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| Section | Objectives |
|---|---|
| Topic 1: Securing Workloads on Alibaba Cloud | - Alibaba Cloud Security Deep Dive |
| Topic 2: Building Enterprise-grade Networks on Alibaba Cloud | - Cloud Networking Deep Dive |
| Topic 3: Building Highly Available, Performant Cloud Architecture | - Leveling up Your Core Infrastructure |
| Topic 4: Delivering Services and Content on Alibaba Cloud | - Delivering Services and Content on Alibaba Cloud |
| Topic 5: Core Infrastructure Deep Dive | - Core Compute Infrastructure Deep Dive - Core Storage Infrastructure Deep Dive - Best Practices for Database Services |
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NEW QUESTION # 22
A global consultancy firm needs to ensure that their applications hosted on Alibaba Cloud have low latency for users distributed worldwide. They require a solution that can cache static content and dynamically route user requests to the nearest point-of-presence (PoP).
Which Alibaba Cloud service should the firm implement to achieve this?
Answer: B
Explanation:
Alibaba Cloud CDN is specifically designed to accelerate content delivery by distributing and caching content at geographically distributed points of presence. When a user requests an accelerated resource, CDN DNS scheduling assigns an appropriate PoP. If the resource is cached there, the PoP returns it directly without requiring a round trip to the origin infrastructure. Alibaba Cloud documentation explicitly states that static resources are cached on the nearest PoP to reduce latency and improve access efficiency.
This directly satisfies both key requirements in the question: caching static content and directing users toward edge infrastructure close to their locations. If content is not cached or has expired, the CDN PoP performs an origin fetch and then serves the resource.
GTM can perform DNS-based geographical or latency routing among application endpoints and regions, but it is not itself a distributed static-content caching service. Express Connect provides private dedicated connectivity between enterprise/on-premises networks and Alibaba Cloud. SLB distributes traffic among backend servers but does not provide a worldwide edge caching network.
Therefore, Alibaba Cloud CDN is the only listed service that simultaneously implements PoP-based edge delivery and static-content caching.
Study Guide reference: Delivering Content on Alibaba Cloud; content acceleration and global application- delivery architecture.
NEW QUESTION # 23
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,B,C
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 # 24
Keanu uses Elastic Compute Service (ECS) instances to run batch jobs to process data at 00:00 AM and 04:00 AM every day. An Auto Scaling group manages the ECS instances, which run as pay-as-you-go instances. If a batch job fails on one instance, another instance will reprocess the job.
Which of the following solutions provides the MOST cost-effective way to run these jobs?
Answer: D
Explanation:
The workload is an excellent candidate for preemptible, currently called spot, ECS capacity because it is short- lived, batch-oriented, horizontally scalable, and explicitly tolerant of interruption. The question states that if an instance fails, another instance can reprocess the job. That removes the main architectural objection to using interruptible compute.
Alibaba Cloud describes ECS spot instances as unused ECS capacity offered at substantially reduced prices compared with standard pay-as-you-go instances. The documented recommended scenarios include short- term tasks, data analytics, and applications that are highly fault tolerant and able to tolerate interruption.
Savings Plans and reserved-instance-style commitments can reduce costs for predictable long-term baseline consumption, but this workload runs only at two scheduled times each day. Purchasing committed capacity for a sporadic workload can leave paid capacity economically underutilized. Higher-specification pay-as-you- go instances also do not inherently minimize compute cost.
Using a launch template with preemptible/spot ECS instances allows Auto Scaling to add inexpensive compute when the batch workload requires it, while the application ' s retry mechanism handles interruptions.
Study Guide reference: Core Compute Infrastructure Deep Dive; Scalable Architecture on Alibaba Cloud; cost optimization for elastic compute.
NEW QUESTION # 25
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?
Answer: C
Explanation:
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.
NEW QUESTION # 26
Sandra hosts a web application on a single ECS instance that stores documents uploaded by users in an EBS data disk. As the requirements grow, they duplicate the application and host it in a second ECS instance in a different zone. An ALB instance is used to distribute traffic between these ECS instances. However, after completing this change, users reported that every time they access the web application, they could only see some of their documents at any given time, but never all of the documents at the same time.
As a Cloud Architect, how would you solve this issue?
Answer: C
Explanation:
The architectural defect is that application state is stored independently on local block storage attached to each ECS instance. ALB can route successive requests to either backend, so each server exposes only the files stored on its own EBS disk. The correct solution is therefore to separate persistent shared data from individual compute instances.
Alibaba Cloud File Storage NAS provides shared file storage that can be mounted concurrently by multiple ECS instances. A single NAS file system becomes the authoritative repository for uploaded documents, so regardless of which ECS instance receives a request, both instances access the same underlying dataset.
Alibaba Cloud explicitly supports mounting NAS on multiple ECS instances for shared access.
Periodic EBS synchronization is operationally fragile and introduces consistency windows. ALB session persistence would merely hide the architectural problem and would fail when an ECS instance becomes unavailable or is replaced. Sending every request to both servers would also complicate application logic and still leave divergent storage.
Moving the data to NAS converts the application tier into a horizontally scalable compute layer while maintaining one consistent shared filesystem.
Study Guide reference: Core Infrastructure Deep Dive - ECS storage patterns, File Storage NAS, shared storage, and stateless application architecture.
NEW QUESTION # 27
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