Practice Free CAP-C01 Alibaba Cloud Certified Professional: Cloud Architect Exam Questions Answers With Explanation

Simple Log Service (SLS) is the appropriate logging platform for an ACK Serverless environment. Serverless Kubernetes removes much of the node-management responsibility, so the logging architecture should follow the same managed-service model rather than introduce dedicated log-processing infrastructure.

Alibaba Cloud provides native SLS integration for ACK Serverless. SLS can collect container standard output and application log files and then provide centralized search, analysis, dashboards, alerting, and downstream shipping. Alibaba documentation specifically states that ACK Serverless provides managed SLS capabilities and supports collecting container logs directly into SLS.

ARMS is primarily an application performance monitoring and observability platform; it does not replace SLS as the core centralized log-ingestion service. Option C is incorrect because SLS supports near-real-time collection and analysis. Option D also misunderstands serverless logging: scaling events do not inherently require dedicated logging servers.

The architecture should therefore preserve the operational advantages of serverless compute by using SLS as a fully managed, elastic logging layer capable of handling workload fluctuations without requiring the organization to provision and administer separate logging infrastructure.

Study Guide reference: Core Infrastructure Deep Dive — ACK, serverless container architecture, observability, and Simple Log Service.

Global Database Network is the architecture specifically intended for geographically distributed PolarDB deployments requiring cross-region data replication, local read capability, and disaster recovery. A GDN contains a primary cluster plus secondary clusters in other regions. Data is continuously synchronized between them. Applications can connect to regional cluster endpoints; read requests can be served locally while write requests are routed to the primary cluster. Alibaba Cloud also supports switching the primary cluster to a secondary cluster, including forced switchover scenarios for failures.

Option C provides strong node-level and zone-level availability within a PolarDB cluster, but it does not deliver the same level of protection against an entire regional outage. Option D relies on backup restoration, which introduces significantly higher RTO and operational intervention. Option B invents an unnecessary Function Compute replication mechanism instead of using PolarDB ' s native cross-region replication.

For a mission-critical global e-commerce database, GDN provides the best combination of cross-region redundancy, replication, local reads, and regional failover capabilities.

Study Guide reference: Building Highly Available, Performant Cloud Architecture — PolarDB high availability, cross-region disaster recovery, and Global Database Network.

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.

Tair (Redis OSS-Compatible) is the appropriate centralized session-state layer for an elastic, distributed application. When ECS instances frequently scale in and out, application sessions must not depend on the lifecycle of any individual compute node. By storing session tokens and session state in Tair, every ECS instance can retrieve the same session information, making the web/application tier effectively stateless and compatible with Auto Scaling.

Alibaba Cloud Tair is a fully managed Redis-compatible database designed for high throughput, low latency, elastic scalability, and high availability. Alibaba Cloud also documents session-oriented Tair use cases in which session tokens are stored as Redis/Tair data structures with TTL values, demonstrating precisely why the service fits distributed session management.

Session stickiness is weaker because it attempts to keep a user on a specific backend and therefore creates affinity to an instance that might be removed during scaling or failover. CloudMonitor is an observability service, not a session store. STS issues temporary Alibaba Cloud credentials and does not maintain application user sessions.

Consequently, separating session state from ECS compute by storing it in Tair gives the architecture the elasticity and fault tolerance required.

Study Guide reference: Distributed Architecture on Alibaba Cloud; Performant Architecture; Core Infrastructure Deep Dive.

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OSS, E-MapReduce, and MaxCompute collectively provide the strongest large-scale analytics architecture among the listed services.

OSS supplies the scalable data-lake storage layer. Alibaba Cloud describes OSS-based data lakes as capable of retaining structured, semi-structured, and unstructured datasets at very large scale while decoupling storage capacity from compute resources. OSS storage can scale independently into exabyte-scale environments.

E-MapReduce provides managed big-data processing based on ecosystems such as Hadoop and Spark and integrates directly with OSS. EMR DataLake configurations support Spark and Hive for batch workloads and Presto/Trino for interactive SQL analysis, making EMR highly appropriate for workloads requiring both scheduled processing and ad-hoc querying.

MaxCompute supplies a massively scalable managed data-warehouse and analytical processing layer. Alibaba Cloud also supports architectures where MaxCompute processes structured analytical datasets while OSS provides the underlying flexible data-lake storage.

PolarDB is an operational relational database and is not intended to act as the primary petabyte-scale data-lake processing platform. Elasticsearch is valuable for search and log analytics but does not replace the combination of OSS, EMR, and MaxCompute for generalized big-data processing.

Study Guide reference: Core Infrastructure Deep Dive — OSS data lakes, EMR, MaxCompute, distributed analytics, batch processing, and interactive query architectures.

The threats described exist at different layers, so the architecture should apply layered protection. WAF is the correct control for public HTTP/API traffic because it analyzes application-layer requests and blocks threats such as SQL injection, cross-site scripting, command injection, brute-force attacks, and other OWASP-style attacks. Alibaba Cloud explicitly supports integrating WAF with API Gateway and recommends disabling direct access paths afterward so clients cannot bypass WAF.

Large DDoS attacks require a dedicated volumetric mitigation service. Anti-DDoS Proxy scrubs malicious network and transport-layer traffic before clean traffic is forwarded toward the application infrastructure. Alibaba Cloud ' s Anti-DDoS architecture supports protected services behind Server Load Balancer resources and provides port-forwarding mechanisms for non-HTTP workloads.

Alibaba Cloud specifically recommends combining Anti-DDoS and WAF when an application needs protection against both large volumetric attacks and sophisticated application-layer exploits.

WAF should protect the HTTP/API application boundary rather than being treated as a general Layer-4 NLB firewall. Security Center provides workload security and posture management, while basic DDoS protection alone is less suitable for the question ' s explicitly stated large and sophisticated attacks.

Study Guide reference: Securing Workloads on Alibaba Cloud — WAF, Anti-DDoS, API Gateway security, and defense-in-depth.

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The existing architecture has two important bottlenecks: a single ECS compute node and files stored on storage attached to that individual ECS instance. Option E eliminates the compute single point of failure. A custom image allows identical ECS instances to be created, while Auto Scaling maintains multiple instances and ALB distributes requests across healthy backends. This provides horizontal scalability and significantly stronger application availability.

Option D addresses shared application storage. File Storage NAS is a managed, POSIX-compatible shared filesystem that multiple ECS instances can mount concurrently. All web servers therefore see the same files, while NAS handles storage scalability and consistency independently from the ECS lifecycle.

Option A improves performance by moving cacheable website content toward users. CDN serves static resources from nearby POPs and reduces requests and bandwidth reaching the origin infrastructure.

Although OSS is excellent for native object-storage workloads, mounting OSS through ossfs does not provide the same filesystem semantics and consistency characteristics as NAS for a traditional application requiring minimal modification. Global Accelerator primarily optimizes network paths and does not eliminate the application ' s compute or storage single points of failure.

Study Guide reference: Building Highly Available, Performant Cloud Architecture — ALB, Auto Scaling, NAS shared storage, and CDN.

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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.

Option B provides the simplest consolidated content-delivery architecture. Alibaba Cloud CDN can use multiple origins, and current CDN functionality supports origin-selection rules based on parameters such as request path, headers, query strings, and cookies. This allows static requests to be associated with an OSS origin while application requests are forwarded toward the ALB-backed application tier.

Static objects stored in OSS benefit directly from CDN edge caching. Requests are routed to nearby CDN points of presence, and cached resources can be returned without repeatedly accessing the OSS origin, reducing both latency and origin load.

Dynamic responses are generally not cached because they are generated uniquely for requests. They can still be routed to the application origin according to the configured origin rules.

The Global Accelerator alternatives create an unnecessarily fragmented architecture and attempt to use separate acceleration paths where one CDN-facing domain and origin-routing configuration can satisfy the question with fewer components. They also introduce additional DNS and acceleration configuration.

Therefore, a single CDN delivery layer with OSS and ALB-backed origins, combined with Alibaba Cloud DNS directing the application domain to CDN, produces the lowest configuration overhead.

Study Guide reference: Delivering Services and Content on Alibaba Cloud — CDN, OSS acceleration, ALB origins, and intelligent content delivery.

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ROS Stack Groups are specifically designed for centrally deploying a common Resource Orchestration Service template across multiple Alibaba Cloud accounts and regions. This makes option D the architecture that directly addresses both dimensions of the requirement: multi-account governance and multi-region infrastructure-as-code deployment.

Alibaba Cloud documentation states that stack instances belonging to a stack group can deploy stacks into destination accounts and different regions. With Resource Directory integration and service-managed permissions, trusted access can be enabled so that stack groups are operated by a management account or delegated administrator while deployments occur in organization member accounts.

Nested stacks are primarily a template-composition mechanism; they do not constitute centralized multi-account deployment orchestration. Manually combining ordinary ROS templates and RAM policies could technically enable cross-account operations, but it recreates functionality that Stack Groups provide natively and increases operational overhead. Resource Directory and Cloud Governance alone also do not replace the actual multi-account, multi-region stack deployment mechanism.

Therefore, Resource Directory establishes the organizational account structure while ROS Stack Groups provide repeatable infrastructure deployment across those accounts and target regions.

Study Guide reference: Core Infrastructure Deep Dive; Resource Orchestration Service, multi-account governance, and repeatable cloud architecture.

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