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| Section | Weight | Objectives |
|---|---|---|
| Securing Workloads on Alibaba Cloud | 22% | - Alibaba Cloud Security Deep Dive
|
| Delivering Services and Content on Alibaba Cloud | 12% | - Delivering Services and Content on Alibaba Cloud
|
| Building Highly Available, Performant Cloud Architecture | 22% | - Leveling up Your Core Infrastructure
|
| Core Infrastructure Deep Dive | 26% | - Core Compute Infrastructure Deep Dive
|
| Building Enterprise-grade Networks on Alibaba Cloud | 18% | - Cloud Networking Deep Dive
|
>> CAP-C01 Zertifizierungsprüfung <<
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48. Frage
Clarence runs a technology services company that uses ApsaraDB RDS. The company wants to streamline their database management and set up a robust access control structure.
Which of the following solutions provides the required functionality with the LEAST operational overhead?
Antwort: D
Begründung:
Data Management Service is specifically designed to centralize database administration, authorization, and governance. Its permission model provides fine-grained control over instances, databases, tables, columns, rows, and sensitive data. Administrators can control logon, query, export, and change privileges while maintaining centralized governance rather than manually coordinating several independent services.
DMS is also appropriate where the organization needs auditable database access. Alibaba Cloud explicitly describes DMS authorization scenarios that include controlling RDS access and auditing employee data access.
RAM controls permissions to Alibaba Cloud resources and APIs, but combining RAM with ActionTrail would require multiple mechanisms and would not provide DMS ' s database-object-level permission model.
An RDS IP whitelist is useful as a network access restriction but cannot express granular user permissions or provide centralized database governance. WAF protects HTTP/HTTPS applications and is not the appropriate control plane for direct RDS database authorization.
DMS therefore provides the required access control and audit functionality with the lowest operational complexity by consolidating database security administration into a purpose-built managed service.
Study Guide reference: Securing Workloads on Alibaba Cloud - DMS access control, database governance, RDS security, and auditing.
49. Frage
Muthu is a Cloud Architect who is designing the architecture of a new application being deployed to Alibaba Cloud. The application will run on Elastic Compute Service (ECS) pay-as-you-go instances and will automatically scale across multiple zones based on load. The ECS cluster will scale in and out frequently throughout the day. An Application Load Balancer (ALB) will handle the load distribution. The architecture needs to support distributed session data management.
What should Muthu do to ensure that the architecture supports distributed session data management?
Antwort: A
Begründung:
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.
50. Frage
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?
Antwort: A
Begründung:
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.
51. Frage
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)
Antwort: A,C
Begründung:
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.
52. Frage
Ibrahim manages a large-scale manufacturing plant equipped with state-of-the-art instrumentation and telemetry that collects various information about the machines and products. These sensors collectively generate 1 TB worth of logs each day. Each notification is approximately 2 KB in size. You have been contracted to design a solution to ingest and store these logs for future analysis.
Ibrahim wants a highly available solution, but also wants to minimize costs. Additionally, he does not want to manage additional infrastructure. To meet their business requirements, they need to keep 14 days of data available for immediate analysis, and archive any other data older than 14 days.
What is the MOST operationally efficient solution that meets these requirements?
Antwort: A
Begründung:
Simple Log Service (SLS) is a managed log-ingestion, storage, query, analysis, and visualization service, making it the most operationally efficient front-end for this telemetry workload. It eliminates the requirement to provision and manage ECS-based collectors or a separate search cluster simply to ingest and analyze log records.
For longer-term retention, Alibaba Cloud supports automatically shipping SLS data to OSS. This creates a clean hot-to-cold architecture: maintain recent data in SLS for interactive analysis and export older data to OSS for economical retention.
OSS lifecycle management can then automatically transition aging objects to lower-cost storage classes such as Archive. Lifecycle rules are explicitly designed to automate storage-class transitions based on object age, eliminating manual archival administration.
Option A requires additional Elasticsearch retention administration. Option B requires managing ECS infrastructure even though the question explicitly prioritizes reduced operational management. Option D adds Kafka unnecessarily and still specifies manual archival, directly conflicting with the requirement to minimize operational effort.
Thus, SLS for managed ingestion and recent analysis combined with SLS-to-OSS shipping and OSS lifecycle transitions provides the strongest serverless/managed retention architecture.
Study Guide reference: Core Infrastructure Deep Dive; Core Storage Infrastructure; operationally efficient log and data-storage architecture.
53. Frage
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