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| Section | Objectives |
|---|---|
| Securing Workloads on Alibaba Cloud | - Alibaba Cloud Security Deep Dive |
| Core Infrastructure Deep Dive | - Best Practices for Database Services - Core Compute Infrastructure Deep Dive - Core Storage Infrastructure Deep Dive |
| Building Enterprise-grade Networks on Alibaba Cloud | - Cloud Networking Deep Dive |
| Delivering Services and Content on Alibaba Cloud | - Delivering Services and Content on Alibaba Cloud |
| Building Highly Available, Performant Cloud Architecture | - Leveling up Your Core Infrastructure |
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NEW QUESTION # 18
A company runs its cloud infrastructure on Alibaba Cloud. Jose, a Cloud Architect for the company, needs to define the infrastructure as code. Currently, the infrastructure is deployed in a single Alibaba Cloud region.
The company ' s business expansion plan includes deployments across multiple regions and multiple Alibaba Cloud accounts.
What should Jose do to meet these requirements?
Answer: A
Explanation:
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.
NEW QUESTION # 19
A global hotel chain is migrating its reservation system to Alibaba Cloud. The system must provide high availability across multiple regions, ensure data consistency, and support real-time updates to prevent double bookings. Additionally, the system should integrate with third-party payment gateways securely.
Which combination of Alibaba Cloud services should the hotel chain implement to architect this reservation system effectively? (Correct answers: 3)
Answer: A,B,C
Explanation:
Option A refers to PolarDB Global Database Network (GDN), Alibaba Cloud ' s architecture for connecting PolarDB clusters across regions. A GDN contains a primary cluster and secondary regional clusters. Data changes are continuously replicated, local reads can be served by regional clusters, and write operations are routed to the primary cluster. Maintaining a single authoritative write path is particularly important for reservation transactions where concurrent booking operations must be controlled consistently.
Option C provides resilient application capacity by deploying ECS application servers in multiple regions and using ALB within each regional deployment to distribute requests among healthy instances. In a complete production implementation, a global routing mechanism such as DNS traffic management or Global Accelerator would normally direct users between those regional application stacks.
Function Compute is suitable for payment-gateway integrations because payment callbacks and API interactions are event-driven or request-driven workloads. Function Compute can be exposed securely through API Gateway, which provides routing, authentication, traffic control, and API management without persistent integration servers.
OSS versioning is useful for protecting stored objects but does not supply the transactional database, regional application availability, or payment-processing functionality required here.
Study Guide reference: Building Highly Available, Performant Cloud Architecture - multi-region PolarDB, GDN, regional application tiers, ALB, and serverless integration.
NEW QUESTION # 20
Kenneth plans to deploy a real-time data processing platform on Alibaba Cloud to support his company ' s Internet-of-Things (IoT) business. The platform will handle millions of sensor data points collected from smart devices globally. Kenneth needs to ensure high throughput and low latency for data ingestion and analysis.
Which solutions should Kenneth consider integrating into the platform architecture to meet his expected performance requirements? (Correct answers: 3)
Answer: A,C,D
Explanation:
Time Series Database is specifically designed for timestamped telemetry generated by IoT devices, monitoring systems, and industrial equipment. Alibaba Cloud identifies IoT device monitoring as a core TSDB scenario, including continuously collecting, storing, analyzing, and querying device-status and business-event data in real time.
ApsaraMQ for Kafka provides the high-throughput ingestion and buffering layer. It is a managed distributed Kafka platform intended for real-time data pipelines, monitoring-data aggregation, log collection, streaming processing, and large-scale analytics. Its partitioned distributed architecture lets producers ingest very large event volumes while downstream consumers process the streams independently.
Function Compute supplies elastic event processing without persistent compute servers. Alibaba Cloud supports ApsaraMQ for Kafka triggers that invoke Function Compute automatically whenever new records arrive in Kafka topics. This enables functions to perform transformations, filtering, enrichment, alert generation, or routing in near real time.
EMR is valuable for Hadoop/Spark-style batch analytics, but the question specifically emphasizes low-latency real-time ingestion and analysis. It therefore does not replace the streaming components selected above.
Study Guide reference: Core Infrastructure Deep Dive - IoT telemetry, TSDB, ApsaraMQ for Kafka, Function Compute, and real-time streaming architectures.
NEW QUESTION # 21
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 # 22
A company is building a big data analytics platform on Alibaba Cloud to process and analyze petabytes of data. They require a highly scalable storage solution that can handle both structured and unstructured data, and a processing framework that supports batch and interactive queries.
Which combination of Alibaba Cloud services should the company use to build this platform? (Correct answers: 3)
Answer: A,C,E
Explanation:
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.
NEW QUESTION # 23
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