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Alibaba Cloud Certified Expert: Solutions Architect Practice Test

SAE-C01 exam Format | Course Contents | Course Outline | exam Syllabus | exam Objectives

Exam Code: SAE-C01
Exam Name: Alibaba Cloud Certified Expert: Solutions Architect
Number of Questions: 100
Time Allotted: 120 minutes
Passing Marks: 80 out of 100 (80%)
Exam Format: Multiple-choice questions; available online or offline via Pearson VUE test centers (not available via OnVUE for overseas customers)
Languages: English

Security Services on Public Cloud
- Identity and Access Management (IAM)
- RAM (Resource Access Management): Centralized service for managing user identities- permissions- and roles. Supports fine-grained access control via policies (e.g.- JSON-based statements with actions- resources- and conditions).
- STS (Security Token Service): Temporary credential service for federated access- enabling short-lived tokens for secure API calls without long-term keys.
- MFA (Multi-Factor Authentication): Layered security requiring additional verification (e.g.- TOTP or SMS) for privileged accounts.
- Data Protection and Encryption
- KMS (Key Management Service): Managed hardware security module (HSM)-backed service for creating- rotating- and auditing cryptographic keys (symmetric/asymmetric- CMK - Customer Master Keys).
- SSE (Server-Side Encryption): Automatic encryption at rest for services like OSS; supports SSE-KMS for customer-managed keys.
- TDE (Transparent Data Encryption): Database-level encryption for RDS to protect data files without application changes.
- Threat Detection and Response
- Security Center (SC): Unified dashboard for vulnerability scanning- baseline checks- and real-time alerts on threats like malware or intrusions.
- WAF (Web Application Firewall): Layer-7 protection against OWASP Top 10 threats- including SQL injection- XSS- and CC attacks; uses managed rulesets and custom policies.
- Anti-DDoS (Anti-DDoS Pro/Basic): Traffic scrubbing service mitigating volumetric attacks up to 5 Tbps; includes SYN flood protection and blackhole activation.
- Compliance and Auditing
- ActionTrail: Logs API calls for auditing and compliance (e.g.- PCI DSS- HIPAA); supports trail delivery to OSS or Log Service.
- CloudMonitor: Metrics and alerts for security events- integrated with SLB and ECS for anomaly detection.

Storage Services on Public Cloud
- Object Storage
- OSS (Object Storage Service): S3-compatible storage for unstructured data; supports Standard- Infrequent Access (IA)- Archive- and Cold Archive tiers for cost efficiency.
- Multipart Upload: Parallel upload for large objects (>100 MB) to Boost reliability and speed.
- Bucket Policies: ACLs and cross-account access using JSON conditions for read/write permissions.
- Block and File Storage
- ESS (Enhanced SSD): High-IOPS block storage for ECS; performance tiers (PL0-PL3) based on IOPS/throughput (e.g.- PL1: 50-500 MB/s).
- NAS (Network Attached Storage): NFS/SMB file system for shared access; supports Extreme NFS for low-latency workloads.
- Snapshot Service: Point-in-time copies for EBS volumes; incremental backups with rollback capabilities.
- Backup and Archival
- Hybrid Backup Recovery (HBR): Centralized backup for ECS- OSS- and on-premises; features vault-based storage and GRS (Geo-Redundant Storage).
- Data Lifecycle Management: Automated transitions (e.g.- OSS IA to Archive after 30 days) via rules to reduce costs.
- High-Performance Storage
- OSS-HPC: Parallel file system for AI/ML workloads; integrates with OSS for petabyte-scale data lakes.

Compute Services on Public Cloud
- Virtual Machines
- ECS (Elastic Compute Service): IaaS VMs with instance types (e.g.- ecs.g7: general-purpose- ecs.c7: compute-optimized); supports burstable performance (bPSU).
- Auto Scaling: Dynamic adjustment of ECS groups based on metrics (CPU >80%); integrates with SLB for HA.
- Security Groups: Stateful firewalls for inbound/outbound traffic rules at instance level.
- Serverless Compute
- FC (Function Compute): Event-driven- pay-per-use execution; supports custom runtimes (Node.js- Python) and triggers from OSS/SMS.
- EDAS (Enterprise Distributed Application Service): Middleware for Java apps with auto-scaling and zero-downtime deployments.
- Bare Metal and GPU Instances
- EBM (Elastic Bare Metal): Single-tenant instances for compliance; no hypervisor overhead.
- Elastic GPU Service (EGS): vGPU sharing for graphics-intensive tasks; types like gn6v (NVIDIA V100).
- Image and Deployment Management
- Custom Images: Built from snapshots; supports encrypted images for secure sharing.
- Deployment Sets: Fault isolation strategies (high-availability set- zone-disaster-recovery set) for multi-AZ resilience.

Public Cloud Architectures
- High Availability and Disaster Recovery
- RPO/RTO: Recovery Point Objective (data loss tolerance) and Recovery Time Objective (downtime tolerance); e.g.- synchronous replication for RPO=0.
- Multi-AZ Architecture: Spreading resources across Availability Zones within a region for 99.99% SLA.
- GSLB (Global Server Load Balancing): DNS-based traffic routing for global HA; health checks and weighted policies.
- Scalability Patterns
- Horizontal Scaling: Adding ECS instances via Auto Scaling groups; stateless design for loose coupling.
- Vertical Scaling: Instance type upgrades (e.g.- from c6 to c7) for CPU/memory bursts.
- Cost Optimization
- Savings Plans: Committed usage discounts (e.g.- 1/3-year terms) vs. Spot Instances for interruptible workloads.
- TCO Calculator: Tool for comparing on-premises vs. cloud costs- factoring in Reserved Instances (RI).
- Migration and Modernization
- Migrate to Cloud: Tools like Database Migration Service for lift-and-shift; re-architect for microservices.

Database Services on Public Cloud
- Relational Databases
- RDS (Relational Database Service): Managed MySQL/PostgreSQL/SQL Server; primary/secondary replication with semi-sync mode.
- ApsaraDB for RDS: High-availability edition with read replicas (up to 15) and auto-backup (7-732 days retention).
- Tair: In-memory caching (Redis-compatible); supports AOF/RDB persistence and cluster mode for 1M+ QPS.
- NoSQL and Big Data
- Table Store (OTS): Wide-column NoSQL for massive structured data; supports single-table partitioning and 10K+ ops/sec.
- PolarDB: Cloud-native RDBMS with shared storage; scales to 100 TB- 99.99% durability via log-based replication.
- Analytical Databases
- AnalyticDB: HTAP (Hybrid Transactional/Analytical Processing) for real-time queries; MPP architecture with 1 PB scale-out.
- Data Transmission Service (DTS): Real-time sync/migration between DBs; supports schema/table-level CDC (Change Data Capture).
- Backup and Performance
- Physical Backup: Block-level snapshots for RDS; cross-region DR with PITR (Point-in-Time Recovery).
- Performance Insights: Query optimization with slow log analysis and index recommendations.

Networking Services on Public Cloud
- Virtual Networking
- VPC (Virtual Private Cloud): Isolated network with CIDR blocks; supports IPv4/IPv6 and flow logs via SLS.
- VSwitch: Subnet within VPC for resource attachment; spans one AZ with route tables for inter-VSwitch routing.
- NAT Gateway: Outbound internet access for private subnets; SNAT/DNAT with EIP binding.
- Load Balancing and Acceleration
- SLB (Server Load Balancer): L4/L7 balancing; Classic (CLB) for intra-VPC- Application (ALB) for HTTP/HTTPS path routing.
- CDN (Content Delivery Network): Edge caching with dynamic acceleration; protocols like QUIC for reduced latency.
- GA (Global Accelerator): Any-cast EIP for traffic steering to nearest POP; integrates with SLB for 50% latency reduction.
- Connectivity and Peering
- VPN Gateway: IPsec/IKEv2 tunnels for site-to-site connectivity; supports BGP for dynamic routing.
- Express Connect: Private fiber links to on-premises; CEN (Cloud Enterprise Network) for multi-VPC/region peering.
- Cloud Firewall: Centralized policy enforcement across VPCs; threat intel feeds for east-west traffic.
- DNS and Monitoring
- Alibaba Cloud DNS: Authoritative/managed DNS with health checks; supports private zones for VPC resolution.

Cloud Native Services on Public Cloud
- Container Orchestration
- ACK (Alibaba Cloud Container Service for Kubernetes): Managed K8s with auto-upgrades; supports node pools (system/user) and CSI for storage.
- Container Registry (ACR): Docker OCI-compliant repo; Enterprise edition with vulnerability scanning and geo-replication.
- Helm Charts: Package manager for K8s apps; ACK integrates with ARGO for GitOps deployments.
- Serverless and Microservices
- Serverless App Engine (SAE): PaaS for Java/Node.js; auto-scales pods with traffic mirroring for canary releases.
- MSE (Microservices Engine): Service mesh with Istio-compatible governance; circuit breakers- rate limiting- and tracing via Jaeger.
- EventBridge: SaaS integration bus for event routing; sources like OSS uploads trigger FC functions.
- DevOps and Monitoring
- DevOps Platform: CI/CD with Jenkins integration; pipeline as code for blue-green deployments.
- ARMS (Application Real-Time Monitoring Service): APM for cloud native; traces requests across services with Prometheus metrics.
- Service Security
- CS (Container Security Service): Runtime protection with Falco rules; scans images for CVEs and enforces pod policies.

Hybrid Cloud
- Connectivity and Extension
- Cloud Enterprise Network (CEN): Global transit hub for hybrid peering; supports VBR (Virtual Border Router) attachments.
- Express Connect Circuit: Dedicated 1-100 Gbps links to data centers; low-latency (<10 ms) with SLA 99.95%.
- VPN Connect: Encrypted tunnels over public internet; supports dead peer detection for failover.
- Data Synchronization and Backup
- DataSync: Real-time file/folder sync between on-premises NFS and OSS/NAS; bandwidth throttling for hybrid DR.
- HBR (Hybrid Backup Recovery): Agent-based backups from physical servers to cloud vaults; deduplication and encryption.
- Management and Governance
- CloudMonitor Hybrid: Unified metrics for on-premises agents; alerts on cross-environment anomalies.
- Apsara Stack: On-premises Alibaba Cloud replica for regulated industries; supports hybrid ACK for consistent K8s.
- Workload Portability
- Server Migration Center (SMC): VM import from VMware/Hyper-V to ECS; block replication with minimal downtime.
- Edge Node: Outpost-like extension for low-latency inference; integrates ACK for hybrid container runs.

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SAE-C01
Alibaba Cloud Certified Expert: Solutions Architect
https://killexams.com/pass4sure/exam-detail/SAE-C01
Question: 1592
A global e-commerce platform experiences unpredictable spikes in write and read
requests with massive amounts of semi-structured user data, requiring smooth handling of
10k+ operations per second without full table scans. Which feature of Table Store
architecture optimally supports this workload?
A. Multi-master replication
B. Vertical scaling of storage nodes
C. Single-table partitioning
D. ACID-compliant transactions
Answer: C
Explanation: Table Store utilizes single-table partitioning to shard data across multiple
nodes, allowing it to handle massive structured data and 10k+ operations per second
efficiently. Vertical scaling or multi-master replication is less relevant here, while ACID
transactions are limited in Table Store as a NoSQL database.
Question: 1593
A genomics research consortium is migrating a 5 PB exome sequencing dataset to
Alibaba Cloud for real-time variant calling using a hybrid Spark-on-Kubernetes
workload, where OSS-HPC serves as the intermediate scratch space for SAM/BAM file
transformations. The architecture must handle 10,000 concurrent reads from E-HPC
clusters with sub-10ms latency for random 4KB metadata accesses, while ensuring fault-
tolerant striping of sequence alignments to underlying OSS buckets for long-term
petabyte-scale data lake persistence. During peak variant discovery phases, the system
experiences metadata contention leading to 20% throughput degradation. Which OSS-
HPC capabilities and integrations would resolve this contention and enhance overall
pipeline resilience?
A. Implement OSS-HPC's dynamic scaling of metadata servers to auto-provision up to
1,000 MDS nodes based on IOPS demand, restoring throughput to 95% of baseline
during contention spikes
B. Utilize OSS-HPC's integration with Alibaba Cloud's Data Lake Analytics to offload
metadata indexing to serverless queries, reducing MDS load by 70% for BAM header
lookups
C. Enable OSS-HPC's erasure coding with N+3 redundancy on OSS-backed stripes,
ensuring zero data loss during 48-hour transformation jobs even with 3 concurrent node
failures
D. Configure OSS-HPC with hybrid caching layers using local NVMe SSDs on ECS
nodes, prefetching alignment metadata to achieve consistent sub-5ms access times across
the Kubernetes pod fleet
Answer: A, C, D
Explanation: OSS-HPC addresses metadata contention in high-concurrency genomics
workloads by dynamically scaling metadata servers (MDS) up to 1,000 instances based
on real-time IOPS metrics, which intelligently redistributes load and recovers throughput
to near-baseline levels without manual intervention. For resilience, its erasure coding
integration with OSS applies N+3 parity across striped files, tolerating up to three node
failures mid-job while maintaining data integrity for critical BAM transformations in
petabyte pipelines. Hybrid caching in OSS-HPC leverages NVMe SSDs on ECS
instances for metadata prefetching, delivering sub-5ms latencies for random accesses in
distributed Spark jobs on Kubernetes. Offloading to Data Lake Analytics is feasible for
analytics but does not directly mitigate OSS-HPC's internal MDS contention, as it
operates outside the parallel file system's core metadata plane.
Question: 1594
After enabling Prometheus monitoring with ARMS, why might some metrics not be
visible in dashboards?
A. CS container policies blocked metric endpoints
B. Jenkins pipeline failed to deploy applications
C. Incorrect Prometheus scraping configuration or missing metrics exposition
D. Falco detection disabled metrics
Answer: C
Explanation: Prometheus requires correct scraping targets and that services expose
metrics endpoints properly. Jenkins pipelines don�t affect metrics visibility after
deployment. CS and Falco focus on security, not metrics exposure.
Question: 1595
A SaaS CRM provider scales customer data pipelines on Alibaba Cloud, blending pay-as-
you-go ECS for ETL jobs with preemptible for data cleansing bursts, amid a TCO shift
from 250 on-premises servers (4-year depreciation at 500,000 USD total, 0.16 USD/kWh
power). The architect must layer discounts for 25% YoY growth. Which?
A. TCO via Pricing Calculator projecting server refresh cycles against ECS with 3-year
Savings Plans at 70% discount for ETL.
B. Preemptible cleansing at 75% bid, with Data Lake Analytics for burst orchestration.
C. 1-year Reserved for ETL, underprojecting growth TCO.
D. Savings Plans 80% commitment + preemptible, TCO growth-scaled.
Answer: A, B, D
Explanation: Pricing Calculator TCO models on-premises (250 servers 125,000 USD/
year + power) vs. ECS, 3-year Savings Plans 70% for ETL yielding 48% savings with
growth. Preemptible 75% for bursts, Data Lake Analytics handles. Savings 80% +
preemptible, TCO YoY scaled, over Reserved.
Question: 1596
During a penetration test, an application behind Alibaba Cloud WAF was found
vulnerable to a new zero-day OWASP attack vector not covered in existing managed
rulesets. What is the best course of action?
A. Disable WAF to avoid false positives
B. Create a custom WAF rule to detect and block the zero-day attack pattern immediately
C. Wait for Alibaba Cloud to update managed rulesets
D. Handle traffic filtering manually
Answer: B
Explanation: Creating a custom WAF rule allows immediate mitigation of the new threat,
protecting the application proactively. Disabling WAF exposes the app, waiting for
vendor updates delays mitigation, and manual filtering is impractical at scale.
Question: 1597
A multinational e-commerce platform experiences a surge in user-generated content
during peak shopping seasons, resulting in 5 million daily writes of semi-structured
product reviews, each with variable attributes like timestamps, ratings, and embedded
images metadata. The platform requires a solution to handle this at sub-10ms latency
while integrating with real-time analytics pipelines for sentiment analysis. Existing
infrastructure uses ECS instances with self-managed Cassandra, but hotspots cause 20%
query failures. Which approaches should the solutions architect recommend to migrate to
Alibaba Cloud while ensuring 99.999999999% data durability and seamless scaling to 10
PB without downtime?
A. Configure Table Store with a composite partition key using user ID and timestamp
hash to distribute hotspots, enabling single-table partitioning for massive structured data
ingestion at 10K+ ops/sec per partition.
B. Deploy PolarDB for MySQL in a multi-master cluster edition with shared storage,
leveraging log-based replication for active geo-redundancy across three AZs to achieve
zero RPO during regional failures.
C. Utilize Table Store's streaming read interfaces combined with DataHub for
incremental data tunnels to MaxCompute, allowing SQL-based real-time queries on 1
billion+ records without pre-defining schemas.
D. Implement PolarDB-X for distributed scaling with Paxos protocol multi-replica
consistency, partitioning review data across petabyte-scale storage while supporting
HTAP for concurrent OLTP writes and OLAP analytics.
Answer: A, C
Explanation: For handling massive semi-structured data with variable attributes and high
write throughput, Table Store's wide-column NoSQL model excels due to its schema-free
design, sparse tables allowing differing column counts per row, and automated
partitioning via composite keys to mitigate hotspots�achieving 10K+ ops/sec per
partition and scaling to 10 PB per table with three-replica durability ensuring
99.999999999% reliability through Parallel-Raft consensus. Integrating with DataHub
and MaxCompute via streaming reads enables efficient incremental synchronization for
real-time analytics like sentiment processing on trillion-scale records, avoiding the need
for schema pre-definition and reducing migration complexity from Cassandra. PolarDB
options, while robust for relational workloads, introduce unnecessary overhead for semi-
structured NoSQL ingestion, as their shared storage and log replication are optimized for
ACID transactions rather than the platform's variable-attribute, high-velocity writes.
Question: 1598
A security team wants to enforce runtime protection of containers on ACK (Alibaba
Cloud Container Service). Which CS feature leverages Falco rules to detect suspicious
system calls and behaviors?
A. Vulnerability scanning of container images
B. Runtime security monitoring
C. Jenkins pipeline enforcement
D. Prometheus metric security
Answer: B
Explanation: CS runtime security integrates Falco rules to monitor system calls and
container behaviors in real time to detect breaches or anomalous activity. Image
vulnerability scanning checks images before deployment, Jenkins pipelines manage CI/
CD, and Prometheus metrics focus on monitoring, not runtime security.
Question: 1599
An enterprise experiences increased latency when encrypting data at the application layer
using client-side encryption before uploading to OSS. What is a possible alternative to
reduce encryption overhead while maintaining strong security?
A. Use symmetric encryption with static keys
B. Remove encryption entirely
C. Use OSS SSE-KMS encryption
D. Switch to TDE for object encryption
Answer: C
Explanation: OSS SSE-KMS offloads encryption to server side with managed keys,
reducing client overhead while maintaining strong security guarantees. TDE applies only
to databases, and removing encryption reduces security.
Question: 1600
A e-commerce peak hybrid, centers in Seoul and Dubai to Alibaba Cloud Korea/ME via
CEN. ECMP 60 Gbps, flow anomalies, AI latency, CCN partners. Which CEN for peak
e-com?
A. ECMP 60 Gbps peaks.
B. Flow anomalies, CCN.
C. AI latency.
D. No ECMP.
Answer: A, B, C
Explanation: ECMP for loads, flow/CCN detect/partner, AI fast. No ECMP bottlenecks.
Question: 1601
In a healthcare telemedicine app on Alibaba Cloud integrating with on-premises EMR
systems, threats involve ransomware via web tampering on patient portals, SQLi in query
endpoints, and SYN floods on ALB during virtual consults. Security Center's anti-
ransomware must snapshot recoveries, WAF custom policies for healthcare schema
compliance, and Anti-DDoS exception thresholds to avoid blackholing consult streams.
Which scenario-specific configurations across services ensure HIPAA-aligned
protection?
A. Security Center Snapshot Recovery for tamper-proof patient data restoration
B. WAF Healthcare Schema Policies for SQLi mitigation in EMR queries
C. Anti-DDoS Exception Thresholds for SYN flood tolerance on ALB
D. CTDR Cross-Service Alerting for integrated ransomware and DDoS tracing
Answer: A, B, C, D
Explanation: Security Center Snapshot Recovery provides automated backups and point-
in-time restores for tampered portal files, integrated with web tamper proofing to alert
and revert ransomware changes, supporting HIPAA data integrity. WAF Healthcare
Schema Policies validate EMR API payloads against standards like FHIR, blocking SQLi
via parameterized queries and input escaping tailored for sensitive health data exchanges.
Anti-DDoS Exception Thresholds customize SYN flood limits per ALB IP, preventing
blackhole disruptions to real-time consult video streams while scrubbing excess traffic.
CTDR Cross-Service Alerting unifies Security Center, WAF, and Anti-DDoS logs for
threat tracing, generating HIPAA-compliant incident reports on correlated ransomware-
DDoS vectors.
Question: 1602
A legal doc review on Alibaba Cloud deploys EDAS HSF for analysis, auto-scaling
threads>80%/latency, zero-downtime blue-green, GTS reviews, mTLS, SchedulerX
indexing, Jaeger, RDS store. Which EDAS?
A. HSF analysis, auto-scaling threads/latency, blue-green zero-downtime, GTS reviews.
B. Professional mTLS, Jaeger traces, SchedulerX indexing, RDS.
C. Standard no GTS, manual, no Jaeger.
D. Container no mTLS, basic.
Answer: A, B
Explanation: HSF for doc services, auto-scaling threads>80%/latency; blue-green zero-
downtime, GTS consistency. Professional mTLS; Jaeger traces, SchedulerX indexes,
RDS stores.
Question: 1603
Which statement correctly describes the route table behavior in Alibaba Cloud regarding
VSwitches within a single VPC?
A. Route tables must be manually configured for each VSwitch to enable communication
between VSwitches
B. Each VSwitch automatically inherits the main route table from the VPC for routing
C. Route propagation in the route table must be disabled to allow VSwitch routing
D. VSwitches in different AZs cannot communicate regardless of route tables
Answer: B
Explanation: By default, all VSwitches within a VPC use the main route table, allowing
them to communicate without additional configuration. Route propagation settings
control dynamic routes and are unrelated to default VSwitch routing.
Question: 1604
Gaming leaderboard resolves "score.game.leader" to SRV Redis in ACK VPC
(Philippines Manila), TCP 6379 every 8 seconds. Forward to Redis Cloud 34.202.0.1,
200 TTL, CloudMonitor score updates. 2026, which ACK Redis?
A. Acceleration zones SRV Redis, TCP 6379, ACK bind, forward to Redis Cloud,
CloudMonitor updates.
B. Regular zones leader, recursion Redis, subzones score.
C. HTTP Redis, manual SRV, no forward.
D. No SRV, disable ACK, ignore updates.
Answer: A
Explanation: Acceleration zones SRV for Redis services, TCP port checks at 8 seconds,
ACK binding auto; forwarding + CloudMonitor update scores. Regular leader phases,
recursion risks; HTTP mismatches, manual SRV static, no forward isolates. No SRV
limits, disable ACK manual, ignore unranked.
Question: 1605
Your organization must integrate ACK clusters with VPCs to ensure secure private
network communication between pods and enterprise services. Which ACK networking
feature supports this integration?
A. Using public IPs for pod-to-service communication
B. Using overlay networks without VPC integration
C. Deploying nodes without private IPs
D. VPC-native networking with ENI (Elastic Network Interface) mode
Answer: D
Explanation: ACK supports VPC-native networking using ENI mode, allowing pods to
obtain IP addresses from the VPC subnet, facilitating secure, high-performance private
connectivity within enterprise networks.
Question: 1606
A supply chain Oracle/OSS HBR Mumbai GRS Chennai, RAC consistency, OSS Cold
Archive 40 days access, delete 3 years. Compression, DR ECS.
A. HBR Oracle RAC, compression GRS.
B. OSS Cold Archive 40, expire 1095.
C. ECS annual DR.
D. Dedup chain data.
Answer: A, B, D
Explanation: RAC consistency/compression for queries, Cold Archive for shipments.
ECS DR, dedup savings.
Question: 1607
PolarDB�s LogIndex technology offers two record replay modes: lazy replay and parallel
replay. For which scenario is parallel replay especially beneficial?
A. Encrypting data-at-rest
B. Increasing storage capacity dynamically
C. Minimizing replication lag for large OLAP queries
D. Scaling read-only nodes horizontally
Answer: C
Explanation: Parallel replay accelerates redo log application on replicas, reducing
replication lag for complex analytical queries (OLAP) with heavy workloads. It does not
directly relate to storage scaling, encryption, or horizontal scaling of nodes.
Question: 1608
Telecom lifts OSS/BSS from Amdocs to RDS, modernizing to 5G services on MSE. TM
Forum compliance. Which?
A. DTS Amdocs schemas.
B. MSE TM APIs.
C. Event streaming.
D. Orchestration.
Answer: A, B, C
Explanation: DTS syncs OSS/BSS. MSE exposes TM. Streaming enables 5G.
Question: 1609
How does Alibaba Cloud ActionTrail assist in meeting HIPAA compliance requirements
for covered entities using cloud resources?
A. By encrypting all ECS data volumes by default
B. By logging all API calls related to resource access and delivering encrypted logs for
audit and forensic analysis
C. By anonymizing user identities in cloud logs
D. By automatically patching cloud services for vulnerabilities
Answer: B
Explanation: HIPAA compliance requires detailed, tamper-evident audit trails recording
access to protected health information and cloud resources. ActionTrail helps by logging
all relevant API calls and enabling secure log delivery. Encryption of data volumes and
patching are important security controls but not direct functions of ActionTrail.
Anonymizing logs would conflict with audit traceability.
Question: 1610
For AR/VR content, creators upload 90 GB scenes multipart globally, accelerated via
Transfer. Policies limit to Verified creators, abort >4 hours. CDN with geo-routing. Which
accel and route enhances?
A. Enable Transfer Acceleration, SDK endpoint *.accelerate.aliyuncs.com
B. Policy "Allow" if "StringEquals": {"sts:RoleSessionName": "verified-creator-*"}
C. Lifecycle abort >4 hours incomplete
D. CDN geo-routing to nearest POP for scene delivery
Answer: A, B, C, D
Explanation: Acceleration speeds global multipart. Session name verifies creators. Abort
manages incompletes. Geo-CDN reduces latency. Powers 2026 AR/VR.
Question: 1611
How does Alibaba Cloud Function Compute ensure high availability across zones?
A. Re-deploy functions on ECS instances in one zone
B. Deploy functions in distributed clusters across multiple availability zones
C. Use static DNS to route requests
D. Use manual failover scripts
Answer: B
Explanation: Function Compute is deployed on distributed clusters in multiple
availability zones so that if one zone fails, another takes over automatically to ensure
service continuity.
Question: 1612
A financial analytics platform processes batch jobs on c6.xlarge ECS instances, facing
memory exhaustion during quarterly reports that involve complex simulations. Vertical
scaling to c7.2xlarge is planned during off-peak hours, but the workload uses GPU-
accelerated libraries incompatible with standard c7 CPUs. The architect must balance
compute upgrades with fallback options for burst scenarios. Which factors should be
prioritized for a hybrid vertical scaling strategy?
A. Schedule instance type changes via Auto Scaling's vertical scaling feature during
maintenance windows, ensuring zero-downtime by using blue-green deployments with
SLB routing.
B. Select c7.2xlarge for its superior SPECint benchmark scores (up to 20% higher than c6
equivalents), optimizing CPU-bound simulations without altering NUMA configurations
for multi-threaded tasks.
C. Provision burstable t7 instances as a supplemental tier, configuring CloudMonitor
alarms to trigger vertical scaling only when sustained CPU credits deplete below 20%.
D. Validate application compatibility with c7's enhanced I/O engine, testing packet
forwarding rates up to 100 Gbps to handle increased data ingress from ApsaraDB RDS
during reports.
Answer: B, D
Explanation: c7.2xlarge instances deliver markedly higher SPECint performance due to
Intel Xeon 6 P-cores and CIPU optimizations, making them ideal for CPU-intensive
financial simulations in vertical scaling, with NUMA awareness already tuned for such
workloads. Testing compatibility with the enhanced I/O engine ensures the upgraded
packet forwarding capabilities (up to 100 Gbps) support escalated data flows from RDS
without latency spikes. Auto Scaling vertical scaling supports scheduled changes but
relies on SLB for zero-downtime, not inherently requiring blue-green for ECS upgrades.
Burstable t7 instances suit variable loads but introduce credit management complexity
unsuitable as primary for sustained batch vertical scaling.
Question: 1613
Energy monitoring CLB L4 TCP sensors, GA anycast AU 35% latency. CLB IP hash,
drain 55s, ACL data. Weights 60/40. Which?
A. CLB TCP IP hash, 55s drain, ACL TCP
B. GA TCP to CLB, Anycast, 60/40, CEN
C. LCU, multicast sensors, geo AU
D. GA checks 8s, 1.2 Gbps, failover 11s
Answer: A, B
Explanation: CLB TCP IP hash persist, drain, ACL. GA TCP Anycast, weights, CEN for
35% cut. LCU; multicast; geo; checks 5s; failover 10s.
Question: 1614
Your team wants to run serverless applications in Alibaba Cloud Function Compute using
a custom runtime for a new language not natively supported. Which approach is the best
practice to implement this?
A. Use Alibaba Cloud provided Node.js runtime and transpile code
B. Develop a custom runtime adhering to FC runtime API and package it with the
function
C. Run the code on ECS instances behind FC
D. Use EDAS for custom language support
Answer: B
Explanation: Function Compute supports custom runtimes by allowing users to provide
their own runtime implementations that comply with the FC runtime API. This enables
running functions in any language by packaging the runtime alongside function code.
Question: 1615
If a NAT Gateway EIP is bound to multiple VPCs in different regions, what is the
Alibaba Cloud recommendation?
A. EIP bound to NAT Gateway must be unique per region; cross-region binding is
unsupported
B. NAT Gateway supports multi-region EIP binding by default
C. VPC peering is automatically established to support multi-region EIP use
D. Gateway Load Balancer distributes traffic to multiple NAT Gateways
Answer: A
Explanation: NAT Gateway EIPs are regional resources and cannot be bound across
multiple regions. The architecture must design EIPs specific to each region's NAT
Gateway.
Question: 1616
Which Alibaba Cloud feature allows customers to import their own cryptographic key
material into KMS?
A. BYOK (Bring Your Own Key)
B. SSE-KMS default keys
C. Client-side encryption only
D. TDE key import
Answer: A
Explanation: BYOK enables customers to maintain control over key material by
importing keys into Alibaba Cloud KMS, improving trust and compliance.
Question: 1617
A logistics firm's 250 on-premises hosts report network latency metrics to CloudMonitor,
with dashboards for global views and alerts on >200ms spikes. Apsara Stack governance
logs ACK pod evictions for audits. Which correct?
A. CloudMonitor Hybrid latency metrics, global dashboards, spike alerts
B. Apsara Stack logging for ACK pod evictions in governance audits
C. CloudMonitor regional-only views
D. Apsara Stack no eviction logging
Answer: A, B
Explanation: CloudMonitor Hybrid collects network latency from hybrid agents, renders
global dashboards, and triggers alerts for spikes over 200ms to ensure logistics visibility.
Apsara Stack captures detailed logs of ACK pod evictions for comprehensive governance
and audit trails.
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