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AWS Certified Solutions Architecture - Associate (SAA-C03)
AWS Certified Solutions Architecture - Associate (SAA-C03)

Practice Test #1

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1
Frage 1

A global streaming media company operates over 250 video streaming platforms across different regions. The company needs to process approximately 25 TB of user viewing behavior and interaction data daily to optimize content recommendations and user experience. The solution must handle high-volume real-time data ingestion, provide reliable data transmission, and enable efficient analytics processing for the large-scale streaming data. What should a solutions architect recommend to ingest and process the streaming behavior data?

AWS Data Pipeline is primarily for scheduled/batch data movement and orchestration, not high-volume real-time streaming ingestion. While S3 + EMR can analyze large datasets, the ingestion layer here is the weak point: Data Pipeline does not provide the same real-time buffering, scaling, and replay semantics as Kinesis. This option also increases operational complexity for near-real-time requirements.

An Auto Scaling group of EC2 instances to capture and forward streaming events is a DIY ingestion approach that is harder to scale reliably and operate (capacity planning, backpressure handling, retries, ordering, and failure recovery). It can work, but it is not the most appropriate managed pattern for 25 TB/day of real-time telemetry. Kinesis provides these capabilities natively with less operational overhead.

Amazon CloudFront is designed to cache and deliver content with low latency; it is not intended to store or collect user interaction telemetry as a primary data ingestion mechanism. Triggering Lambda from S3 object creation implies batch/object-based ingestion rather than continuous streaming, and it can create scaling and latency challenges at very high volumes. This is an architectural mismatch for real-time behavior analytics.

Kinesis Data Streams provides scalable, durable real-time ingestion for large volumes of event data from many sources. Kinesis Data Firehose then reliably delivers the stream to an S3 data lake with automatic scaling, buffering, retries, and optional transformation. From S3, loading into Amazon Redshift supports efficient large-scale analytics. This directly matches the requirements for real-time ingestion, reliable transmission, and scalable analytics.

Fragenanalyse

Core Concept: This question tests designing a high-throughput, reliable streaming ingestion and analytics pipeline. The key AWS services are Amazon Kinesis Data Streams (real-time ingestion and buffering), Amazon Kinesis Data Firehose (managed delivery to storage/analytics destinations), Amazon S3 (durable data lake), and Amazon Redshift (analytics/warehouse). Why the Answer is Correct: With ~25 TB/day across 250+ platforms, the company needs scalable, near-real-time ingestion with durable buffering and reliable delivery. Kinesis Data Streams is purpose-built for high-volume event ingestion with ordered records per shard, retention for replay, and horizontal scaling via shards (or on-demand mode). Kinesis Data Firehose then provides a fully managed, reliable delivery layer to land data into an S3 data lake with batching, retries, and optional transformation, minimizing operational overhead. From S3, data can be loaded into Redshift (e.g., COPY from S3) for large-scale behavioral analytics and recommendation feature generation. Key AWS Features: - Kinesis Data Streams: shard-based scaling (or on-demand), multiple consumers, enhanced fan-out, retention for reprocessing, and integration with IAM/KMS. - Kinesis Data Firehose: automatic batching/compression/encryption, retry logic, S3 delivery, and optional Lambda-based transformation. - S3 data lake: high durability, lifecycle policies, partitioned storage for efficient downstream queries. - Redshift: columnar storage and MPP for fast aggregations; COPY from S3 for high-throughput loads. Common Misconceptions: Data Pipeline and DIY EC2 ingestion can look viable, but they are not optimized for real-time streaming at this scale and add significant operational burden. CloudFront is a content delivery/cache service, not an event ingestion system; using it for behavior telemetry is an architectural mismatch. Exam Tips: When you see “high-volume real-time ingestion” plus “reliable transmission” and “analytics,” think Kinesis (Streams for ingestion/buffering, Firehose for managed delivery) + S3 as the landing zone. Pair with Redshift/EMR/Athena depending on analytics needs; Redshift is a common choice for structured behavioral analytics at scale.

2
Frage 2

A company runs SQL Server on EC2 with daily EBS snapshots. A cleanup script accidentally deleted all snapshots. They need to prevent data loss without keeping snapshots forever. Provide a safety net for accidental deletions with minimal development. Which solution meets these requirements with the LEAST development effort?

Denying ec2:DeleteSnapshot in IAM can reduce accidental deletions for a specific principal, but it’s not a reliable safety net. The script could run under another role, an admin could still delete, and it doesn’t provide recovery if deletion happens. It also conflicts with the requirement to allow deletions (not keep snapshots forever) because you’d need exceptions and more policy management.

Copying snapshots to another Region is primarily a disaster recovery strategy for regional outages, not an accidental-deletion safety net. If the same automation or operator deletes snapshots in both Regions (or if permissions allow), you can still lose them. It also adds ongoing cost and operational complexity (copy schedules, monitoring, retention management) compared to a simple recycle bin rule.

EBS Snapshot Recycle Bin retention rules are designed specifically to protect against accidental snapshot deletion. With a 7-day retention rule for all snapshots, deleted snapshots remain recoverable during that window and are then permanently removed, meeting the “don’t keep forever” requirement. This is minimal development: configure the rule once and use restore when needed.

EBS snapshots are not objects you can copy directly into an S3 bucket and then choose S3 Standard-IA. Snapshots are stored and managed by the EBS snapshot service. While some AWS services can export certain data to S3, “copy snapshots to S3 Standard-IA” is not a valid native mechanism for EBS snapshot retention and recovery in this context.

Fragenanalyse

Core Concept - The question is testing AWS Backup/Amazon EBS data protection controls that provide resilience against accidental deletion, specifically the EBS Snapshot Recycle Bin feature (part of EBS snapshot management) and retention-based recovery. This aligns with resilient architecture principles: recoverability, controlled retention, and minimizing operational risk. Why the Answer is Correct - A 7-day EBS Snapshot Recycle Bin retention rule creates a “safety net” so that if snapshots are accidentally deleted (by a script or user), they are retained in the Recycle Bin and can be restored during the retention window. This directly addresses the incident (accidental deletion of all snapshots) while also meeting the requirement to avoid keeping snapshots forever. It also requires minimal development: you configure a retention rule once, rather than redesigning backup workflows. Key AWS Features - EBS Snapshot Recycle Bin lets you set retention rules (by tags or for all snapshots in the account/Region) so deleted snapshots are recoverable until the retention period expires. This is purpose-built for accidental deletions and complements (not replaces) normal snapshot lifecycle policies. It’s an account/Region-level control and is operationally simple compared to building cross-Region copy pipelines. Common Misconceptions - Denying snapshot deletion in IAM (Option A) seems like it prevents deletion, but it’s brittle: the cleanup script might run under a different role, an admin could still delete, and it doesn’t help if deletion already occurred or if you need legitimate deletions. Cross-Region copies (Option B) improve disaster recovery, but they don’t inherently protect against accidental deletion unless you also protect the copies with separate controls; plus it adds cost and operational overhead. Copying “snapshots to S3 Standard-IA” (Option D) is not how EBS snapshots work; snapshots are managed by EBS and you can’t directly tier them to S3 storage classes. Exam Tips - When you see “accidental deletion” + “don’t keep forever” + “least development,” look for managed retention/recovery features: EBS Snapshot Recycle Bin, AWS Backup Vault Lock (for backups), and lifecycle policies. Choose the option that directly provides recoverability after deletion with time-bound retention and minimal custom automation.

3
Frage 3

A financial services company operates a critical file exchange system for processing daily transaction reports from 50+ partner banks. The system currently uses two Amazon EC2 instances with elastic IP addresses running FTP services, backed by shared storage. The system processes approximately 10,000 files daily, each ranging from 100MB to 2GB in size. The company needs to migrate to a serverless architecture that can handle peak loads of 15,000 IOPS during business hours (9 AM - 5 PM EST) and provide enterprise-grade security controls. The solution must support file transfers from specific partner bank IP ranges and maintain granular user access control for compliance auditing. Which solution will best meet these high-performance and security requirements?

Incorrect. AWS Transfer Family does not use Amazon EBS as a storage backend, so attaching an io2 EBS volume to a Transfer Family endpoint is not a supported architecture. EBS is block storage intended for EC2 and similar compute-attached use cases, not for managed Transfer Family storage integration. In addition, the option specifies FTP rather than SFTP, which does not meet the implied enterprise-grade security expectations for a financial services workload unless explicitly required.

Incorrect. AWS Transfer Family can use Amazon EFS as a backend, so this option is closer than A or D, but it is not the best answer for a serverless high-scale partner file exchange workload. EFS introduces file-system performance design considerations and is generally less straightforward than S3 for large-scale external file exchange, while the question does not require POSIX semantics that would justify EFS. The wording about elastic IP addresses is also problematic because Transfer Family endpoint networking is managed differently, and the option is less clean and less aligned with the simplest scalable serverless design than S3-backed Transfer Family.

Correct. AWS Transfer Family with SFTP provides a fully managed, serverless file transfer endpoint so the company no longer needs to operate EC2-based FTP servers. Using Amazon S3 as the backend is ideal for large daily file volumes and variable throughput because S3 scales automatically and does not require provisioning IOPS or capacity for performance. Granular user access can be implemented with IAM roles and policies that restrict users to specific buckets or prefixes, while encryption and service logging support compliance and auditing requirements. The only caveat is that strict source-IP filtering is most directly implemented with a VPC-hosted endpoint and security groups, but among the choices this is still the best overall architecture.

Incorrect. A Transfer Family endpoint placed in a private subnet behind a NAT gateway would not be reachable inbound from external partner banks on the internet. NAT gateways are used for outbound internet access from private resources, not for accepting inbound partner connections or enforcing source-IP allow lists. Although S3 and a custom identity provider could satisfy storage and authentication requirements, the networking design as stated fails the external access requirement.

Fragenanalyse

Core Concept: This question tests selection of a fully managed file transfer service that is serverless, highly scalable for large file volumes, and secure enough for financial-services partner integrations. The best fit is AWS Transfer Family using SFTP with Amazon S3 as the backend, because S3 provides virtually unlimited scale without provisioning storage performance and Transfer Family provides managed user access controls and logging. Why correct: Option C is the best answer because it uses AWS Transfer Family with SFTP, which is a managed service that removes the need to run EC2-based FTP servers. Amazon S3 is the most appropriate backend for a serverless architecture handling many large files, and it avoids the need to size or provision IOPS like block or file storage would. Granular access can be enforced with IAM roles and policies scoped to specific buckets or prefixes, and encryption plus logging support compliance requirements. Key features: - AWS Transfer Family supports managed SFTP endpoints without managing servers. - Amazon S3 provides durable, massively scalable object storage for large file exchange workloads. - IAM policies can restrict each user to specific S3 prefixes for least-privilege access. - S3 default encryption and AWS Transfer Family logging support security and audit requirements. - IP-based restrictions can be implemented with a VPC-hosted endpoint and security groups when strict source-IP filtering is required. Common misconceptions: - EBS cannot be used as a Transfer Family backend. - NAT gateways do not provide inbound internet access control for partner connections. - CloudTrail records API activity, but detailed transfer/session visibility typically comes from Transfer Family logging and related service logs. - S3 Transfer Acceleration applies to direct S3 access, not to clients connecting through AWS Transfer Family. Exam tips: When the question emphasizes serverless managed file transfer, external partner access, large file volumes, and granular permissions, think AWS Transfer Family with S3 unless a clearly valid EFS-specific requirement exists. Eliminate answers that propose unsupported storage backends or incorrect networking patterns. Prefer SFTP over FTP for sensitive financial workloads unless the protocol requirement explicitly says otherwise.

4
Frage 4

A healthcare company operates a medical imaging analysis application that processes X-ray and MRI scans. The application frequently stores and retrieves large medical image files from Amazon S3 buckets within the same AWS Region. The IT team has observed that monthly data transfer charges have increased by 40% over the past quarter. The solutions architect needs to implement a cost-effective solution to minimize data transfer fees while maintaining secure access to the S3 buckets for medical image processing. How can the solutions architect meet this requirement?

API Gateway is for building and managing APIs, not for routing generic S3 API calls from workloads to S3 to reduce data transfer charges. Placing API Gateway in a subnet is also conceptually incorrect (API Gateway is a managed regional service, not deployed into your VPC unless using private integrations). It would add request-based costs and complexity and does not provide the direct private S3 routing benefit of a gateway endpoint.

A NAT gateway in a public subnet allows private subnets to reach the internet/AWS public endpoints, including S3, but it introduces NAT gateway hourly charges and per-GB data processing fees. For large medical images, NAT processing costs can be substantial and often the root cause of rising bills. Also, you don’t attach an “endpoint policy” to a NAT gateway; endpoint policies apply to VPC endpoints.

Putting the application in a public subnet and using an internet gateway sends S3 traffic over public IP routing paths. This does not minimize cost and can increase security risk by expanding the attack surface. It also doesn’t provide fine-grained network-level controls like VPC endpoint policies and bucket policies requiring a specific VPC endpoint. This is generally the opposite of best practice for healthcare workloads.

An S3 VPC gateway endpoint provides private connectivity from the VPC to S3 without NAT or IGW, typically reducing costs by avoiding NAT gateway data processing charges and improving security by keeping traffic on the AWS network. You can attach an endpoint policy to restrict access to only the required medical imaging buckets and actions, and reinforce it with S3 bucket policies requiring aws:SourceVpce.

Fragenanalyse

Core Concept: This question tests how to reduce Amazon S3 data transfer costs and improve security for private connectivity from a VPC to S3. The key service is an Amazon S3 VPC gateway endpoint (AWS PrivateLink for S3 uses gateway endpoints, not interface endpoints). Why the Answer is Correct: An S3 VPC gateway endpoint provides private, direct connectivity between resources in a VPC (EC2, ECS, EKS, Lambda in VPC) and Amazon S3 without traversing the public internet, without using an internet gateway (IGW), and without using a NAT gateway. This eliminates NAT gateway data processing charges and reduces exposure to internet paths. For workloads that “frequently store and retrieve large files,” avoiding NAT gateway per-GB processing fees is often the biggest cost win. The endpoint is regional and highly available, and traffic stays on the AWS network. Key AWS Features: 1) Gateway endpoint route table entries: You associate the endpoint with VPC route tables so that traffic destined for S3 prefixes is routed to the endpoint. 2) Endpoint policies: You can restrict access to only the required medical imaging buckets and actions (e.g., s3:GetObject, s3:PutObject) and even enforce conditions (aws:PrincipalArn, s3:prefix, etc.). 3) Defense-in-depth: Combine endpoint policy with S3 bucket policies that require access via the VPC endpoint (aws:SourceVpce) and IAM least privilege. This is aligned with AWS Well-Architected (Cost Optimization + Security pillars). Common Misconceptions: Many assume “same Region S3 access” is always free. While S3 request costs and in-Region data transfer patterns vary, a common driver of increased charges is routing S3 traffic through a NAT gateway (incurs NAT data processing per GB) or other egress paths. Another misconception is that API Gateway or public subnets/IGW reduce cost; they typically add cost and do not provide the private routing benefit. Exam Tips: When you see “reduce data transfer fees to S3 from within a VPC” and “keep access secure/private,” think “S3 gateway endpoint.” If the option mentions NAT gateway for S3 access, it’s usually a red flag for cost. Also look for “endpoint policy” and “bucket policy with aws:SourceVpce” as the secure pattern.

5
Frage 5

An e-learning platform operates a multi-tier educational content delivery system using Amazon Linux EC2 instances behind a Network Load Balancer. The infrastructure runs in an Auto Scaling group distributed across three Availability Zones. The platform experiences significant scaling events when students download large video lectures and PDF materials during peak study hours (6-10 PM), causing the system to provision additional On-Demand instances to handle the increased load. The platform serves approximately 15,000 concurrent students and needs to reduce infrastructure costs while maintaining low latency for content delivery. The static educational content (videos, PDFs, images) accounts for 80% of the total bandwidth usage. What should a solutions architect recommend to redesign the platform MOST cost-effectively?

Savings Plans can reduce compute cost for steady-state, predictable EC2 usage, but they do not address the root cause: heavy static content bandwidth driving scale-out events. Peak demand (6–10 PM) is spiky and may not be fully covered by a commitment without overcommitting. Also, Savings Plans don’t reduce latency or offload traffic from the instances; they only discount eligible compute usage.

Spot Instances with a mixed instances policy can lower costs for burst capacity, but it introduces interruption risk and still keeps static content delivery on EC2. For large video/PDF downloads, the main cost driver is data transfer and origin load, not just instance-hours. Spot can help, but it’s not the MOST cost-effective redesign compared to moving static delivery to CloudFront/S3.

CloudFront in front of S3 is the best redesign because it offloads 80% static bandwidth from EC2, reduces Auto Scaling events, and improves latency via edge caching. S3 provides low-cost, highly durable storage for videos and PDFs, while CloudFront reduces origin egress and request load. Use OAC to secure the bucket, caching policies/TTLs, and optionally signed URLs/cookies for protected educational content.

API Gateway + Lambda is not suitable for serving large static assets like videos and PDFs at scale. Lambda has payload/streaming constraints and would be cost-inefficient for high-bandwidth delivery; API Gateway also adds per-request costs and isn’t a CDN. This option increases complexity and cost while not providing the edge caching and optimized delivery that CloudFront offers.

Fragenanalyse

Core Concept: This question tests cost-optimized delivery of predominantly static content at scale. The key services are Amazon CloudFront (CDN) with an Amazon S3 origin, offloading bandwidth and request load from EC2/Auto Scaling while improving latency via edge caching. Why the Answer is Correct: Because 80% of bandwidth is static (videos, PDFs, images), the most cost-effective redesign is to move that content out of the EC2 fleet and serve it through CloudFront backed by S3. CloudFront caches content at edge locations close to students, reducing origin fetches and dramatically lowering EC2 data transfer and compute required during 6–10 PM spikes. This reduces scaling events (fewer On-Demand instances) and maintains or improves low latency for 15,000 concurrent users. S3 provides highly durable, low-cost storage; CloudFront provides global distribution and optimized delivery. Key AWS Features / Best Practices: Use an S3 bucket as the origin with appropriate storage classes (e.g., S3 Standard for hot content; consider S3 Intelligent-Tiering for variable access patterns). Enable CloudFront caching with suitable TTLs, cache policies, and compression. Use Origin Access Control (OAC) to restrict direct S3 access and serve content only through CloudFront. Optionally use signed URLs/cookies for protected course materials and enable HTTP/2/HTTP/3 for performance. This aligns with AWS Well-Architected Cost Optimization (reduce demand, use managed services) and Performance Efficiency (edge caching). Common Misconceptions: It’s tempting to focus on instance purchasing (Savings Plans/Spot) because scaling is visible, but that treats the symptom (compute cost) rather than the primary driver (static bandwidth). Also, Lambda/API Gateway is not intended for large static file delivery and would be expensive and operationally awkward. Exam Tips: When a workload is dominated by static content and bandwidth, think “S3 + CloudFront” first. If the question mentions low latency for global or large-scale downloads, a CDN is usually the best architectural lever. Purchase models (Savings Plans/Spot) are secondary optimizations after you reduce load on compute and shift to purpose-built managed services.

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6
Frage 6

A healthcare organization is using Amazon S3 to store sensitive patient medical records and compliance documentation. The S3 bucket implements bucket policies that restrict access to specific healthcare compliance team IAM users following the principle of least privilege. The healthcare organization's administrators are concerned about accidental deletion of critical patient records in the S3 bucket and need to implement a more secure solution to protect these documents from unintended removal. What should a solutions architect recommend to secure the patient medical records?

Correct. S3 Versioning preserves prior versions and turns deletes into delete markers, enabling recovery of accidentally deleted patient records. MFA Delete adds an additional control requiring MFA to permanently delete object versions or suspend versioning, reducing the risk of irreversible deletion due to human error or compromised credentials. This directly addresses “accidental deletion” and “unintended removal.”

Incorrect. Enabling MFA for IAM user sign-in improves authentication security but does not inherently prevent object deletion or provide a recovery mechanism. Users (or applications) can still delete objects if allowed by policy, and if deletion occurs, the data is gone unless versioning is enabled. MFA on users also does not specifically enforce MFA for delete operations in S3.

Incorrect. S3 Lifecycle policies are configured on buckets (or prefixes/tags), not on IAM user accounts, and they manage transitions/expirations rather than acting as an IAM-style deny control. Denying s3:DeleteObject should be done via IAM/bucket policies, but that would block legitimate deletions and still wouldn’t help recover from accidental overwrites. It also doesn’t provide a robust recovery path.

Incorrect. SSE-KMS encryption protects data confidentiality and can restrict who can decrypt/read objects, but it does not prevent deletion of objects. A user with s3:DeleteObject permission can still delete encrypted objects regardless of KMS permissions because delete does not require decrypt. This option addresses access to content, not protection from unintended removal.

Fragenanalyse

Core Concept: This question tests Amazon S3 data protection controls against accidental or unintended deletion. The key S3 features are Versioning (to retain prior object versions) and MFA Delete (to require multi-factor authentication to permanently delete versions or suspend versioning). Why the Answer is Correct: Enabling S3 Versioning ensures that when an object is deleted, S3 does not immediately remove the data; instead, it adds a delete marker and preserves prior versions. This allows administrators to recover patient records by removing the delete marker or restoring a previous version. Adding MFA Delete further hardens deletion protection by requiring MFA for versioned object deletions and for changing the versioning state, reducing the risk that a compromised credential or an operator mistake can permanently remove critical records. This is especially relevant for healthcare records where retention and recoverability are essential. Key AWS Features: 1) S3 Versioning: Keeps multiple variants of an object in the same bucket, enabling rollback and recovery from accidental deletes/overwrites. 2) MFA Delete: Requires MFA to permanently delete object versions or suspend versioning (configured at the bucket level, typically via the root user or authorized process). 3) Least privilege bucket policies remain useful, but they do not inherently provide recoverability once deletion is allowed. Common Misconceptions: It’s common to think “enable MFA on IAM users” is enough, but MFA on sign-in does not prevent programmatic deletes if credentials are misused, nor does it provide recovery. Another misconception is that encryption (SSE-KMS) prevents deletion; encryption protects confidentiality, not availability or recoverability. Lifecycle policies also cannot be attached to IAM users and are not designed as an access-control mechanism. Exam Tips: For “accidental deletion” in S3, look first for Versioning. If the question emphasizes preventing permanent deletion or requiring extra assurance for deletes, add MFA Delete. For compliance/immutability requirements, also consider S3 Object Lock (WORM) in other questions, but here the best match among options is Versioning + MFA Delete. References: Amazon S3 Versioning and MFA Delete documentation; AWS Well-Architected Framework (Security and Reliability pillars: protect data, enable recovery).

7
Frage 7

A gaming company runs a resource-intensive multiplayer game on Amazon ECS with AWS Fargate. The game must be available 24/7 with short bursts of high traffic. The solution must ensure high availability and handle traffic bursts cost-effectively. Which solution will meet these requirements MOST cost-effectively?

Using only Fargate with load testing and CloudWatch rightsizing can improve performance and reduce some overprovisioning, but it does not introduce a cheaper burst capacity tier. You still pay on-demand Fargate rates for both baseline and spikes. Also, “third-party load testing” is not an architectural lever for ongoing cost-effective burst handling; it’s a one-time validation activity, not a scaling/cost strategy.

This is the best fit: run the always-on baseline on regular Fargate for high availability, and scale out burst capacity on Fargate Spot to reduce costs during spikes. ECS capacity providers support base/weight strategies so the service prefers Spot for additional tasks while maintaining a guaranteed baseline. If Spot is interrupted or unavailable, the baseline remains on Fargate and ECS can fall back to Fargate for replacements.

Running steady state on Fargate Spot is risky for a 24/7 game because Spot tasks can be interrupted with short notice and Spot capacity can be unavailable. Even if you use on-demand Fargate for bursts, the core always-on capacity would still be subject to interruption, which conflicts with the availability requirement. This option optimizes cost but sacrifices reliability where it matters most.

Compute Optimizer can help recommend CPU/memory settings to reduce waste, but it does not solve the key requirement of cost-effective burst handling. With only Fargate, burst traffic still incurs full on-demand pricing. Also, Compute Optimizer support and recommendation quality for ECS/Fargate may vary; regardless, rightsizing alone is typically less impactful than using Spot for overflow capacity in bursty workloads.

Fragenanalyse

Core Concept: This question tests cost-optimized, highly available scaling on Amazon ECS with AWS Fargate using ECS capacity providers and the tradeoffs between Fargate (on-demand) and Fargate Spot (spare capacity with interruption risk). Why the Answer is Correct: The game must be available 24/7 (steady baseline capacity must be reliable) and must handle short, bursty spikes cost-effectively. The most cost-effective pattern is to run the steady-state service on regular Fargate to ensure availability and predictable capacity, then use Fargate Spot for burst capacity because it is significantly cheaper. If Spot capacity is interrupted or unavailable, the baseline service remains healthy on on-demand Fargate, preserving 24/7 availability. Key AWS Features: ECS capacity providers let you define a strategy (base and weight) across Fargate and Fargate Spot. A common approach is: - Base: N tasks on Fargate (guaranteed baseline) - Weight: additional tasks preferentially on Fargate Spot during scale-out This integrates with ECS Service Auto Scaling (target tracking on CPU/memory or ALB request count). For resilience, use multiple subnets across multiple AZs, and ensure the service has appropriate health checks and deployment settings. Spot interruption handling is inherent: ECS will stop interrupted Spot tasks and replace them according to desired count; with a mixed strategy, replacements can land on Fargate if Spot is constrained. Common Misconceptions: Options focused on “rightsizing” (CloudWatch/Compute Optimizer) can reduce waste but do not directly address burst cost optimization. Another common trap is putting steady state on Spot: it’s cheaper but violates the 24/7 availability requirement because Spot can be interrupted with little notice. Exam Tips: When you see “steady state + bursts” and “most cost-effective,” think “baseline on on-demand, burst on Spot,” especially for stateless or horizontally scalable workloads. For ECS/Fargate, the exam-friendly mechanism is an ECS capacity provider strategy combining Fargate and Fargate Spot with Auto Scaling. Always map Spot usage to non-critical or overflow capacity unless the question explicitly tolerates interruptions.

8
Frage 8
(2 auswählen)

A financial services company operates a real-time trading platform on-premises consisting of containerized microservices running on multiple Linux servers. The platform connects to a MySQL database cluster that stores transaction data and user portfolios. The current infrastructure requires significant manual intervention for scaling during peak trading hours (market open/close), and the IT team spends 60% of their time on infrastructure maintenance rather than feature development. The company wants to reduce operational overhead, eliminate capacity planning concerns, and enable automatic scaling during trading peaks. The solution must maintain high availability and reduce infrastructure management burden while supporting containerized applications. Which combination of actions should the solutions architect take to accomplish this? (Choose two.)

Correct. Amazon RDS for MySQL with Multi-AZ provides a managed database with synchronous replication to a standby in a different AZ and automatic failover. It reduces operational overhead (patching, backups, monitoring integration) compared to self-managed MySQL clusters on servers. This directly supports the requirement for high availability and reduced infrastructure management for the stateful transaction datastore.

Incorrect. Running containers on Amazon EC2 Auto Scaling groups can scale capacity, but it does not eliminate capacity planning or infrastructure management. The team would still manage EC2 instances, AMIs, OS patching, container runtime/agent updates, and cluster sizing. This conflicts with the goal of reducing ops burden and removing manual intervention during peak trading periods.

Incorrect. Amazon ElastiCache for Redis can reduce database load and improve latency, which may help a trading platform, but it does not address the primary requirements: eliminating capacity planning and reducing infrastructure management. It also introduces cache consistency/invalidation considerations and additional architecture complexity. The question does not indicate a read-heavy bottleneck that necessitates caching.

Incorrect. Amazon CloudWatch monitoring and alarms are important for observability, but by themselves they do not provide automatic scaling or reduce infrastructure maintenance. Alarms can trigger actions (like scaling policies), yet the option does not include implementing those scaling mechanisms. Monitoring is complementary, not the core solution to the stated operational and scaling requirements.

Correct. Migrating containers to Amazon ECS on AWS Fargate removes the need to manage servers and cluster capacity. ECS Service Auto Scaling can automatically scale tasks based on CPU/memory or custom metrics to handle predictable market open/close spikes. This meets the requirements for automatic scaling, reduced operational overhead, and eliminating capacity planning while continuing to run containerized microservices.

Fragenanalyse

Core Concept: This question tests migrating an on-prem, container-based, peak-driven workload to managed AWS services that provide high availability and automatic scaling with minimal operations. The key services are AWS Fargate (serverless containers) with Amazon ECS for microservices, and Amazon RDS for MySQL with Multi-AZ for a managed, highly available relational database. Why the Answer is Correct: Option E (ECS on Fargate) removes the need to manage EC2 hosts, patch OSs, or perform cluster capacity planning. You define task CPU/memory and use ECS Service Auto Scaling (target tracking on CPU/memory or custom CloudWatch metrics) to scale out during market open/close and scale in afterward. This directly addresses “eliminate capacity planning concerns” and “reduce infrastructure management burden” while supporting containers. Option A (RDS for MySQL Multi-AZ) offloads database administration tasks (backups, patching, monitoring integrations) and provides high availability via synchronous replication to a standby in another AZ with automatic failover. This reduces operational overhead and improves resilience for transaction and portfolio data. Key AWS Features: - AWS Fargate: serverless compute for containers; no EC2 management; integrates with ECS services, IAM roles for tasks, and ALB. - ECS Service Auto Scaling: target tracking policies; scheduled scaling can also match predictable market events. - Amazon RDS for MySQL Multi-AZ: automated failover, managed backups, maintenance windows, and CloudWatch metrics. - Resiliency best practice: multi-AZ design for stateful components (database) and horizontally scalable stateless services (microservices). Common Misconceptions: EC2 Auto Scaling groups (Option B) do scale, but still require AMI lifecycle management, patching, cluster sizing, and capacity planning—contrary to the goal of minimizing infrastructure management. ElastiCache (Option C) can improve performance, but it does not eliminate scaling/ops burden by itself and adds cache-invalidation complexity; it’s not required by the prompt. CloudWatch alarms (Option D) improve observability but don’t inherently provide automatic scaling or reduce maintenance without pairing with scaling actions. Exam Tips: When requirements emphasize “reduce operational overhead,” “no capacity planning,” and “containers,” default to ECS on Fargate (or EKS on Fargate) over EC2-based container hosting. For MySQL needing high availability with minimal admin, choose RDS Multi-AZ. Map each requirement explicitly: serverless containers for compute ops reduction; managed Multi-AZ database for resilient state.

9
Frage 9

A global e-commerce platform is launching operations in 5 new regions simultaneously. The platform currently serves 2 million customers and expects to reach 8 million customers within 6 months. A solutions architect needs to establish access management for 150+ new employees across different teams (Development, Operations, Marketing, Finance, Customer Support). The architect plans to organize users into IAM groups by team function. Which additional action is the MOST secure way to grant permissions to the new users?

SCPs are an AWS Organizations feature used to define account-level guardrails (maximum permissions) for member accounts or OUs. They do not grant permissions to users; they only restrict what IAM policies could allow. SCPs can be part of a secure multi-account strategy, but they are not the correct mechanism to grant team-based permissions to new IAM users.

IAM roles cannot be attached to IAM groups. Roles are assumed via STS by users, services, or federated identities, and you can allow users to assume roles by granting sts:AssumeRole in a policy. While role assumption is a valid pattern, the statement “attach the roles to the respective IAM groups” is not an IAM capability, making this option incorrect.

Creating least-privilege IAM policies and attaching them to IAM groups is the standard, secure, and scalable way to grant permissions to many employees by job function. Users inherit permissions through group membership, simplifying onboarding/offboarding and reducing configuration errors. This directly implements least privilege and aligns with IAM best practices for managing human access.

Permissions boundaries set the maximum permissions a role (or user) can ever receive, which is useful for delegated administration and preventing privilege escalation. However, boundaries do not grant permissions by themselves; you still need identity-based policies. In this scenario, the primary need is to grant team permissions securely via groups, so boundaries are not the best “additional action” compared to attaching least-privilege policies to groups.

Fragenanalyse

Core Concept: This question tests AWS IAM identity-based access management best practices: assigning permissions using IAM policies attached to IAM groups, following least privilege, and scaling access control for many users. It also implicitly tests understanding of what IAM groups can and cannot do (groups cannot have roles “attached” to them). Why the Answer is Correct: The most secure and standard approach for granting permissions to many new employees organized by job function is to create least-privilege IAM policies and attach those policies to the corresponding IAM groups (e.g., Dev, Ops, Finance). Users inherit permissions from group membership, which centralizes management, reduces drift, and supports rapid onboarding/offboarding. This aligns with AWS security best practices and the AWS Well-Architected Security Pillar: implement least privilege and manage identities at scale. Key AWS Features: - IAM Groups: permission management at scale by attaching policies to groups and adding/removing users. - Customer-managed IAM Policies: reusable, version-controlled policies tailored to each team’s job functions. - Least privilege techniques: start with minimal actions/resources, use resource-level permissions where possible, and add conditions (e.g., aws:RequestedRegion, MFA conditions, source IP, tag-based access control). - Separation of duties: distinct policies per team, avoiding broad shared permissions. Common Misconceptions: - SCPs (Option A) are for AWS Organizations to set guardrails on accounts/OUs, not for granting permissions to IAM users. SCPs don’t grant; they only limit what identity policies could allow. - “Attach roles to groups” (Option B) is not how IAM works; groups can’t assume roles automatically. Roles are assumed by principals (users, services, federated identities) via sts:AssumeRole. - Permissions boundaries (Option D) are powerful but are primarily for delegating administration and limiting maximum permissions for roles/users; they don’t replace the need to grant permissions via identity policies and are not the primary “most secure” next step given the scenario. Exam Tips: - Remember: IAM policies grant permissions; SCPs and permissions boundaries set maximum limits. - For employee access, prefer IAM Identity Center (SSO) in real-world designs, but on exams, “IAM groups + least-privilege policies” is the canonical answer when groups are explicitly mentioned. - If an option suggests attaching roles to groups, treat it as a red flag—groups attach policies, not roles.

10
Frage 10

A company wants to configure its Amazon CloudFront distribution to use an SSL/TLS certificate. The company owns a domain name (e.g., 'www.example.com') and wants to use it instead of the default CloudFront domain name. The company needs to deploy a certificate for its custom domain and wants to avoid any additional costs. Which solution will deploy the certificate without incurring any additional costs? Which solution will deploy the certificate without incurring any additional costs?

Correct. CloudFront requires ACM certificates to be in us-east-1 (N. Virginia). Amazon-issued public certificates from ACM are provided at no additional cost (no certificate fee) and integrate directly with CloudFront. After DNS or email validation, the certificate can be attached to the distribution to enable HTTPS for www.example.com without extra certificate charges.

Incorrect. An Amazon-issued private certificate implies using ACM Private CA. ACM Private CA incurs additional costs (monthly CA fee and per-certificate charges). Also, private certificates are intended for internal PKI use and are not appropriate for public internet trust by default. Even though us-east-1 is the correct region for CloudFront, this option fails the “avoid additional costs” requirement.

Incorrect. Although an ACM public certificate is free, CloudFront can only use ACM certificates that are requested/imported in us-east-1. A certificate in us-west-1 will not appear as a selectable certificate for a CloudFront distribution. This is a common exam trap: the service is global, but the certificate must be in a specific region.

Incorrect. This option is wrong for two reasons: (1) ACM Private CA private certificates have additional costs, violating the “avoid any additional costs” requirement, and (2) CloudFront cannot use ACM certificates from us-west-1 anyway. Even if cost were ignored, the region constraint would still prevent using this certificate with CloudFront.

Fragenanalyse

Core Concept: This question tests how to use SSL/TLS certificates with Amazon CloudFront custom domain names (alternate domain names/CNAMEs) and how AWS Certificate Manager (ACM) pricing and regional requirements work for CloudFront. Why the Answer is Correct: To serve HTTPS for a custom domain like www.example.com on a CloudFront distribution, you must attach an ACM certificate (or an imported certificate) to the distribution. For CloudFront, ACM certificates must be requested (or imported) in the US East (N. Virginia) Region (us-east-1). Public ACM certificates are issued at no additional cost. Therefore, requesting an Amazon-issued public certificate in us-east-1 deploys the certificate for CloudFront without incurring additional certificate charges. Key AWS Features: - CloudFront Alternate Domain Names (CNAMEs): Lets CloudFront respond to requests for www.example.com instead of the default *.cloudfront.net domain. - ACM Public Certificates: Free to issue and renew when used with AWS services like CloudFront. - Regional requirement for CloudFront: CloudFront is a global service, but it only sources ACM certificates from us-east-1. - Validation: You typically validate domain ownership via DNS validation in Route 53 (or your DNS provider), which is operationally simpler and supports automatic renewal. Common Misconceptions: - “Any region works for CloudFront certificates”: Incorrect. Certificates in us-west-1 (or any region other than us-east-1) cannot be selected for a CloudFront distribution. - “Private certificates are also free”: Incorrect. ACM Private CA (used to issue private certificates) has ongoing costs (monthly CA fee and per-certificate charges). Also, private certificates are generally for internal/private PKI use, not public internet-facing CloudFront endpoints. Exam Tips: - Memorize: CloudFront + ACM certificate must be in us-east-1. - Prefer public ACM certs for internet-facing domains to avoid cost and complexity. - If you see “avoid additional costs,” eliminate ACM Private CA options. - When using a custom domain, remember you also need DNS (e.g., Route 53 ALIAS/AAAA) pointing to the CloudFront distribution, but the certificate selection is the key tested point here.

Erfolgsgeschichten(31)

이
이**Apr 25, 2026

Lernzeitraum: 1 month

시험문제보다 난이도가 있는편이고 같은문제도 조금 나왔습니다

C
C*********Mar 23, 2026

Lernzeitraum: 1 week

요구사항 정확히 인지하기(이거 젤중요 이 훈련이 제일 중요한듯), 오답노트 갈겨서 200문제만 확실히 해서 갔어요 실제 시험 지문은 훨씬 간단한데 난이도는 앱이랑 비슷하거나 더 낮았던것같아요 느낌상 탈락이었는데 통과해서 기쁘네요 큰 도움 되었습니다 감사해요!

소
소**Feb 22, 2026

Lernzeitraum: 1 week

그냥 문제 풀면서 개념들 GPT에 물어보면서 학습했어요 768점 턱걸이 합격,,

조
조**Jan 12, 2026

Lernzeitraum: 3 months

그냥 꾸준히 공부하고 문제 풀고 합격했어요 saa 준비생분들 화이팅!!

김
김**Dec 9, 2025

Lernzeitraum: 1 month

앱으로는 4일만에 몇 문제를 풀었는지 모르겠지만 1딜동안 aws 기본 개념부터 덤프로 시나리오 그려보고 하니까 합격했습니다. 시험은 생각보다 헷갈리게 나와서 당황했는데 30분 추가 테크로 flag한 지문들 다시 확인하니까 문제 없었습니다.

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