Tüm alıştırma soruları

1462 soru

Soru 1001Soru

A news agency hosts a dynamic web application on Amazon EC2 instances behind an Application Load Balancer (ALB). During breaking news events, traffic spikes significantly, occasionally causing backend database exhaustion and HTTP 503 Service Unavailable errors. The agency has created a static backup site in an Amazon S3 bucket. A solutions architect must design a highly resilient caching solution that automatically serves this static backup content globally with the lowest latency when the primary ALB is unavailable or failing. Which solution meets these requirements with the least operational complexity?

Cevabı ve açıklamayı göster

Cevap: Configure an Amazon CloudFront distribution with an origin group containing the ALB as the primary origin and the S3 bucket as the secondary origin. Set the origin group to fail over to the S3 bucket on 500, 502, 503, and 504 HTTP status codes.

Cevap

Configure an Amazon CloudFront distribution with an origin group containing the Application Load Balancer as the primary origin and the S3 bucket as the secondary origin, setting failover status codes to redirect traffic to the S3 bucket.
The correct solution uses an Amazon CloudFront origin group. By setting the Application Load Balancer as the primary origin and the Amazon S3 bucket as the secondary origin, CloudFront automatically catches HTTP server errors (such as 503 Service Unavailable) at the edge and routes requests to the backup S3 bucket. This provides automatic failover with minimal latency, leverages edge caching, and avoids client-side DNS propagation delays.

Adım Adım Çözüm

1
Identify the resilience and latency requirements.
The solution requires dynamic edge caching to minimize latency globally and automatic failover during origin outages without relying on slow DNS changes.
CloudFront distributions provide global edge caching, and CloudFront origin groups support active-passive origin failover.
2
Configure the CloudFront Origin Group.
An origin group is created with the Application Load Balancer as the primary origin and the Amazon S3 bucket as the secondary origin.
This allows CloudFront to fallback to the secondary origin if the primary origin is unreachable or returns error codes.
3
Define failover criteria based on HTTP response status codes.
CloudFront is configured to fail over when the primary origin returns 500, 502, 503, or 504 status codes.
This captures backend failures and database connection exhaustion issues immediately and serves static placeholder pages from the S3 bucket.

Anahtar Kavram

CloudFront Origin Groups allow solutions architects to configure origin failover for high availability and resilient content delivery.
Tahmini Süre:1m 30s
Soru 1002Soru

A pharmaceutical research company operates a clinical trial monitoring application. The application stores real-time patient telemetry data in an Amazon Aurora PostgreSQL DB cluster. The company requires a disaster recovery strategy across two AWS Regions. The database configuration must achieve a Recovery Point Objective (RPO) of less than 22 seconds and a Recovery Time Objective (RTO) of less than 22 minutes. Additionally, researchers in both regions need low-latency access to read the telemetry data. Which database configuration meets these requirements with the least operational complexity?

Cevabı ve açıklamayı göster

Cevap: Deploy an Amazon Aurora Global Database with the primary DB cluster in the main region and a secondary DB cluster in the recovery region.

Cevap

Deploy an Amazon Aurora Global Database with the primary DB cluster in the main region and a secondary DB cluster in the recovery region.
The correct database configuration is to deploy an Amazon Aurora Global Database. Aurora Global Databases use storage-based replication to copy data to secondary regions with a typical replication lag of less than 11 second, fulfilling the RPO constraint of less than 22 seconds. The secondary cluster allows read scaling with local low latency for remote users. In the event of a primary region outage, the secondary cluster can be promoted to a primary read-write cluster in less than 22 minutes, meeting the RTO constraint.

Adım Adım Çözüm

1
Analyze the disaster recovery constraints, specifically the Recovery Point Objective (RPO) of less than 22 seconds and the Recovery Time Objective (RTO) of less than 22 minutes.
The solution must support near real-time data replication (under 22 seconds) and rapid failover (under 22 minutes) between regions.
This filters out backup-and-restore or pilot-light strategies that introduce recovery delays.
2
Analyze the read scalability requirement for researchers in both regions to access data with low latency.
The target configuration must allow active read operations in the secondary region.
This requires a database engine that supports active read replicas or secondary active reader clusters in the remote region.
3
Compare Aurora Global Database capabilities against Amazon RDS cross-region replication.
Amazon Aurora Global Database provides storage-level replication with lag under 11 second and managed regional failover that takes less than 22 minutes, meeting all criteria with minimal operational overhead.
Aurora Global Database is the native AWS solution designed for low-latency multi-region read scaling and fast cross-region failover.

Anahtar Kavram

Amazon Aurora Global Database replication and regional failover capabilities.
Tahmini Süre:1m 30s
Soru 1003Soru

A logistics company is migrating its package tracking system and customer portal to AWS. The database tier has two main requirements:

1. A relational database to store package status updates, which must support high availability with a recovery time objective (RTO) of under 6060 seconds, while also handling heavy read traffic from customer queries.
2. A NoSQL session state store that experiences highly unpredictable, spiky traffic with sudden write bursts during peak holiday delivery seasons.

The company wants to minimize overall database costs while meeting all performance and availability requirements. Which of the following database configurations is the most cost-effective?

Cevabı ve açıklamayı göster

Cevap: Configure an Amazon RDS Multi-AZ DB Cluster with one primary and two readable standby DB instances for the tracking database, and use an Amazon DynamoDB table in On-Demand capacity mode for the session state store.

Cevap

Configure an Amazon RDS Multi-AZ DB Cluster with one primary and two readable standby DB instances for the tracking database, and use an Amazon DynamoDB table in On-Demand capacity mode for the session state store.
The configuration using an Amazon RDS Multi-AZ DB Cluster and DynamoDB On-Demand is the most cost-effective. A Multi-AZ DB Cluster provides high availability with automatic failover (meeting the low RTO requirement) using three instances total (one primary and two standby instances). Because both standby instances are readable, they can serve customer read traffic, eliminating the need for additional read replicas and reducing instance count by 25% compared to a Multi-AZ instance plus replicas setup. For the session state store, DynamoDB in On-Demand capacity mode is ideal for spiky, unpredictable workloads because it automatically scales to handle sudden bursts and charges only for the requests made, preventing expensive over-provisioning.

Adım Adım Çözüm

1
Analyze the high availability and read capacity requirements for the relational database.
High availability with an RTO of under 6060 seconds requires an automated synchronous failover mechanism, eliminating Single-AZ configurations. The workload requires at least two read endpoints to handle reporting query volume.
This establishes the baseline HA and scalability requirements for the tracking database.
2
Compare the cost and resource usage of different RDS Multi-AZ configurations.
An RDS Multi-AZ DB Cluster provides one primary and two readable standby instances (totaling 33 instances). An RDS Multi-AZ DB Instance with two separate Read Replicas requires one primary, one passive standby, and two read replicas (totaling 44 instances).
The Multi-AZ DB Cluster allows the standby instances to serve reads, reducing instance count and overall compute cost by 25%.
3
Determine the optimal capacity mode for the DynamoDB session state store.
Select DynamoDB On-Demand capacity mode to automatically scale and accommodate highly unpredictable, spiky traffic with sudden bursts.
Provisioned capacity mode requires either expensive over-provisioning to handle maximum peak bursts or risks throttling due to slow target tracking auto-scaling adjustments.

Anahtar Kavram

Cost-optimized database capacity planning and high-availability design
Soru 1004Soru

A logistics company is designing an automated route simulation platform. The platform receives route telemetry data files in an Amazon S3 bucket. A processing task must analyze each file to simulate traffic conditions and update a central tracking database. Each simulation must run sequentially in the exact chronological order the data is received to ensure state consistency. A single simulation run typically takes between 1212 to 2020 minutes to complete. The volume of incoming telemetry files is highly unpredictable, with periods of zero activity followed by sudden bursts of hundreds of uploads. The company needs to design a highly available, serverless, and cost-effective architecture.

Which TWO configurations should a solutions architect recommend to meet these requirements? (Select TWO.)

Geçerli olan tümünü seçin

Cevabı ve açıklamayı göster

Cevap: Configure an Amazon SQS FIFO queue to capture Amazon S3 Event Notifications, ensuring that telemetry files are processed in the strict chronological order they were uploaded.; Deploy the simulation workloads as containerized tasks using Amazon ECS on AWS Fargate, and configure Auto Scaling based on queue depth metrics.

Cevap

The correct configurations are using an Amazon SQS FIFO queue to capture S3 events in chronological order, and executing the simulations as containerized tasks on Amazon ECS with AWS Fargate using scaling based on queue depth metrics.
The correct configurations combine Amazon SQS FIFO queues to maintain strict chronological message ordering and Amazon ECS on AWS Fargate to handle long-running simulation workloads. Since simulations take 1212 to 2020 minutes, they exceed the 1515-minute execution limit of AWS Lambda, requiring a containerized serverless solution that can scale down to zero when idle to optimize costs.

Adım Adım Çözüm

1
Evaluate execution time requirements.
The simulation tasks run for 1212 to 2020 minutes. Since AWS Lambda functions have a maximum timeout limit of 1515 minutes, Lambda is not viable. AWS Fargate provides a serverless execution environment suitable for containerized long-running tasks.
Choosing a compute option that supports long-running execution without timing out is critical for successful completion.
2
Determine message ordering requirements.
The system must process simulations sequentially in the exact chronological order of file arrival. A standard Amazon SQS queue cannot guarantee this, making an Amazon SQS FIFO queue necessary to enforce ordering.
Strict chronological sequencing is required to prevent race conditions and preserve data consistency.
3
Implement scaling configuration for cost optimization.
To handle unpredictable traffic efficiently (scaling to zero when idle and scaling out during bursts), configure Auto Scaling for the Amazon ECS service using the queue depth metric from Amazon CloudWatch.
Basing scaling rules on SQS queue metrics ensures compute resources are provisioned only when workload backlog is present, minimizing idle costs.

Anahtar Kavram

Leveraging AWS Fargate for serverless workloads exceeding the AWS Lambda execution limit combined with SQS FIFO queues for strict ordering and cost-effective scaling.
Soru 1005Soru

A company is building a corporate internal application that runs on Amazon DynamoDB. The database experiences short, highly unpredictable spikes in query volume at random times throughout the day, followed by long periods of inactivity with no requests. The primary objective is to minimize database costs. Which capacity planning strategy is the most cost-effective for this workload?

Cevabı ve açıklamayı göster

Cevap: Configure the DynamoDB table with On-Demand capacity mode

Cevap

Configure the DynamoDB table with On-Demand capacity mode
The correct option is to configure the DynamoDB table with On-Demand capacity mode. This mode charges strictly per request (read/write request units) and does not incur any baseline storage or capacity charges when the database is idle. This makes it ideal and highly cost-effective for spiky, unpredictable workloads with long periods of zero traffic.

Adım Adım Çözüm

1
Analyze the workload characteristics and requirements
The database has highly unpredictable, short spikes in queries and long periods of inactivity, with a constraint to minimize cost.
Understanding workload patterns is necessary to select the correct database capacity mode.
2
Evaluate Amazon DynamoDB capacity modes against the workload profile
Provisioned capacity mode (with or without auto scaling) incurs minimum baseline costs even when the database is idle. On-Demand capacity mode charges per request and has zero idle cost.
Comparing capacity planning modes helps identify which option minimizes costs for idle periods while accommodating spikes.
3
Select the most cost-effective capacity strategy
DynamoDB On-Demand capacity mode matches the requirements perfectly as it charges only for requests served.
Determining the final configuration that satisfies the performance and cost optimization goals.

Anahtar Kavram

Selecting between DynamoDB On-Demand and Provisioned capacity modes for cost optimization of spiky, idle workloads
Tahmini Süre:45s
Soru 1006Soru

A company runs a web application where the frontend static assets (images, CSS, and JavaScript files) are stored in an Amazon S3 bucket, and the backend dynamic API is hosted on Amazon EC2 instances behind an Application Load Balancer (ALB). The company wants to use a single Amazon CloudFront distribution to serve both the static assets and the dynamic API to prevent Cross-Origin Resource Sharing (CORS) issues. The dynamic API responses are user-specific and must never be cached, while the static assets should be cached at the edge to maximize performance and minimize origin load. Which configuration should a solutions architect recommend to meet these requirements?

Cevabı ve açıklamayı göster

Cevap: Create a cache behavior for the path pattern `/api/*` with the ALB as the origin, and associate it with the Managed-CachingDisabled cache policy. Create a default cache behavior (`*`) with the S3 bucket as the origin, and associate it with the Managed-CachingOptimized cache policy.

Cevap

Create a cache behavior for the path pattern `/api/*` with the ALB as the origin, and associate it with the Managed-CachingDisabled cache policy. Create a default cache behavior (`*`) with the S3 bucket as the origin, and associate it with the Managed-CachingOptimized cache policy.
Configuring separate cache behaviors allows path-based routing in CloudFront. The path pattern `/api/*` takes precedence over the default behavior (`*`), routing dynamic traffic to the ALB with caching disabled, while the default behavior routes static requests to S3 with caching optimized. This solves CORS issues by serving both under the same domain, ensures dynamic data is always fresh, and caches static assets to minimize origin load.

Adım Adım Çözüm

1
Analyze the requirements for routing and caching dynamic vs static content.
The dynamic API `/api/*` needs to bypass caching entirely, while static assets under the default path `*` need to be cached.
This allows the application to serve both static and dynamic content under the same domain name, avoiding CORS issues.
2
Design the path-based cache behaviors in Amazon CloudFront.
Create a specific behavior for `/api/*` routed to the ALB, and a default behavior `*` routed to the S3 bucket.
CloudFront evaluates cache behaviors in order. A specific path pattern like `/api/*` will match API traffic first before falling back to the default behavior.
3
Select the appropriate cache policies for each behavior.
Apply the Managed-CachingDisabled policy (TTL = 0) to the `/api/*` behavior, and Managed-CachingOptimized policy to the default behavior.
This disables caching for API endpoints so that dynamic queries always fetch fresh, user-specific data, while static resources are cached at edge locations for high performance.

Anahtar Kavram

Using path-based cache behaviors in Amazon CloudFront to route traffic to different origins with distinct caching policies.
Soru 1007Soru

A startup is deploying a data ingestion application that must run continuously 24 hours a day, 7 days a week, to consume a steady stream of updates from an external API. The processing load is constant and predictable. The startup wants to minimize compute costs for running this worker.

Which compute option is the MOST cost-effective solution for this workload?

Cevabı ve açıklamayı göster

Cevap: Amazon ECS tasks on AWS Fargate with a Compute Savings Plan.

Cevap

Amazon ECS tasks on AWS Fargate with a Compute Savings Plan
Running a continuous, predictable 24/7 worker in Amazon ECS on AWS Fargate is the most cost-effective option because it provides a consistent, lower hourly rate for compute capacity, which can be further optimized with a Compute Savings Plan. In contrast, serverless functions like AWS Lambda are designed for ephemeral, event-driven tasks and charge a premium for invocation and execution time when run continuously.

Adım Adım Çözüm

1
Analyze the workload characteristics and requirements.
The workload is a data ingestion worker that runs continuously 24/7 with a constant and predictable processing load.
Understanding whether a workload is steady/predictable or spiky/idle is the first step in selecting the most cost-effective compute option.
2
Evaluate AWS Lambda's billing model against the workload.
AWS Lambda is billed per execution and duration. Running a function continuously 24/7 incurs continuous duration charges, which are much higher than running containers or instances continuously.
Evaluating Lambda helps identify if a serverless function is suitable for a long-running, continuous workload.
3
Evaluate containerized compute options on ECS Fargate with savings models.
Amazon ECS on AWS Fargate provides container hosting without EC2 management. Since the workload is continuous and predictable, a Compute Savings Plan can be applied to Fargate to achieve the lowest hourly rate for the required CPU and memory.
Matching containerized compute with savings plans provides the most cost-effective solution for steady-state workloads.

Anahtar Kavram

Matching workload patterns (continuous vs. ephemeral) to the correct compute billing model for cost optimization
Tahmini Süre:45s
Soru 1008Soru

A marketing agency is hosting a short-term promotional campaign website. During the promotion, users can submit contact forms that trigger a brief confirmation email and record the submission details. The website will experience massive, unpredictable traffic spikes during ad broadcasts, but will have zero traffic at night. The database needs to scale automatically to support these spikes, and the compute layer must run code only when a form is submitted to minimize idle costs.

Which two solutions should a solutions architect recommend to meet these requirements?

Geçerli olan tümünü seçin

Cevabı ve açıklamayı göster

Cevap: Use AWS Lambda to process form submissions and send confirmation emails.; Use Amazon DynamoDB with on-demand capacity mode to store contact form submissions.

Cevap

The correct solutions are to use AWS Lambda to process form submissions and send confirmation emails, and to use Amazon DynamoDB with on-demand capacity mode to store contact form submissions.
The correct options are utilizing AWS Lambda for processing and Amazon DynamoDB with on-demand capacity mode for storage. Because the promotional campaign experiences sudden traffic spikes and zero nightly traffic, event-driven serverless architectures are ideal. AWS Lambda ensures that compute resources are only active and billed when a form is submitted. Amazon DynamoDB in on-demand capacity mode handles scaling automatically without manual provisioning, ensuring you only pay for the exact volume of read and write requests and incur zero database compute costs during idle periods.

Adım Adım Çözüm

1
Analyze the compute requirements for event-driven execution.
Identify that the application must run code only when a form is submitted to avoid paying for idle compute capacity during periods of inactivity.
AWS Lambda runs code in response to events (form submissions) and scales down to zero when there is no traffic, ensuring optimal compute cost efficiency.
2
Analyze the database requirements for automatic scaling.
Identify that the database must scale automatically to handle sudden spikes and cost nothing during idle periods.
Amazon DynamoDB with on-demand capacity mode scales dynamically to handle arbitrary workloads and has no base cost per request unit, matching the cost-efficiency requirements.

Anahtar Kavram

Serverless compute and database capacity modes can scale to zero, providing maximum cost efficiency for workloads with unpredictable spikes and idle periods.
Tahmini Süre:1m 0s
Soru 1009Soru

A bioinformatics research institute is deploying a distributed genomic sequence alignment pipeline on Amazon EC2 instances. The analysis nodes must communicate with each other using a specialized Message Passing Interface (MPI) implementation, requiring sub-millisecond, low-latency node-to-node network performance. Client requests are distributed across these instances using a Network Load Balancer (NLB) that routes incoming traffic to a custom processing engine listening on TCP port 99999999. A lightweight status daemon is running on TCP port 8080 on each instance to monitor the node's system-level health. Which combination of actions should a solutions architect take to meet these requirements? (Choose TWO.)

Geçerli olan tümünü seçin

Cevabı ve açıklamayı göster

Cevap: Deploy the EC2 instances in a cluster placement group within a single Availability Zone.; Configure the NLB target group to route traffic to TCP port 99999999 and explicitly set the health check port to TCP port 8080.

Cevap

Deploy the EC2 instances in a cluster placement group within a single Availability Zone, and configure the NLB target group to route traffic to TCP port 99999999 and set the health check port to TCP port 8080.
To achieve sub-millisecond, low-latency node-to-node network performance for MPI-based communications, instances must be placed as close together as possible, which is achieved by deploying them in a cluster placement group within a single Availability Zone. Additionally, because the client traffic is routed to the custom processing engine on TCP port 99999999 but system-level health is monitored by a separate status daemon on TCP port 8080, the Network Load Balancer target group must route traffic to port 99999999 while explicitly querying port 8080 for health checks. This prevents the load balancer from sending health check requests to the custom engine port, which would otherwise result in nodes being marked as unhealthy.

Adım Adım Çözüm

1
Analyze the network latency requirement for MPI-based node-to-node communication.
Determine that a cluster placement group in a single Availability Zone is required to achieve the lowest possible latency and highest network throughput.
Cluster placement groups place instances physically close together on the same underlying hardware network, which is ideal for tightly coupled node-to-node communication.
2
Analyze the ports used by the application and the health monitoring agent.
Identify that incoming client traffic uses TCP port 99999999, while system health status is exposed on TCP port 8080.
The target group must route traffic to port 99999999, but target group health checks must target port 8080 where the status daemon is listening.
3
Configure the Network Load Balancer target group settings.
Set the target group port to 99999999 and override the health check port to explicitly use 8080.
Leaving the health check port at the default 'traffic-port' would cause the NLB to probe port 99999999, which would fail because the status daemon is not listening there, resulting in all targets being marked unhealthy.

Anahtar Kavram

High-performing compute architectures require low-latency placement groups combined with correctly aligned load balancer health check configurations.
Tahmini Süre:2m 30s
Soru 1010Soru

An engineering team is deploying a collaborative CAD (Computer-Aided Design) application on a fleet of Linux-based Amazon EC2 instances distributed across two Availability Zones. The application requires concurrent read and write access to a shared directory containing active project design files. The storage solution must support POSIX compliance, provide sub-millisecond latencies for active files, and scale automatically to handle unpredictable file access spikes. Which storage solution should a solutions architect recommend to meet these requirements?

Cevabı ve açıklamayı göster

Cevap: An Amazon EFS file system configured with Elastic throughput.

Cevap

An Amazon EFS file system configured with Elastic throughput.
The correct choice is the Amazon EFS file system with Elastic throughput. Amazon EFS is designed to provide serverless, fully managed, POSIX-compliant shared file systems that can be concurrently mounted by EC2 instances across multiple Availability Zones. Configured with Elastic throughput, the file system automatically scales throughput performance to meet the unpredictable demands of the CAD application workload without administrative overhead.

Adım Adım Çözüm

1
Analyze the requirements: shared access across multiple Availability Zones, POSIX compliance, sub-millisecond latencies, and automatic scaling for unpredictable workloads.
Identified that the storage must be a shared file system supporting multi-AZ access and automatic throughput scaling.
This rules out single-AZ block storage (EBS) and non-POSIX object storage (S3) for multi-AZ direct sharing.
2
Evaluate EBS Multi-Attach limitations against the multi-AZ deployment requirement.
EBS Multi-Attach is restricted to a single Availability Zone and only supported on Provisioned IOPS SSDs (io1/io2), not gp3.
This eliminates the EBS options.
3
Select the correct service and throughput configuration.
Amazon EFS provides regional, POSIX-compliant shared file access across AZs, and Elastic throughput matches the requirement to scale automatically for unpredictable workloads.
This fulfills all requirements.

Anahtar Kavram

Shared file systems across multiple Availability Zones with automatic throughput scaling using Amazon EFS.
Soru 1011Soru

A financial services firm runs a risk analysis platform on AWS. The platform has a steady-state baseline workload consisting of containerized microservices running on Amazon ECS with AWS Fargate. Every night, the firm runs a memory-intensive batch processing job on Amazon EC2 that takes exactly 3 hours to complete. The batch processing application is resilient and can save its state, allowing it to resume if interrupted. During execution, the batch job writes large amounts of temporary intermediate data to Amazon S3, which is deleted automatically after 5 days. The database layer consists of an Amazon RDS for PostgreSQL database instance. Which two actions should a solutions architect recommend to optimize compute and storage costs? (Select TWO.)

Geçerli olan tümünü seçin

Cevabı ve açıklamayı göster

Cevap: Purchase a Compute Savings Plan to cover the baseline Fargate container workloads.; Launch the nightly batch processing jobs using EC2 Spot Instances.

Cevap

Purchase a Compute Savings Plan to cover the baseline Fargate container workloads, and launch the nightly batch processing jobs using EC2 Spot Instances.
Purchasing a Compute Savings Plan provides the most cost-effective coverage for the baseline Fargate microservices workload since Compute Savings Plans apply automatically to Fargate. Using EC2 Spot Instances is the most cost-optimized strategy for the nightly batch job because the workload is flexible and resilient to interruptions, allowing the firm to take advantage of the steep discounts offered by Spot pricing.

Adım Adım Çözüm

1
Analyze the baseline workload and apply the correct purchasing model.
Identify that the steady-state baseline containers run on AWS Fargate. Select a Compute Savings Plan, which covers Fargate and offers significant discounts for consistent usage.
Compute Savings Plans are flexible and automatically apply to Fargate, whereas EC2 Instance Savings Plans or EC2 Reserved Instances do not.
2
Analyze the batch processing workload properties.
Identify that the nightly batch job runs on EC2, is memory-intensive, runs for 3 hours, and is resilient to interruptions.
Since the workload is fault-tolerant and interruptible, EC2 Spot Instances are the most cost-effective option, offering up to 90% savings over On-Demand pricing.
3
Evaluate the storage requirements for the temporary batch data.
Determine that the intermediate data is deleted after 5 days. Keep the data in S3 Standard rather than transitioning it to S3 Standard-IA.
S3 Standard-IA enforces a 30-day minimum storage charge. Deleting data after 5 days in S3 Standard-IA incurs a minimum duration fee, neutralizing any storage class savings.

Anahtar Kavram

Selecting cost-optimized compute purchasing strategies (Savings Plans and Spot Instances) while avoiding scope misapplications and storage duration penalties.
Soru 1012Soru

A global multiplayer gaming platform uses Amazon API Gateway, AWS Lambda, and an Amazon DynamoDB table to store and serve live game leaderboards. During peak tournament events, users experience high latency when retrieving leaderboard standings, and the DynamoDB table experiences read throttling. The company needs a caching solution to reduce response latency to milliseconds and offload read queries from the database. Which two actions should the solutions architect take to meet these requirements? (Choose two.)

Geçerli olan tümünü seçin

Cevabı ve açıklamayı göster

Cevap: Deploy an Amazon DynamoDB Accelerator (DAX) cluster to cache read queries to the leaderboard table.; Deploy an Amazon CloudFront distribution in front of the API Gateway, and configure a cache behavior for the leaderboard API resource with a positive Default TTL.

Cevap

Deploying an Amazon DynamoDB Accelerator (DAX) cluster to cache read queries to the leaderboard table, and deploying an Amazon CloudFront distribution in front of API Gateway with a cache behavior configured with positive TTLs.
Deploying Amazon DynamoDB Accelerator (DAX) directly in front of DynamoDB handles database query caching, returning cached results in microseconds and reducing database read load. Deploying Amazon CloudFront in front of Amazon API Gateway with positive TTL values caches API responses at the edge, reducing both Lambda executions and API Gateway hits for global clients.

Adım Adım Çözüm

1
Analyze the application architecture and requirements.
Identified that the leaderboard API is hosted on API Gateway, Lambda, and DynamoDB, and requires low latency and database offloading during peak events.
Understanding the bottleneck locations (API Gateway/Lambda compute and DynamoDB reads) helps target the right caching levels.
2
Select a database caching solution.
Choose DynamoDB Accelerator (DAX) to cache database read operations directly in front of DynamoDB.
DAX provides microsecond latency for cached reads and prevents cache misses or other database clients from overloading the table.
3
Select an edge caching solution.
Choose Amazon CloudFront with positive TTL values to cache API responses at edge locations.
CloudFront reduces latency globally and prevents repetitive requests from hitting API Gateway and Lambda.

Anahtar Kavram

Multi-tier caching using Amazon CloudFront and Amazon DynamoDB Accelerator (DAX)
Soru 1013Soru

A company is designing a cost-optimized database architecture for a non-critical internal application. The architecture includes two databases:

1. An Amazon RDS for MySQL database that has a predictable baseline workload of `500500` writes/second and `1,0001,000` reads/second. During a weekly `44-hour` batch processing job, the read workload spikes to `10,00010,000` reads/second. A short period of downtime is acceptable during database updates or failures.
2. An Amazon DynamoDB table that stores temporary session state data. The write traffic is highly volatile and unpredictable, spiking from `1010` writes/second to `8,0008,000` writes/second within seconds, followed by long periods of idle time.

Which two strategies should the solutions architect implement to meet these requirements in the most cost-effective manner? (Select TWO.)

Geçerli olan tümünü seçin

Cevabı ve açıklamayı göster

Cevap: Configure the RDS for MySQL database as a single-Availability Zone (Single-AZ) instance, purchase a Reserved Instance to cover the baseline workload, and configure RDS Read Replicas with Application Auto Scaling to handle the weekly read spikes.; Configure the DynamoDB table to use On-Demand capacity mode.

Cevap

To design a cost-optimized database tier, configure the RDS for MySQL database as a Single-AZ instance with a Reserved Instance contract for the baseline workload and configure RDS Read Replicas with Application Auto Scaling to handle the weekly spikes. Additionally, configure the DynamoDB table to use On-Demand capacity mode to accommodate the unpredictable write bursts.
For the relational database, a Single-AZ RDS for MySQL instance with a Reserved Instance contract is the most cost-effective way to handle the predictable baseline workload since high availability is not required and short downtime is acceptable. During the weekly batch read spikes, RDS Read Replicas with Application Auto Scaling can scale out to handle the read load and scale in when not in use. For the non-relational database, DynamoDB On-Demand capacity mode is the most cost-effective configuration because the workload is highly volatile and unpredictable, and On-Demand capacity adapts instantly to spikes without over-provisioning or throttling.

Adım Adım Çözüm

1
Analyze the availability and deployment model requirements for the relational database.
Since the application is non-critical and can tolerate short downtime, a Single-AZ deployment is selected. This reduces database licensing and infrastructure costs by approximately `50%50\%` compared to a Multi-AZ deployment.
Avoids unnecessary high-availability standby costs when the business requirements do not demand it.
2
Select the purchasing option and scaling strategy for the predictable relational database workload.
A Reserved Instance contract is chosen for the stable baseline workload (`500500` writes/second and `1,0001,000` reads/second). For the weekly `44-hour` read spikes, RDS Read Replicas with Application Auto Scaling are configured.
Reserved Instances minimize baseline costs, while read replicas scale out dynamically only when needed, keeping idle costs at zero.
3
Determine the capacity planning mode for the volatile non-relational database workload.
DynamoDB On-Demand capacity mode is chosen for the session state table.
Since write spikes are sudden and unpredictable, auto-scaling would fail to react quickly enough, causing write failures, while provisioning for the peak of `8,0008,000` writes/second would lead to extreme idle capacity costs.

Anahtar Kavram

Cost optimization for databases involves matching deployment structures and capacity planning modes to workload predictability and availability requirements. Predictable baselines benefit from Reserved Instances, while temporary spikes should use auto-scaling or on-demand modes. Non-critical applications should avoid Multi-AZ deployments unless high availability is mandatory.
Tahmini Süre:2m 30s
Soru 1014Soru

A digital publishing platform hosts its content delivery tier in VPC Alpha and its logging and analytics cluster in VPC Beta, both located in the `eu-west-1` Region. Every month, the content delivery tier transfers 75 TB75\text{ TB} of raw log files to the analytics cluster. The instances in both VPCs reside in private subnets. Which TWO configuration steps should a Solutions Architect recommend to achieve the most cost-effective network routing? (Select TWO.)

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Cevap: Establish a VPC peering connection between VPC Alpha and VPC Beta, and update the route tables to route the log transfer traffic through the peering connection.; Configure the content delivery instances to transfer the log files using the private IP addresses of the analytics instances in VPC Beta.

Cevap

Establish a VPC peering connection between VPC Alpha and VPC Beta, update the route tables to route the traffic through the peering connection, and configure the instances to communicate using their private IP addresses.
Establishing a VPC peering connection and using private IP addresses is the most cost-effective architecture. VPC peering has no setup fees, hourly attachment fees, or data processing charges. Using private IP addresses ensures that traffic remains within the AWS private network, avoiding NAT Gateway processing fees (which cost $0.045\$0.045 per GB) and public IP data transfer charges.

Adım Adım Çözüm

1
Analyze the source and destination networks and the volume of data transfer.
The traffic is strictly internal between two VPCs in the same AWS Region (`eu-west-1`), involving a high data volume of 75 TB75\text{ TB} per month.
Understanding the data volume and boundaries helps determine the most cost-effective connection type by eliminating options with high per-GB processing charges.
2
Compare the cost structure of VPC Peering versus Transit Gateway.
VPC Peering has no setup fees, hourly charges, or data processing fees. AWS Transit Gateway charges $0.05\$0.05 per GB, which would cost $3,750\$3,750 per month for 75 TB75\text{ TB} of data.
Selecting VPC Peering over Transit Gateway eliminates the data processing fee for intra-region traffic.
3
Evaluate the IP routing mechanism to avoid internet and NAT Gateway costs.
Routing traffic to public IP addresses requires NAT Gateways (incurring $0.045\$0.045 per GB processing fees) or public IP transfer charges. Using private IP addresses over the VPC peering connection avoids these fees.
Private IP routing ensures the traffic remains completely internal and avoids unnecessary NAT or public data transfer charges.

Anahtar Kavram

VPC Peering provides a cost-effective, high-bandwidth connection between VPCs in the same region without data processing fees, whereas Transit Gateway and NAT Gateways charge per-GB processing fees that escalate costs significantly for large data volumes.
Tahmini Süre:2m 0s
Soru 1015Soru

A company wants to allow external development contractors to deploy application resources in a development AWS account. The contractors manage their users in an external identity provider (IdP) that supports SAML 2.0. The security team requires that the contractors only be able to create IAM roles for their applications that do not exceed a specific security baseline. The contractors must not be able to escalate their own permissions or create roles that grant access to unauthorized services. Which TWO options should a solutions architect combine to meet these requirements securely? (Select TWO.)

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Cevap: Configure SAML 2.0 identity federation to map the contractors' external identity provider groups to an IAM role in the AWS account, allowing them to assume the role.; Create an IAM policy for the contractor role that grants permission to create roles only if the role is created with a specific IAM permissions boundary policy attached, using the iam:PermissionsBoundary condition key.

Cevap

Configure SAML 2.0 identity federation to map the external IdP groups to an IAM role, and use an IAM permissions boundary policy enforced via the iam:PermissionsBoundary condition key on the contractor role's permissions.
The correct options implement a secure, best-practice architecture. By configuring SAML 2.0 federation, the company avoids creating long-term IAM credentials for external contractors. Enforcing a permissions boundary via the iam:PermissionsBoundary condition key prevents the contractors from creating roles that exceed the baseline policy or escalating their own permissions.

Adım Adım Çözüm

1
Establish secure federated access for external contractors.
Contractors authenticate using their existing external Identity Provider (IdP) via SAML 2.0, assuming a temporary session role in AWS instead of using long-term IAM user credentials.
Aligns with the principle of least privilege and eliminates the risk associated with managing and rotating static credentials.
2
Define the security baseline using an IAM permissions boundary policy.
An IAM permissions boundary policy is created that lists the maximum allowed actions (e.g., S3 and DynamoDB access).
This policy does not grant permissions by itself, but defines the maximum privilege limit for any role to which it is applied.
3
Enforce the boundary policy on the contractors' role creation actions.
An IAM policy attached to the contractors' assumed role allows the iam:CreateRole action only when accompanied by the iam:PermissionsBoundary condition key referencing the baseline boundary policy ARN.
Prevents contractors from creating roles with elevated privileges, effectively blocking privilege escalation.

Anahtar Kavram

Delegating role creation securely using SAML 2.0 federation and IAM Permissions Boundaries to prevent privilege escalation.
Tahmini Süre:2m 30s
Soru 1016Soru

A media monitoring company processes video and audio news broadcasts. External feeds drop media files of varying sizes into an Amazon S3 bucket. A metadata file specifies a strict processing sequence (chronological ordering) that must be maintained for downstream sentiment analysis. The processing jobs extract transcripts using a CPU-heavy transcription engine, which takes between 1212 to 2525 minutes per file. The current system relies on a fixed fleet of Amazon EC2 instances, which results in high idle costs during periods of low activity. A solutions architect must design a serverless, automated scaling architecture that minimizes costs, scales to zero when there is no activity, and ensures the strict processing order of media files is preserved. Which architecture meets these requirements most cost-effectively?

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Cevap: Configure an Amazon S3 event notification to trigger an AWS Lambda function that sends message metadata to an Amazon SQS FIFO queue. Deploy the transcription engine as containerized tasks in an Amazon ECS cluster using AWS Fargate Spot capacity providers. Configure an ECS service auto scaling policy based on the queue size to process the files. Store the output in Amazon Aurora Serverless v2.

Cevap

Configure an Amazon S3 event notification to trigger an AWS Lambda function that sends message metadata to an Amazon SQS FIFO queue. Deploy the transcription engine as containerized tasks in an Amazon ECS cluster using AWS Fargate Spot capacity providers. Configure an ECS service auto scaling policy based on the queue size to process the files. Store the output in Amazon Aurora Serverless v2.
The correct solution utilizes Amazon SQS FIFO queues to guarantee chronological message ordering and Amazon ECS on AWS Fargate Spot for cost-effective processing of long-running, CPU-intensive transcription workloads. SQS FIFO ensures the strict sequence is preserved, while Fargate Spot scales compute capacity down to zero when the queue is empty, eliminating idle compute costs. Using Fargate Spot provides a discount of up to 70%70\% compared to standard Fargate, and avoids the 1515-minute execution timeout limit of AWS Lambda. Amazon Aurora Serverless v2 handles database scaling dynamically and cost-efficiently for spiky, unpredictable workloads, scaling down during idle periods.

Adım Adım Çözüm

1
Select a message queue pattern that guarantees ordering.
Amazon SQS FIFO queue must be used to preserve chronological order, as SQS Standard and EventBridge do not guarantee strict sequence ordering.
The scenario requires maintaining the strict chronological ordering of media files for downstream sentiment analysis.
2
Determine the appropriate compute service based on task duration and cost constraints.
AWS Fargate Spot is selected over AWS Lambda and standard AWS Fargate.
The CPU-heavy task takes 1212 to 2525 minutes. AWS Lambda has a hard timeout limit of 1515 minutes, making it unsuitable. AWS Fargate Spot provides the required runtime duration at a fraction of the cost of standard Fargate tasks (up to 70%70\% savings), scaling to zero when the queue is empty.
3
Choose a cost-optimized database configuration for unpredictable, spiky workloads.
Amazon Aurora Serverless v2 is selected to store results.
Aurora Serverless v2 scales dynamically to meet workload spikes and scales down to minimum capacity during idle periods, avoiding the high cost of provisioned database resources during idle times.

Anahtar Kavram

Selecting the most cost-effective and scale-to-zero serverless compute and database options based on execution duration and workload patterns.
Soru 1017Soru

A genomics research company runs a batch sequence analysis pipeline on a cluster of Linux EC2 instances. The pipeline requires a shared, high-performance file system that can deliver sub-millisecond latencies and throughput of up to 10 GB/s to ingest and process raw sequence data stored in an Amazon S3 bucket. The file system only needs to exist during the execution of the batch processing jobs, after which the processed results are written back to Amazon S3. Which combination of actions should a solutions architect take to meet these requirements? (Select TWO.)

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Cevap: Create an Amazon FSx for Lustre file system using scratch storage.; Link the FSx for Lustre file system to the Amazon S3 bucket as a data repository.

Cevap

Create an Amazon FSx for Lustre file system using scratch storage, and link the FSx for Lustre file system to the Amazon S3 bucket as a data repository.
The correct architecture uses Amazon FSx for Lustre scratch storage linked to an Amazon S3 bucket. FSx for Lustre provides the high performance (sub-millisecond latencies and gigabytes-per-second throughput) required for genomics batch processing. Using scratch storage is ideal and cost-effective because data is temporary and persists in S3. The data repository link allows the EC2 instances to access and sync files directly with the S3 bucket.

Adım Adım Çözüm

1
Analyze the workload requirements and identify the correct file system type.
The genomics sequence analysis requires high-throughput (up to 10 GB/s) and sub-millisecond latencies on a Linux cluster, which points to Amazon FSx for Lustre as the standard high-performance parallel file system choice.
FSx for Lustre is optimized for compute-heavy workloads like high-performance computing (HPC) and financial modeling.
2
Determine the cost-effective storage type for transient batch processing.
Choose scratch storage for the FSx for Lustre file system.
Scratch file systems are designed for temporary storage and do not replicate data, making them cheaper while delivering the required high performance for temporary batch jobs.
3
Connect the file system to the input/output data source in S3.
Configure a data repository association to link the FSx for Lustre file system to the Amazon S3 bucket.
This links the file system to S3, enabling automatic import of raw sequence files and permitting writing back processed results dynamically.

Anahtar Kavram

Amazon FSx for Lustre is a parallel file system natively integrated with Amazon S3. The scratch storage option is designed for temporary storage and high-performance batch processing, enabling rapid data ingestion and output synchronization back to S3.
Soru 1018Soru

An advertising technology company is deploying a real-time bidding (RTB) engine on Amazon EC2 instances to process ad auctions. The engine must maintain sub-millisecond node-to-node network latency to synchronize internal state tables across the cluster. The bidding application runs on a custom port, 90809080, on each EC2 instance. The company deploys a Network Load Balancer (NLB) with a listener on port 8080 to receive incoming HTTP requests from external ad exchanges and route them to the EC2 instances. During initial testing, the NLB marks all EC2 instances as unhealthy, and node-to-node communication latency is higher than expected. Which combination of EC2 placement and load balancer target group configuration will resolve these issues while meeting the performance requirements?

Cevabı ve açıklamayı göster

Cevap: Deploy the EC2 instances in a cluster placement group. Configure the NLB target group health check to query port 9080.

Cevap

Deploy the EC2 instances in a cluster placement group and configure the NLB target group health check to query port 9080.
To achieve sub-millisecond network latency between nodes, the EC2 instances must be deployed in a cluster placement group. Cluster placement groups place instances physically close to each other in a single Availability Zone, which minimizes latency. Additionally, because the application is listening on port 9080, the Network Load Balancer target group health check must be explicitly configured to query port 9080 (or the traffic port routing to 9080) instead of the default port 80 listener, ensuring the load balancer can verify that the service is running.

Adım Adım Çözüm

1
Analyze the latency requirement for node-to-node communication.
The system needs sub-millisecond network latency to synchronize state tables between instances.
Cluster placement groups pack instances close together within a single Availability Zone, enabling low-latency, high-throughput network performance.
2
Determine the appropriate target group health check port.
The application is bound to port 9080, while the NLB listens on port 80.
Configuring the health check to target the listener port (port 80) will fail because the instances are not running services on port 80. The health check must query port 9080 directly to verify application availability.

Anahtar Kavram

Low-latency network clustering with EC2 Cluster Placement Groups and matching ELB health check ports to application-bound ports.
Soru 1019Soru

An enterprise manages a multi-account AWS environment using AWS Organizations. The operations team needs to implement a cost-monitoring strategy with two primary requirements:
1. Receive proactive alerts within a few hours if there is a sudden, unexpected spike in AWS usage costs.
2. Receive an alert if the total monthly cost of resources tagged with Project: Alpha is projected to exceed a specific budget.

The strategy must minimize operational overhead. Which combination of actions should the solutions architect recommend to meet these requirements? (Select TWO.)

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Cevap: Create an AWS Cost Anomaly Detection monitor using the Resource Tag monitor type, and configure an Amazon Simple Notification Service (Amazon SNS) subscription to send immediate alerts when anomalies are detected.; Create a Cost Budget in AWS Budgets, filter the budget by the Project: Alpha tag, and configure an alert threshold based on forecasted costs to notify the operations team.

Cevap

To meet the requirements, the solutions architect should configure an AWS Cost Anomaly Detection monitor using the Resource Tag monitor type with an Amazon SNS subscription for immediate alerting, and create a Cost Budget in AWS Budgets filtered by the Project: Alpha tag with an alert threshold based on forecasted costs.
AWS Cost Anomaly Detection monitors cost monitors and sends immediate notifications using Amazon SNS when an unexpected spend anomaly is detected, satisfying the quick turnaround requirement. AWS Budgets allows cost budgets to be filtered by tags (like Project: Alpha) and can alert based on actual or forecasted cost thresholds, satisfying the budget projection requirement.

Adım Adım Çözüm

1
Address the sudden cost spike monitoring requirement.
Recommend AWS Cost Anomaly Detection, which uses machine learning to detect unusual cost rises and supports near real-time alerts via Amazon SNS.
Traditional budgeting or retrospective reports cannot alert within a few hours of an unexpected spike without significant custom development and delay.
2
Address the tag-based projected monthly budget requirement.
Recommend AWS Budgets filtered by the Project: Alpha tag with a threshold set on forecasted costs.
AWS Budgets natively evaluates forecasted monthly usage against a specific threshold and sends alerts before the budget limit is actually breached.
3
Eliminate retrospective analysis and custom billing solutions.
Discard options using AWS Cost Explorer scheduled reports and AWS Billing Conductor.
AWS Cost Explorer is a retrospective visualization tool that lacks direct alerting triggers, and AWS Billing Conductor is designed for customer/partner pro forma billing structures, not near real-time monitoring.

Anahtar Kavram

Distinguishing between proactive cost alerting tools (AWS Budgets, AWS Cost Anomaly Detection) and retrospective reporting tools (AWS Cost Explorer) in enterprise cost optimization.
Soru 1020Soru

A digital marketing firm processes web interaction logs that are saved to an Amazon S3 bucket. The logs average 15 KB15\text{ KB} in size. These files are frequently accessed during the first 10 days10\text{ days} for campaign optimization. After 10 days10\text{ days}, access drops significantly, but the files must be kept for an additional 10 days10\text{ days} (total of 20 days20\text{ days} from creation) before being permanently deleted. Which two configurations should the solutions architect implement to achieve the most cost-effective storage strategy? (Select TWO.)

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Cevap: Keep the log files in S3 Standard for the entire 20 days20\text{ days} without transitioning them to another S3 storage class.; Create an S3 Lifecycle rule to expire the objects 20 days20\text{ days} after creation.

Cevap

The solutions architect should keep the log files in S3 Standard for the entire duration and create an S3 Lifecycle rule to expire the objects after 20 days.
Keeping the log files in S3 Standard for the entire lifecycle is correct because the files are small (15 KB15\text{ KB}) and have a short total retention period of 20 days20\text{ days}. Transitioning them to S3 Standard-IA or Glacier Instant Retrieval would trigger minimum storage size billing (128 KB128\text{ KB}) and early deletion charges (due to 30 day30\text{ day} or 90 day90\text{ day} minimums). Configuring an S3 Lifecycle rule to expire the objects after 20 days20\text{ days} is correct because it automates deletion to prevent ongoing storage charges once the retention requirement is met.

Adım Adım Çözüm

1
Analyze the size of the individual objects and their access pattern.
The individual files average 15 KB15\text{ KB}, which is well below the 128 KB128\text{ KB} minimum storage size threshold for S3 Standard-IA and S3 Glacier tiers. Transitioning these objects to these tiers would result in being billed for 128 KB128\text{ KB} per object.
Understanding object size constraints prevents cost inflation from minimum storage size requirements.
2
Evaluate the storage duration against S3 storage class minimum duration rules.
The files are deleted after 20 days20\text{ days}. S3 Standard-IA has a minimum storage duration of 30 days30\text{ days}, and S3 Glacier tiers have a minimum storage duration of 90 days90\text{ days} or more. Deleting them at day 20 incurs early deletion penalties.
Determining retention rules avoids early deletion charge penalties.
3
Formulate the most cost-effective tiering and deletion strategy.
Keep the objects in S3 Standard to avoid minimum storage size and duration penalties, and apply a lifecycle expiration rule to delete them after 20 days20\text{ days} to stop storage costs immediately.
Combining S3 Standard retention with automated expiration optimizes both storage tier charges and deletion lifecycle.

Anahtar Kavram

S3 Lifecycle and Storage Class Constraints (Minimum Object Size and Storage Duration)
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Tüm alıştırma soruları — AWS Certified Solutions Architect - Associate | Examkin