted and becomes visible again after the visibility timeout, allowing another processing attempt.

Function Compute also supports SMQ queue triggers with configurable retries, fault-tolerance behavior, and dead-letter handling, which can further strengthen this architecture.

Increasing memory does not fix network reliability, and multi-region deployment alone does not guarantee message persistence. A durable queue therefore prevents transient failures from silently losing ingestion work.

Study Guide reference: Core Infrastructure Deep Dive — Simple Message Queue, Function Compute, durable asynchronous processing, retries, and decoupled event-driven architecture.