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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Building Enterprise-grade Networks on Alibaba Cloud | 18% | - VPC design and configuration - Express Connect and VPN Gateway - Network routing and security groups |
| Topic 2: 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 3: 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) |
| Topic 4: Securing Workloads on Alibaba Cloud | 22% | - Resource Access Management (RAM) and identity control - WAF, Anti-DDoS and network protection - Data security and compliance best practices |
| Topic 5: Delivering Services and Content on Alibaba Cloud | 12% | - CDN and content delivery strategies - Service integration and access optimization - Alibaba Cloud DNS and domain management |
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NEW QUESTION # 29
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: C
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 # 30
A worldwide retail company is adapting their e-commerce platform to handle spikes in online traffic during annual sales events. They are using Alibaba Cloud services and need a solution that can automatically scale resources to maintain performance during these peaks.
What solutions should the company implement to efficiently manage their resources during high-traffic periods? (Correct answers: 3)
Answer: B,C,D
Explanation:
The strongest architecture for an existing e-commerce platform experiencing predictable but substantial traffic spikes is OSS/CDN + ALB + Auto Scaling. Auto Scaling is specifically designed to increase ECS capacity when traffic or resource utilization rises and remove unnecessary instances after demand subsides. Alibaba Cloud documents this as a core mechanism for handling traffic spikes while avoiding permanent over- provisioning.
ALB complements Auto Scaling by distributing requests across healthy ECS backend instances. As scaling creates additional instances, they can be automatically added to the ALB server group, allowing traffic to use the enlarged compute pool immediately.
Static images and videos should be moved to OSS and accelerated through CDN. CDN caches static resources on geographically distributed edge nodes, substantially reducing requests reaching the ECS application tier and lowering origin bandwidth and processing load during sales events.
Function Compute is highly elastic, but introducing it merely to supplement an existing server-based application normally requires application restructuring. It is therefore less directly applicable than the three mechanisms specifically designed to scale and offload the existing architecture.
Study Guide reference: Building Highly Available, Performant Cloud Architecture - Auto Scaling, ALB, CDN offloading, and elastic ECS architecture.
NEW QUESTION # 31
An e-commerce company needs to execute a daily scheduled job to aggregate and filter sales records stored in an Alibaba Cloud OSS bucket. Each object can be up to 10 GB in size. The task may take up to an hour to run with pre-determined CPU and memory requirements. The goal is to reduce operational management efforts.
Identify an appropriate architecture using Alibaba Cloud services to perform the scheduled job efficiently.
Answer: D
Explanation:
Function Compute with EventBridge provides the lowest-management architecture among the choices.
Function Compute is a fully managed, event-driven compute platform: Alibaba Cloud provisions and scales the required execution infrastructure automatically, and billing is based on configured resources and execution duration. This removes the operational burden of maintaining ECS instances or an ACK cluster.
The stated execution time of up to one hour is supported. Current Function Compute documentation permits individual function executions of up to 24 hours, so the job duration does not require a container cluster merely because it exceeds traditional short-function runtimes.
EventBridge supports recurring time-triggered events using fixed schedules or cron expressions and is suitable for scheduled batch-processing workflows. Function Compute also integrates directly with EventBridge-based cloud-product event triggers.
Options A and C introduce Kubernetes control and workload-management complexity that is unnecessary for a single scheduled processing job. Option B is less precise because Serverless Workflow provides orchestration rather than being required to perform the actual computation.
Therefore, EventBridge schedules the daily invocation and Function Compute performs the OSS-backed processing without persistent infrastructure.
Study Guide reference: Delivering Services on Alibaba Cloud; serverless architecture and event-driven application delivery.
NEW QUESTION # 32
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: B
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 # 33
A startup is building a serverless backend for their mobile application on Alibaba Cloud. The backend includes APIs for user authentication, data storage, and real-time notifications. The startup expects variable traffic with unpredictable spikes and wants to minimize costs by paying only for actual usage.
Which combination of Alibaba Cloud services should the startup use to achieve this architecture? (Correct answers: 2)
Answer: B,D
Explanation:
Function Compute and Simple Message Queue form an appropriate serverless, event-driven backend for bursty mobile workloads.
Function Compute is fully managed and automatically allocates elastic compute resources when functions are invoked. Alibaba Cloud bills Function Compute primarily according to actual configured resources and execution duration, allowing the startup to avoid maintaining continuously running application servers. This is particularly suitable for APIs and backend handlers experiencing unpredictable request spikes.
SMQ provides managed asynchronous messaging for decoupling backend components. It supports queue- based processing and publish-subscribe topics, making it suitable for notification events, background jobs, workflow messages, and traffic buffering. Alibaba Cloud explicitly identifies load leveling during sudden traffic spikes as an SMQ use case.
SMQ can also directly trigger Function Compute through queue or topic integrations, creating an event-driven design without dedicated message-consumer servers.
ECS requires persistent server resources and management, which conflicts with the requested serverless operating model. MaxCompute is a large-scale data warehouse and batch analytics platform rather than the application ' s transactional API or messaging layer.
Therefore, Function Compute supplies elastic execution while SMQ provides reliable asynchronous communication and notification-event handling.
Study Guide reference: Delivering Services and Content on Alibaba Cloud - Function Compute, serverless architectures, SMQ, event-driven integration, and elastic application services.
NEW QUESTION # 34
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