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Quiz
Question 1/101/10
Elastic Compute Service (ECS)
Elastic Compute Service (ECS)
Elastic Compute Service (ECS)
A company is deploying an in-memory caching cluster similar to Redis that requires a memory-to-vCPU ratio of approximately 8 GiB per vCPU and consistent memory bandwidth. Which ECS instance family is the most appropriate choice for this workload?
Select the answer:Select the answer
1 correct answer
A.
General purpose g-series instances with a 1:4 vCPU-to-memory ratio
B.
Memory optimized r-series instances with a 1:8 vCPU-to-memory ratio
C.
Compute optimized c-series instances with a 1:2 vCPU-to-memory ratio
D.
Big data d-series instances with local SATA HDD storage
Explanation: Alibaba Cloud organizes ECS instance types into families that are engineered around specific vCPU-to-memory ratios and hardware characteristics. Memory optimized families such as r6 and r7 provide roughly 8 GiB of memory per vCPU, which matches workloads like in-memory databases, distributed caches such as Redis or Memcached, and real-time big data analytics that hold large working sets in RAM. General purpose families such as g6 offer a balanced 1:4 ratio and suit web applications and mid-sized databases, but they would force you to buy far more vCPUs than needed just to reach the required memory footprint, raising cost. Compute optimized families such as c6 provide a 1:2 ratio and are intended for CPU-bound workloads such as batch processing, video encoding, and high-traffic front-end fleets, making them the least suitable for a memory-hungry cache. Big data d-series instances are built around dense local HDD storage throughput for Hadoop-style sequential workloads rather than large memory footprints. Selecting the family whose resource ratio mirrors the workload profile is a core ECS sizing principle: it minimizes wasted resources and cost while meeting the performance target, which is exactly what the 1:8 memory optimized family achieves for caching clusters.
Right Answer: B
Quiz
Question 2/102/10
Server Load Balancer (SLB)
Server Load Balancer (SLB)
Server Load Balancer (SLB)
A microservices platform needs a load balancer that routes requests to different backend groups based on URL path and HTTP headers, supports canary releases by weighting rules, and speaks HTTP/2 to clients. Which Alibaba Cloud load balancer is the best fit?
Select the answer:Select the answer
1 correct answer
A.
Classic Load Balancer (CLB) with vServer groups and domain forwarding rules
B.
Application Load Balancer (ALB), which is purpose-built for advanced Layer 7 content-based routing
C.
Network Load Balancer (NLB), which offers the highest forwarding performance in the family
D.
DNS round robin across the service endpoints using CloudDNS
Explanation: The requirements are all application-layer routing features: path-based and header-based rule matching, fine-grained traffic splitting for canary releases, and modern protocol support including HTTP/2. Within the Alibaba Cloud load balancing family, the Application Load Balancer is the product positioned exactly here; it processes rich Layer 7 rules that match on domain, path, header, query string, and method, distributes traffic across server groups by weight for canary and blue-green rollouts, scales elastically, and natively supports HTTP/2 and WebSocket. The Classic Load Balancer does offer Layer 7 listeners with basic domain and URL forwarding to vServer groups, but its rule expressiveness stops well short of header matching and weighted rule-level canary control, making it an underpowered fit for a microservices gateway pattern. The Network Load Balancer operates at Layer 4; its strength is enormous connection scale and throughput for TCP and UDP, and it never inspects HTTP semantics, so it cannot route by path or header at all. DNS round robin is not a load balancer: it lacks health-based failover precision, has no request-level routing, and suffers from client-side caching that defeats traffic control during releases.
Right Answer: B
Quiz
Question 3/103/10
Object Storage Service (OSS)
Object Storage Service (OSS)
Object Storage Service (OSS)
An application on ECS instances in the cn-hangzhou region reads and writes several terabytes per day to an OSS bucket that is also in cn-hangzhou, currently using the bucket's public endpoint. How can costs and latency be reduced?
Select the answer:Select the answer
1 correct answer
A.
Enable transfer acceleration on the bucket so ECS traffic takes the accelerated path
B.
Keep the public endpoint but place a CDN in front of the bucket for the write traffic
C.
Migrate the bucket to a different region to spread the network load
D.
Switch the application to the bucket's internal endpoint (oss-cn-hangzhou-internal.aliyuncs.com), which carries no traffic charges and stays on the internal network
Explanation: Every OSS region exposes two endpoint types. The public endpoint is reachable over the internet, and downloads through it generate outbound internet traffic charges. The internal endpoint is reachable from Alibaba Cloud services in the same region, such as ECS instances, and traffic through it travels the internal network, which is both free of traffic charges and lower latency with higher, more stable throughput. For a workload moving terabytes daily between same-region ECS and OSS, pointing SDK or tool configuration at the internal endpoint is the single most effective optimization, often eliminating the majority of the OSS bill for that workload. Transfer acceleration solves a different problem, long-distance transfers across geographies, and adds acceleration fees; using it for same-region traffic would raise costs. A CDN accelerates repeated public downloads of cacheable content and does not apply to write-heavy, same-region service-to-service traffic. Moving the bucket to another region would force the traffic across regions, making it chargeable and slower, the opposite of the goal. Same-region colocation plus the internal endpoint is the intended architecture.
Right Answer: D
Quiz
Question 4/104/10
Virtual Private Cloud (VPC)
Virtual Private Cloud (VPC)
Virtual Private Cloud (VPC)
A network engineer is planning the primary IPv4 CIDR block for a new VPC. Which THREE of the following ranges (or their subsets) are the standard recommended choices for a VPC CIDR block? (Choose THREE)
Select multiple answer: (Choose 3)Select the answer
3 correct answers
A.
172.16.0.0/12
B.
100.64.0.0/10
C.
192.168.0.0/16
D.
10.0.0.0/8
E.
224.0.0.0/4
Explanation: VPC addressing is built on the RFC 1918 private ranges: 10.0.0.0/8, 172.16.0.0/12, and 192.168.0.0/16, and any subnets carved from them, with the CIDR mask for a VPC generally between /8 and /24. Choosing from these ranges avoids conflicts with public Internet addresses and keeps future interconnection options open, though engineers should still ensure the chosen block does not overlap with on-premises networks or other VPCs that may later be connected through VPN, Express Connect, or CEN, since overlapping blocks are the single most common cause of unroutable hybrid designs. 100.64.0.0/10 is the shared address space reserved for carrier-grade NAT; it is not one of the standard recommended VPC ranges and parts of it are used internally by some cloud services, so using it invites conflicts. 224.0.0.0/4 is the multicast address space and cannot be used for unicast host addressing at all. Planning also involves sizing: the block must be large enough for all future vSwitches, because the primary CIDR cannot be replaced later; capacity can be extended only by adding secondary CIDR blocks. Careful initial selection from the private ranges is therefore a foundational design step.
Right Answer: A, C, D
Quiz
Question 5/105/10
ApsaraDB RDS
ApsaraDB RDS
ApsaraDB RDS
A logistics company is building a fleet-tracking platform that must store vehicle coordinates and route polygons, run geospatial queries, and execute complex analytical SQL with window functions, common table expressions, and custom data types. Which ApsaraDB RDS engine is the most suitable choice for this workload?
Select the answer:Select the answer
1 correct answer
A.
ApsaraDB RDS for MySQL, because it is the most widely deployed open-source engine
B.
ApsaraDB RDS for PostgreSQL, because of its native geospatial capabilities and rich SQL feature set
C.
ApsaraDB RDS for SQL Server, because it integrates tightly with Windows-based tooling
D.
ApsaraDB RDS for MariaDB, because it is protocol-compatible with existing MySQL clients
Explanation: Choosing an RDS engine should start from the workload's functional requirements rather than popularity. PostgreSQL is renowned for standards-compliant, feature-rich SQL: it fully supports window functions, recursive common table expressions, user-defined and composite data types, and powerful indexing methods. Critically for this scenario, ApsaraDB RDS for PostgreSQL offers strong geospatial support through spatial extensions, making it the natural fit for storing coordinates and polygons and running distance, containment, and route queries. MySQL is an excellent general-purpose OLTP engine for web applications, but its geospatial functionality and analytical SQL capabilities are comparatively limited, so it would force workarounds for this use case. SQL Server is typically selected when an organization is committed to the Microsoft ecosystem, relies on .NET applications, or needs features such as linked servers and SQL Server-specific tooling; nothing in this scenario points to those needs, and licensing adds cost. MariaDB compatibility with MySQL clients does not address the geospatial or advanced analytical requirements either. On the ACP exam, engine-selection questions reward mapping requirements to engine strengths: geospatial data, complex analytics, and extensibility consistently indicate PostgreSQL; Windows integration indicates SQL Server; simple high-volume web OLTP commonly indicates MySQL.
Right Answer: B
Quiz
Question 6/106/10
Auto Scaling
Auto Scaling
Auto Scaling
An Auto Scaling group is configured with a minimum size of 2 and a maximum size of 8. The group currently contains 7 ECS instances. An administrator manually executes a simple scaling rule defined as "Add 3 instances". What is the outcome?
Select the answer:Select the answer
1 correct answer
A.
The scaling activity fails entirely and no instances are added
B.
All 3 instances are added, temporarily raising the group to 11 until the next health check
C.
The rule waits in a queue until 3 slots become available below the maximum
D.
Only 1 instance is added, because scaling activities are capped at the group's maximum size of 8
Explanation: The minimum and maximum sizes of a scaling group are hard boundaries that every scaling activity must respect, regardless of whether the activity originates from a manually executed rule, an event-triggered task, or a scheduled task. When executing a rule would push the group beyond a boundary, Auto Scaling performs a partial execution: it scales as far as the boundary allows and stops there. In this case the group has room for exactly one more instance before reaching the maximum of 8, so the activity launches a single instance and completes, typically recording that the adjustment was truncated to honor the limit. The activity does not fail outright, because partial fulfillment toward the boundary is the designed behavior, and the platform never overshoots the maximum even briefly, since the cap exists precisely to control cost and quota exposure. There is also no queuing concept whereby a rule waits for future capacity; each activity is evaluated against the group's state at execution time. Administrators who genuinely need 10 instances must first raise the group's maximum size.
Right Answer: D
Quiz
Question 7/107/10
Content Delivery Network (CDN)
Content Delivery Network (CDN)
Content Delivery Network (CDN)
A solutions architect is explaining to a customer how Alibaba Cloud CDN reduces both user latency and origin server load. Which statement correctly describes the request flow through the CDN's cache hierarchy?
Select the answer:Select the answer
1 correct answer
A.
Every user request travels to the origin server, and the CDN's role is limited to compressing the response on the way back
B.
The CDN proactively copies all origin content to every edge node worldwide as soon as the domain is added
C.
A request is routed to the nearest L1 edge node; on a cache miss it goes to an upper-layer L2 node, and only if that also misses does the request reach the origin, so many edges share one fetched copy
D.
Each edge node maintains a permanent synchronous replica of the origin's file system over a dedicated connection
Explanation: Alibaba Cloud CDN uses intelligent DNS scheduling to resolve the accelerated domain to the edge (L1) node closest to the user. If that node holds a valid cached copy, it responds immediately, which is the low-latency hit path. On a miss, the edge does not go straight to the origin; it queries an upper-layer (L2) aggregation node. Because many L1 edges funnel into far fewer L2 nodes, a single back-to-origin fetch made by an L2 node can populate content that subsequently serves misses from numerous edges, multiplying the protective effect for the origin. Only when both layers miss does a request actually consume origin bandwidth and compute. This layered pull model explains the two headline benefits: users are served from nearby nodes, and the origin sees a small fraction of total requests. Content is pulled on demand and cached according to TTL, not proactively replicated everywhere, which would be wildly wasteful for long-tail content; proactive population exists only as the explicit prefetch feature for chosen URLs. There is likewise no synchronous file-system mirroring; the CDN is a cache, and consistency is managed through TTLs and refresh operations rather than replication.
Right Answer: C
Quiz
Question 8/108/10
Cloud Security
Cloud Security
Cloud Security
A company stores sensitive financial reports in an OSS bucket named "finance-reports". A single RAM user needs read and write access to this bucket only and must not be able to access any other OSS bucket in the account. What is the recommended way to grant this access?
Select the answer:Select the answer
1 correct answer
A.
Attach the system policy AliyunOSSFullAccess to the RAM user
B.
Share the AccessKey of the Alibaba Cloud root account with the user, since only one person needs access
C.
Create a custom policy whose Resource element specifies only the finance-reports bucket and its objects, and attach it to the RAM user
D.
Attach AliyunOSSReadOnlyAccess to the RAM user and ask the user to request write permission separately when needed
Explanation: The principle of least privilege requires granting an identity only the permissions it actually needs, on only the resources it needs. A custom RAM policy can list the specific bucket and its objects in the Resource element, for example "acs:oss:*:*:finance-reports" and "acs:oss:*:*:finance-reports/*", combined with only the required read and write actions. This confines the RAM user to a single bucket while permitting both reading and writing. Attaching AliyunOSSFullAccess would grant full control over every bucket in the account, which is far broader than required and violates least privilege. Sharing the root account AccessKey is one of the most serious security anti-patterns on Alibaba Cloud, because the root account has unrestricted permissions over all resources and billing, and its credentials cannot be constrained by RAM policies. A read-only system policy fails the requirement because the user also needs write access, and it still applies to every bucket rather than one. System policies cannot be edited to narrow their scope, which is exactly why custom policies exist: they let administrators define fine-grained combinations of Action, Resource, and Condition tailored to a specific business need.
Right Answer: C
Quiz
Question 9/109/10
CloudMonitor
CloudMonitor
CloudMonitor
A new ECS instance was created an hour ago and no software has been installed on it. In the CloudMonitor console, an operations engineer can already see several metrics for the instance. Which of the following metrics will NOT be visible until the CloudMonitor agent is installed on the instance?
Select the answer:Select the answer
1 correct answer
A.
Memory usage
B.
CPU utilization
C.
Outbound public network bandwidth
D.
Disk read BPS
Explanation: CloudMonitor collects ECS metrics at two distinct levels. Basic monitoring data is gathered from the virtualization (hypervisor) layer without any software inside the guest operating system; this includes CPU utilization, public and internal network inbound and outbound traffic and bandwidth, and disk read and write throughput and IOPS as observed from outside the virtual machine. These metrics appear automatically for every ECS instance shortly after creation. Operating-system-level metrics, by contrast, can only be measured from inside the guest: how much of the memory is actually consumed by processes, what percentage of each mounted file system is used, the system load average, per-process statistics, and TCP connection states. Gathering these requires the CloudMonitor agent to run inside the instance, because the hypervisor cannot reliably see how the guest kernel allocates memory or lays out file systems. Consequently, a freshly created instance with no agent shows CPU, network, and disk throughput data, but the memory usage series is absent. This distinction is a frequent troubleshooting theme: whenever memory or disk usage metrics are missing while CPU data is present, the immediate suspicion should be the absence or failure of the agent.
Right Answer: A
Quiz
Question 10/1010/10
Cloud Computing Fundamentals
Cloud Computing Fundamentals
Cloud Computing Fundamentals
A developer signs in to the Alibaba Cloud console at midnight, provisions an ECS instance and an RDS database in minutes without contacting any sales or support personnel, and deletes them two hours later, paying only for the time used. Which essential characteristic of cloud computing does the provisioning behavior primarily illustrate?
Select the answer:Select the answer
1 correct answer
A.
On-demand self-service, where consumers provision computing capabilities automatically without requiring human interaction with the provider
B.
Broad network access, where capabilities are available over the network through standard client platforms
C.
Resource pooling, where the provider's resources serve multiple consumers using a multi-tenant model
D.
Vendor lock-in, where consumers become dependent on a single provider's proprietary interfaces
Explanation: The widely accepted definition of cloud computing lists essential characteristics that distinguish it from traditional hosting: on-demand self-service, broad network access, resource pooling, rapid elasticity, and measured service. The scenario's defining detail is that the developer obtained and released real infrastructure autonomously, at an arbitrary hour, purely through a self-service interface, with no ticket, salesperson, or manual provisioning step on the provider's side; that is the textbook description of on-demand self-service. The other characteristics are real but describe different facets. Broad network access refers to services being reachable over standard networks from heterogeneous clients such as browsers, CLIs, and SDKs; it is present in the scenario but is not what the provisioning behavior primarily demonstrates. Resource pooling describes how the provider dynamically assigns pooled physical resources to many customers, which is invisible to the developer here. Paying only for the two hours used illustrates measured service, a complementary characteristic mentioned in the scenario but distinct from the autonomous provisioning being asked about. Vendor lock-in is not an essential characteristic of cloud computing at all; it is a commercial and architectural risk to be managed, not part of the definition.
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