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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Securing Workloads on Alibaba Cloud | 22% | - Data security and compliance best practices - Resource Access Management (RAM) and identity control - WAF, Anti-DDoS and network protection |
| Topic 2: Building Enterprise-grade Networks on Alibaba Cloud | 18% | - VPC design and configuration - Express Connect and VPN Gateway - Network routing and security groups |
| Topic 3: Delivering Services and Content on Alibaba Cloud | 12% | - CDN and content delivery strategies - Alibaba Cloud DNS and domain management - Service integration and access optimization |
| Topic 4: Core Infrastructure Deep Dive | 26% | - Elastic Compute Service (ECS) and serverless computing - File Storage NAS and block storage - Object Storage Service (OSS) and storage solutions |
| Topic 5: Building Highly Available, Performant Cloud Architecture | 22% | - Performance optimization and resilience design - Multi-zone deployment and disaster recovery - Auto Scaling and Server Load Balancer (SLB) |
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NEW QUESTION # 42
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: A
NEW QUESTION # 43
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: D
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 # 44
A company has a data ingestion workflow that consists of:
* An Alibaba Cloud Simple Message Queue topic for notifications about new data deliveries.
* An Alibaba Cloud Function Compute service to process the data and record metadata.
The company observes that the ingestion workflow fails occasionally because of network connectivity issues.
When such a failure occurs, the Function Compute instance does not ingest the corresponding data unless the company manually reruns the job.
Which combination of actions should a solutions architect take to ensure that the Function Compute instance ingests all data in the future? (Correct answers: 2)
Answer: D,E
Explanation:
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.
NEW QUESTION # 45
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: A,C
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 # 46
Lucy is a Cloud Architect at a new organization. They are creating a new application for their subscribers, which consists of a single static page and a persistent database layer. Based on the performance of their website, the application will experience traffic from millions of users for 4-6 hours in the morning, but only a few thousand for the rest of the day. Furthermore, the data engineers in the organization have requested that the app support rapid access to the database for their data warehouse requirements.
Which of the following solutions can meet these requirements while providing the MOST scalability?
(Correct answers: 2)
Answer: A,C
Explanation:
The workload has an extreme daily usage differential, making serverless PolarDB more appropriate than a fixed database configuration. PolarDB Serverless automatically scales compute resources up or out when CPU, memory, or database load increases and scales them down when demand subsides. This allows the database tier to accommodate millions of morning users without permanently paying for peak capacity throughout the remainder of the day.
The application front end is a single static page, so ECS instances are unnecessary. OSS can host HTML, CSS, JavaScript, images, and other static files directly. Placing Alibaba Cloud CDN in front of the OSS bucket caches those files at globally distributed edge nodes and serves requests from locations near users.
Alibaba Cloud recommends OSS + CDN for high-concurrency static websites because it reduces access latency and removes most origin load.
Option A can scale but retains fixed provisioned database resources and therefore provides less elasticity than the serverless model. Option D creates unnecessary compute infrastructure for content that requires no server- side execution.
The architecture therefore separates an infinitely scalable static delivery tier from an elastic serverless persistent database tier.
Study Guide reference: Building Highly Available, Performant Cloud Architecture - PolarDB Serverless, OSS static hosting, CDN, and automatic resource scaling.
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