Tüm alıştırma soruları

1462 soru

Soru 681Soru

A media streaming platform needs to design a high-performing ingestion pipeline to process video playback quality telemetry from 10 million10 \text{ million} active players. During peak hours, the system receives 150000150{}000 events per second, with an average event payload size of 2 KB2 \text{ KB}. The platform requires that buffering events be analyzed within 5 seconds5 \text{ seconds} to trigger adaptive bitrate changes, while all raw telemetry must be transformed into Apache Parquet format and archived in Amazon S3 within 5 minutes5 \text{ minutes} for daily analytical processing. Which architecture meets these requirements with the highest performance and the lowest operational overhead?

Cevabı ve açıklamayı göster

Cevap: Configure Amazon Kinesis Data Streams in Provisioned mode with 300300 shards. Deploy an Amazon Managed Service for Apache Flink application to perform real-time analysis of buffering events from the stream. Configure Amazon Data Firehose to consume from the same Kinesis stream to transform the telemetry to Apache Parquet format and write it to Amazon S3.

Cevap

Configure Amazon Kinesis Data Streams in Provisioned mode with 300300 shards, deploy an Amazon Managed Service for Apache Flink application for real-time analysis, and use Amazon Data Firehose to consume from the same stream, transform the data to Parquet, and write it to Amazon S3.
Designing the ingestion layer with Amazon Kinesis Data Streams in Provisioned mode with 300300 shards satisfies the throughput requirement. At 150000150{}000 events/second and 2 KB2 \text{ KB} per event, the peak ingest throughput is 300 MB/s300 \text{ MB/s}. Since a single shard supports up to 1 MB/s1 \text{ MB/s} write throughput, 300300 shards are needed. Using Amazon Managed Service for Apache Flink enables real-time stream analysis within the 55-second latency requirement. Amazon Data Firehose can consume from the stream asynchronously to buffer, transform to Parquet, and write to Amazon S3, meeting the 55-minute archival requirement.

Adım Adım Çözüm

1
Calculate the peak write throughput requirement.
Peak write throughput is 300 MB/s300 \text{ MB/s} (derived from 150000 events/sec×2 KB/event=300000 KB/s=300 MB/s150{}000 \text{ events/sec} \times 2 \text{ KB/event} = 300{}000 \text{ KB/s} = 300 \text{ MB/s}).
Knowing the peak throughput is necessary to select the correct ingestion service and capacity configuration.
2
Determine the stream capacity mode and scaling requirements.
A Kinesis stream with 300300 provisioned shards is required because Kinesis Data Streams On-Demand has a default capacity limit of 200 MB/s200 \text{ MB/s} write throughput. A single shard supports up to 1 MB/s1 \text{ MB/s} write throughput, meaning 300300 shards are needed to support 300 MB/s300 \text{ MB/s}.
This ensures the stream can handle peak traffic without throttling or experiencing ProvisionedThroughputExceededException errors.
3
Evaluate the real-time processing and delivery components.
Amazon Managed Service for Apache Flink provides sub-55-second processing, and Amazon Data Firehose handles Parquet transformation and S3 delivery.
This meets the dual latency requirements of real-time analysis (under 5 seconds5 \text{ seconds}) and batch archival (under 5 minutes5 \text{ minutes}).

Anahtar Kavram

High-performing real-time data ingestion scaling limits and streaming analytics architectures
Soru 682Soru

A media production agency is deploying a video rendering application on a fleet of Amazon EC2 instances distributed across multiple Availability Zones. The instances require concurrent read and write access to a shared file system that can deliver up to 2.5 GiB/s2.5 \text{ GiB/s} of throughput during peak rendering windows. The throughput demands are highly variable throughout the day. Which storage solution will meet these requirements while providing the highest performance and concurrent access?

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 solution uses Amazon EFS with Elastic throughput because EFS naturally supports concurrent access across multiple Availability Zones. Elastic throughput scales automatically up to 3 GiB/s3 \text{ GiB/s} for read operations, making it ideal for the highly variable, high-performance rendering workload.

Adım Adım Çözüm

1
Identify the architectural requirements, which include concurrent read and write access across multiple Availability Zones and highly variable throughput peaking at 2.5 GiB/s2.5 \text{ GiB/s}.
The solution must support a shared file system architecture that scales performance dynamically up to 2.5 GiB/s2.5 \text{ GiB/s} across multiple Availability Zones.
This establishes the performance and network boundary constraints for the selection process.
2
Evaluate Amazon EBS limitations regarding Multi-Attach and multi-AZ deployments.
EBS gp3 does not support Multi-Attach, and io2 Multi-Attach is restricted to a single Availability Zone.
This eliminates the EBS options as they cannot satisfy the requirement for cross-AZ shared storage.
3
Evaluate Amazon EFS throughput modes to handle the spiky 2.5 GiB/s2.5 \text{ GiB/s} workload.
Elastic throughput scales dynamically to support the peak workload, whereas a low Provisioned throughput will cause performance throttling once credits are exhausted.
Elastic throughput matches the spiky nature of rendering workloads with zero provisioning overhead.

Anahtar Kavram

Shared file storage scaling dynamically across multiple Availability Zones using EFS Elastic throughput.
Soru 683Soru

An online education platform hosts its web application on Amazon EC2 instances distributed across multiple Availability Zones. The platform requires a resilient storage architecture that includes a shared file system for active course media files which must be concurrently accessible by all EC2 instances. Additionally, database backups must be stored with high durability, ensuring a Recovery Time Objective (RTO) of 55 minutes and a Recovery Point Objective (RPO) of 2424 hours. Which two storage configurations should a solutions architect recommend to meet these requirements?

Geçerli olan tümünü seçin

Cevabı ve açıklamayı göster

Cevap: Use Amazon Elastic File System (Amazon EFS) to provide a shared, regional file system for the active course media files.; Store the database backups in Amazon S3 Standard to ensure high availability and immediate data retrieval.

Cevap

Use Amazon Elastic File System (Amazon EFS) for the shared file system, and store the database backups in Amazon S3 Standard.
The correct configurations are using Amazon EFS for shared multi-AZ storage and Amazon S3 Standard for backup storage. Amazon EFS is a regional service that supports concurrent read and write access from EC2 instances in multiple Availability Zones. Amazon S3 Standard provides active storage with immediate (millisecond-level) access, which easily satisfies the 5-minute Recovery Time Objective (RTO) for restoring backups.

Adım Adım Çözüm

1
Identify the access requirement for the active media files.
Multiple EC2 instances in different Availability Zones require concurrent read/write access to a single file system.
Amazon EFS is selected because it is a shared, regional file system designed for concurrent access across multiple AZs.
2
Evaluate the backup recovery metrics (RTO).
The RTO is 5 minutes, which requires immediate, low-latency retrieval of backup files.
Amazon S3 Standard is selected because it provides active storage with millisecond-level retrieval, satisfying the 5-minute RTO.

Anahtar Kavram

Selecting highly available, multi-AZ shared storage (Amazon EFS) and low-latency backup storage (Amazon S3 Standard) to meet specific application access and RTO requirements.
Tahmini Süre:1m 30s
Soru 684Soru

A retail company wants to track real-time inventory updates from 100100 physical stores. Each store publishes an inventory update XML payload (averaging 10 KB10\text{ KB} each) every 55 seconds. The company wants to ingest this data with minimal operational overhead, automatically convert the XML payload to JSON format, and write the JSON data to an Amazon S3 bucket for downstream analytics.

Which two AWS services or features should the solutions architect combine to build this solution? (Select two.)

Geçerli olan tümünü seçin

Cevabı ve açıklamayı göster

Cevap: Amazon Data Firehose to ingest the incoming stream and deliver the transformed data to Amazon S3.; An AWS Lambda function integrated with Amazon Data Firehose to perform the XML-to-JSON transformation.

Cevap

The solutions architect should combine Amazon Data Firehose and an integrated AWS Lambda function to ingest the data stream, convert the XML payloads to JSON, and deliver the output to Amazon S3 with minimal operational overhead.
Combining Amazon Data Firehose with an integrated AWS Lambda function provides a completely serverless, high-performing data ingestion and transformation pipeline. Amazon Data Firehose manages the ingestion and automatically scales to deliver the transformed data to the destination Amazon S3 bucket. The integrated AWS Lambda function executes the custom logic to convert the XML payloads to JSON format inline as the data flows through the stream, requiring no server provisioning or management.

Adım Adım Çözüm

1
Select Amazon Data Firehose to serve as the streaming delivery stream.
This provides an auto-scaling, serverless ingestion service that natively integrates with Amazon S3 as a destination, minimizing operational management.
Firehose handles high-throughput stream ingestion and handles S3 delivery out of the box.
2
Create an AWS Lambda function with the logic to parse XML payloads and output JSON format.
A serverless transformation function is defined that can run on small batches of records.
Lambda scales automatically with Firehose invocations and performs the required transformation without requiring dedicated servers.
3
Enable the Data Transformation feature in the Amazon Data Firehose stream and associate the Lambda function.
Incoming data is buffered, passed to Lambda for inline conversion, and then written as JSON to the target S3 bucket.
This configuration connects ingestion and transformation into a single managed pipeline.

Anahtar Kavram

Serverless real-time data ingestion and inline transformation using Amazon Data Firehose and AWS Lambda.
Soru 685Soru

A financial services company hosts a global web application across multiple AWS Regions. The primary infrastructure is in the us-east-1 Region, containing an Application Load Balancer (ALB) and an Auto Scaling group of EC2 instances. To meet strict recovery time objective (RTO) requirements, the company deploys a replica of the environment in the eu-central-1 Region as a standby. The application serves a mix of cacheable static assets and highly dynamic, non-cacheable transactional API endpoints under /api/*. The architecture must ensure minimal latency, immediate failover to the standby region during an outage without relying on client-side DNS caching, and full support for all HTTP write methods (POST, PUT, DELETE) on the transactional endpoints. Which solution should a solutions architect recommend to meet these requirements with the least operational complexity?

Cevabı ve açıklamayı göster

Cevap: Create an Amazon CloudFront distribution and define an Origin Group with the us-east-1 ALB as the primary origin and the eu-central-1 ALB as the secondary origin. Configure origin failover with 500, 502, 503, and 504 status codes. Create two cache behaviors: a default behavior for static assets with caching enabled, and a behavior for the /api/* path with caching disabled by setting the Minimum, Maximum, and Default TTLs to 0, forwarding all headers, cookies, and query strings, and allowing all HTTP methods.

Cevap

Create an Amazon CloudFront distribution and define an Origin Group with the us-east-1 ALB as the primary origin and the eu-central-1 ALB as the secondary origin. Configure origin failover with 500, 502, 503, and 504 status codes. Create two cache behaviors: a default behavior for static assets with caching enabled, and a behavior for the /api/* path with caching disabled by setting the Minimum, Maximum, and Default TTLs to 0, forwarding all headers, cookies, and query strings, and allowing all HTTP methods.
The correct solution utilizes Amazon CloudFront Origin Groups, which natively handle regional failover at the edge. When the primary origin returns any of the configured 5xx errors, CloudFront transparently retries the request against the secondary origin without involving client-side DNS updates. By defining two cache behaviors, the static assets remain cached for performance, while the dynamic path (/api/*) is configured with TTLs of 0 and forwards all headers, cookies, and query strings, ensuring that transactional requests are dynamically routed to the active origin and support all HTTP write operations.

Adım Adım Çözüm

1
Configure the CloudFront Origin Group.
An Origin Group is defined with the primary load balancer in us-east-1 and the secondary standby load balancer in eu-central-1, specifying failover HTTP status codes (500, 502, 503, 504).
This establishes a resilient, edge-based failover mechanism that bypasses DNS cache propagation delays, meeting the low RTO requirement.
2
Configure the cache behavior for static content.
The default cache behavior (*) is configured with standard caching enabled (positive TTLs) to serve static assets from edge locations.
This offloads traffic from the backend origins, reducing latency and compute overhead.
3
Configure the cache behavior for the dynamic REST API.
A specific cache behavior for the path /api/* is created with caching disabled (TTLs set to 0), allowed HTTP methods configured to include POST, PUT, DELETE, and cache key settings configured to forward all headers, cookies, and query strings.
This ensures that transactional API calls bypass cache storage, preserve user session state, and execute successfully against the healthy backend.

Anahtar Kavram

CloudFront Origin Groups and Origin Failover combined with path-based cache behaviors for hybrid static/dynamic architectures.
Soru 686Soru

A financial services firm needs to establish a dedicated, private network connection between its on-premises datacenter and multiple VPCs located in the useast1us-east-1 and uswest2us-west-2 Regions. The connection must provide consistent network performance, low latency, and support a minimum data transfer rate of 10 Gbps10\text{ Gbps} for real-time database replication. The solution must also scale to accommodate new VPCs in both Regions in the future.

Which combination of actions should a solutions architect take to meet these requirements? (Select TWO.)

Geçerli olan tümünü seçin

Cevabı ve açıklamayı göster

Cevap: Establish a 10 Gbps10\text{ Gbps} AWS Direct Connect connection and create a transit virtual interface (transit VIF) associated with a Direct Connect gateway.; Associate the Direct Connect gateway with an AWS Transit Gateway in each Region to route traffic to the local VPCs.

Cevap

Establishing a 10 Gbps10\text{ Gbps} AWS Direct Connect connection with a transit virtual interface (transit VIF) associated with a Direct Connect gateway, and associating the Direct Connect gateway with an AWS Transit Gateway in each Region.
Establishing a 10 Gbps10\text{ Gbps} AWS Direct Connect connection with a transit virtual interface (transit VIF) associated with a Direct Connect gateway provides the required dedicated private connection, high throughput, and consistent low latency. Associating the Direct Connect gateway with an AWS Transit Gateway in each Region enables highly scalable routing to multiple VPCs across different Regions, meeting the requirement to easily accommodate future VPCs.

Adım Adım Çözüm

1
Provision a dedicated connection using AWS Direct Connect.
A 10 Gbps10\text{ Gbps} private, dedicated physical connection is established between the on-premises datacenter and an AWS Direct Connect location.
Provides the required 10 Gbps10\text{ Gbps} throughput and consistent low-latency network performance.
2
Create a transit virtual interface (transit VIF) and associate it with a Direct Connect gateway.
The Direct Connect connection is logicalized to route traffic to the Direct Connect gateway using a Transit VIF.
A Transit VIF is required to connect AWS Direct Connect to AWS Transit Gateway.
3
Associate the Direct Connect gateway with AWS Transit Gateways in both the local and remote Regions.
The Direct Connect gateway routes traffic from the on-premises network to Transit Gateways across multiple AWS Regions.
Transit Gateway allows central management and scaling of connections to multiple VPCs in each Region, accommodating future VPC additions easily.

Anahtar Kavram

AWS Direct Connect combined with Direct Connect Gateway and AWS Transit Gateway provides high-performance, private, and highly scalable hybrid network architectures across multiple AWS Regions.
Tahmini Süre:2m 0s
Soru 687Soru

A financial services company runs a high-throughput processing application on AWS. The application has two primary compute requirements: a web-tier backend running on Amazon ECS using AWS Fargate that requires a continuous, predictable baseline of 6464 vCPUs and 256256 GB RAM 24/7, scaling up during peak business hours; and a batch-tier risk analysis job that runs nightly for 66 hours, requiring up to 1,0001,000 vCPUs of highly parallelized, fault-tolerant compute that checkpoints its state to Amazon DynamoDB. The application's database layer runs on an Amazon Aurora PostgreSQL DB cluster. Which two options should the solutions architect select to design a hosting and purchasing strategy that minimizes costs while meeting these requirements?

Geçerli olan tümünü seçin

Cevabı ve açıklamayı göster

Cevap: Purchase a Compute Savings Plan to cover the continuous 24/7 baseline of the Amazon ECS tasks running on AWS Fargate.; Deploy the batch processing tier on Amazon EC2 Spot Instances using an EC2 Fleet with a capacity-optimized allocation strategy.

Cevap

The correct strategy is to purchase a Compute Savings Plan for the steady-state Fargate tasks and deploy the fault-tolerant batch tier on Amazon EC2 Spot Instances.
Purchasing a Compute Savings Plan covers the continuous 24/7 baseline of the Amazon ECS tasks running on AWS Fargate. Deploying the batch processing tier on Amazon EC2 Spot Instances with a capacity-optimized allocation strategy minimizes compute costs for a parallelized, fault-tolerant workload that checkpoints its state.

Adım Adım Çözüm

1
Analyze the baseline compute requirement for the 24/7 ECS web tier.
The web tier runs on AWS Fargate continuously. Fargate compute costs are eligible for Compute Savings Plans, but not EC2 Instance Savings Plans.
This determines the correct discount type for the Fargate baseline usage.
2
Analyze the batch processing workload's characteristics.
The batch job runs for 6 hours, is highly parallelized, fault-tolerant, and checkpoints its state. This fits the profile for Spot Instances.
This selects the most cost-effective compute pricing model for transient, interruption-tolerant workloads.
3
Evaluate the database layer cost-optimization options.
Database costs for Amazon Aurora cannot be covered by EC2 Instance Savings Plans or Compute Savings Plans.
This rules out incorrect purchasing models that attempt to apply compute-specific Savings Plans to database services.

Anahtar Kavram

Selecting and combining cost-effective compute options (Compute Savings Plans, Spot Instances) based on workload stability, duration, tolerance to interruption, and service scope constraints.
Tahmini Süre:3m 0s
Soru 688Soru

A company is deploying a database application on a single Amazon EC2 instance. The database requires a dedicated block storage volume with 100 GB100\text{ GB} of capacity and a guaranteed performance of 10,000 IOPS10,000\text{ IOPS}. The performance must be provisioned independently of the volume size. Which AWS storage solution is the most cost-effective option that meets these requirements?

Cevabı ve açıklamayı göster

Cevap: An Amazon EBS gp3 volume

Cevap

An Amazon EBS gp3 volume is the most cost-effective block storage option that meets the requirements.
The correct answer is the option specifying an Amazon EBS gp3 volume. Amazon EBS gp3 is a General Purpose SSD volume type that allows customers to provision IOPS (up to 16,00016,000) and throughput (up to 1,000 MiB/s1,000\text{ MiB/s}) independently of the volume size. This provides a cost-effective solution for database workloads that require high IOPS (10,00010,000) with a relatively small storage capacity (100 GB100\text{ GB}), avoiding the need to over-provision storage size (as required by gp2) or pay for expensive provisioned IOPS volumes (io2).

Adım Adım Çözüm

1
Identify the storage type required by the application.
The database application runs on a single Amazon EC2 instance and requires a dedicated block storage volume.
Databases require block storage (EBS) rather than file (EFS) or object (S3) storage for high-performance transactions.
2
Evaluate the IOPS scaling requirements.
The volume needs 10,000 IOPS10,000\text{ IOPS} for a 100 GB100\text{ GB} capacity, with performance scaled independently of size.
This requirement rules out volume types like gp2 where IOPS scale strictly with storage size (3 IOPS3\text{ IOPS} per GB, requiring a 3.33 TB3.33\text{ TB} volume to get 10,000 IOPS10,000\text{ IOPS}).
3
Select the most cost-effective EBS volume type that supports independent IOPS provisioning.
Amazon EBS gp3 supports up to 16,000 IOPS16,000\text{ IOPS} independently of storage size at a lower cost than Provisioned IOPS (io2).
GP3 meets the 10,000 IOPS10,000\text{ IOPS} limit easily and is more cost-effective than IO2.

Anahtar Kavram

Provisioning independent IOPS and throughput on SSD-backed Amazon EBS volumes (gp3) for database workloads.
Soru 689Soru

An educational institution is migrating its student enrollment system to AWS and will use Amazon RDS for SQL Server. The database must remain highly available within the primary AWS Region with a recovery time objective (RTO) of less than 2 minutes in the event of an Availability Zone failure. Failover must be completely automated, requiring no updates to the database endpoint in the application's configuration. Which configuration will meet these requirements?

Cevabı ve açıklamayı göster

Cevap: A Multi-AZ DB instance deployment

Cevap

A Multi-AZ DB instance deployment
The Multi-AZ DB instance deployment configuration is correct because Amazon RDS automatically provisions and maintains a synchronous standby replica in a different Availability Zone within the same AWS Region. In the event of a planned or unplanned outage of the primary DB instance, Amazon RDS automatically performs a failover to the standby instance. This failover process typically completes in under 2 minutes and updates the DNS CNAME record of the DB instance to point to the standby, eliminating the need to update database endpoints in the application configuration.

Adım Adım Çözüm

1
Analyze the high availability and recovery requirements.
Identify that the system requires a Recovery Time Objective (RTO) of less than 2 minutes, automatic failover across Availability Zones, and no manual configuration changes to the database endpoint.
This sets the criteria for evaluating RDS deployment configurations.
2
Evaluate the capabilities of RDS Multi-AZ deployments.
Confirm that Multi-AZ deployments provide synchronous replication, automatic failover within 1-2 minutes, and automatic DNS CNAME redirection.
Multi-AZ directly satisfies all the stated constraints of the scenario.
3
Evaluate the alternative configurations against the requirements.
Determine that Read Replicas do not support automatic failover, snapshots have a high RTO for restores, and Route 53 routing cannot manage database failover state.
This rules out the incorrect options.

Anahtar Kavram

Amazon RDS Multi-AZ Deployments
Tahmini Süre:45s
Soru 690Soru

A company is setting up a hybrid network connection between its local office and a VPC. The connection requires a minimum bandwidth of 2 Gbps2\text{ Gbps}. The company implements a standard AWS Site-to-Site VPN connection, but network performance testing indicates that throughput is capped at 1.25 Gbps1.25\text{ Gbps} per tunnel. Which of the following actions should a solutions architect recommend to scale the VPN throughput to meet the requirement?

Cevabı ve açıklamayı göster

Cevap: Associate the Site-to-Site VPN connection with an AWS Transit Gateway and enable Equal-Cost Multi-Path (ECMP) routing to aggregate throughput across multiple tunnels.

Cevap

Associate the Site-to-Site VPN connection with an AWS Transit Gateway and enable Equal-Cost Multi-Path (ECMP) routing to aggregate throughput across multiple tunnels.
The correct option correctly identifies that a single AWS Site-to-Site VPN tunnel has a maximum throughput of 1.25 Gbps1.25\text{ Gbps}. To achieve a throughput of 2 Gbps2\text{ Gbps} or more, you must associate the VPN with an AWS Transit Gateway and enable Equal-Cost Multi-Path (ECMP) routing, which aggregates bandwidth across multiple active VPN tunnels.

Adım Adım Çözüm

1
Identify the bandwidth constraint of a single AWS Site-to-Site VPN tunnel, which is capped at 1.25 Gbps1.25\text{ Gbps}.
Confirming that a single tunnel cannot meet the 2 Gbps2\text{ Gbps} requirement.
To determine why the current setup is underperforming and how much additional bandwidth is needed.
2
Leverage AWS Transit Gateway to aggregate multiple VPN connections using Equal-Cost Multi-Path (ECMP) routing.
Enabling ECMP allows traffic to be dynamically load balanced across multiple tunnels, scaling overall throughput beyond 1.25 Gbps1.25\text{ Gbps}.
Transit Gateway support for ECMP allows multiple VPN tunnels to be pooled together to achieve higher aggregate throughput.

Anahtar Kavram

AWS Site-to-Site VPN throughput limits and Transit Gateway ECMP scaling
Tahmini Süre:1m 0s
Soru 691Soru

A gaming company is launching a multiplayer online game that stores player state updates in an Amazon DynamoDB table. The application performs up to 150,000150,000 write operations per second during peak hours. The partition key is currently designed as `GameSessionDate` (formatted as `YYYY-MM-DD`) and the sort key is `PlayerID`. During load testing, the database experiences write throttling even though the provisioned write capacity units (WCUs) are scaled far beyond the requirements. Additionally, the application requires sub-millisecond latency for game session read queries. Which database architecture modification should the solutions architect implement to resolve the performance bottleneck and meet the latency requirements?

Cevabı ve açıklamayı göster

Cevap: Redesign the table schema to append a randomized shard suffix to the `GameSessionDate` partition key, and deploy an Amazon DynamoDB Accelerator (DAX) cluster to cache read requests.

Cevap

Redesign the table schema to append a randomized shard suffix to the `GameSessionDate` partition key, and deploy an Amazon DynamoDB Accelerator (DAX) cluster to cache read requests.
The correct answer resolves the write throttling issue by implementing write sharding on the partition key. Appending a randomized suffix to the date partition key distributes the 150,000150,000 write operations per second across multiple physical partitions. Additionally, deploying DynamoDB Accelerator (DAX) satisfies the requirement for sub-millisecond read latency by providing an in-memory cache directly integrated with the database.

Adım Adım Çözüm

1
Analyze the current DynamoDB partition design and identify the bottleneck.
The partition key `GameSessionDate` only changes daily, causing all concurrent writes for a single day to hit the same partition.
DynamoDB distributes data across partitions based on the partition key. A single partition has performance limits (1,0001,000 WCUs and 3,0003,000 RCUs), leading to throttling when writes exceed these limits.
2
Introduce write sharding to distribute writes.
Appending a random shard suffix (e.g., 11 to NN) to the partition key distributes the write workload across multiple partitions.
This design ensures that write requests are spread evenly, preventing hot partitions and resolving the throttling issue.
3
Select the appropriate caching mechanism for sub-millisecond read queries.
Deploying a DynamoDB Accelerator (DAX) cluster provides in-memory caching directly integrated with DynamoDB.
DAX delivers microsecond response times for read queries and operates transparently without requiring application-level caching logic changes.

Anahtar Kavram

Partition key design, write sharding, and write/read performance scaling in Amazon DynamoDB.
Tahmini Süre:3m 0s
Soru 692Soru

A financial company is designing a high-performance computing (HPC) cluster running risk analysis models on a fleet of Amazon EC2 Linux instances. The workload requires a shared storage solution that supports standard NFSv4 mounts, delivers consistent sub-millisecond latencies for small-file random I/O, scales up to 100,000100\text{,000} IOPS and 3 GB/s3\text{ GB/s} of throughput, and enables the creation of instantaneous, space-efficient writable clones of the datasets for sandbox testing. Which two storage configurations will satisfy these requirements? (Select TWO.)

Geçerli olan tümünü seçin

Cevabı ve açıklamayı göster

Cevap: Deploy an Amazon FSx for OpenZFS file system, mount the volumes on the instances using NFSv4, and use the native ZFS snapshot and cloning capabilities to create staging environments.; Deploy an Amazon FSx for NetApp ONTAP file system, mount the volumes on the instances using NFSv4, and use the NetApp FlexClone feature to create instantaneous writable volume clones.

Cevap

The correct configurations are Amazon FSx for OpenZFS and Amazon FSx for NetApp ONTAP. Both support NFSv4 client mounts, deliver consistent sub-millisecond latencies, scale to the required performance limits, and offer native, near-instantaneous, space-efficient writable cloning capabilities.
The correct configurations are Amazon FSx for OpenZFS and Amazon FSx for NetApp ONTAP. Both solutions support standard NFSv4 protocols, provide consistent sub-millisecond SSD latencies, comfortably scale to 100,000100\text{,000} IOPS and 3 GB/s3\text{ GB/s} throughput, and natively support near-instantaneous, space-efficient writable cloning of datasets (via native ZFS cloning and NetApp FlexClone respectively).

Adım Adım Çözüm

1
Analyze the I/O, latency, protocol, and functional requirements of the shared storage solution.
The requirements are: shared access via standard NFSv4, sub-millisecond latency for small-file random I/O, 100,000100\text{,000} IOPS, 3 GB/s3\text{ GB/s} throughput, and instantaneous space-efficient writable clones.
This establishes the baseline metrics to filter out incompatible AWS storage services.
2
Evaluate Amazon EFS and Amazon EBS Multi-Attach against the requirements.
Amazon EFS cannot guarantee sub-millisecond latency for metadata and random I/O and lacks native instant writable cloning. Amazon EBS Multi-Attach is block storage (cannot natively format with NFSv4 or provide server-side instant writable file system clones).
This eliminates options that violate basic latency, storage type, or cloning speed constraints.
3
Evaluate FSx file systems (Lustre, OpenZFS, ONTAP) against the protocol and performance requirements.
Amazon FSx for Lustre is eliminated because it requires the Lustre client, not standard NFSv4. Amazon FSx for OpenZFS and FSx for NetApp ONTAP both fully support NFSv4, provide sub-millisecond SSD latency, scale to the requested IOPS/throughput, and support instant writable cloning (ZFS clones and NetApp FlexClone).
This identifies the two solutions that perfectly meet all the architectural requirements.

Anahtar Kavram

High-performance shared file systems with advanced data management capabilities (snapshots and clones) on AWS.
Soru 693Soru

A company runs a legacy application that must run continuously 24/7 on Amazon EC2 instances. The database tier is hosted on Amazon RDS for PostgreSQL and also runs continuously. The company wants to make a 3-year commitment to reduce their AWS costs for these resources. Which recommendation should a solutions architect make to achieve the most cost-effective architecture?

Cevabı ve açıklamayı göster

Cevap: Purchase a Compute Savings Plan to cover the Amazon EC2 instances, and purchase Amazon RDS Reserved Instances for the RDS database.

Cevap

Purchase a Compute Savings Plan to cover the Amazon EC2 instances, and purchase Amazon RDS Reserved Instances for the RDS database.
Purchasing a Compute Savings Plan covers the Amazon EC2 instances, while purchasing Amazon RDS Reserved Instances provides a discount for the Amazon RDS database. This combination correctly applies the appropriate purchasing model to each service and maximizes savings over the 3-year term.

Adım Adım Çözüm

1
Analyze the compute requirements for the Amazon EC2 instances and the Amazon RDS database.
Identify that the EC2 instances run continuously and the RDS database also runs continuously.
This determines that long-term commitment models are suitable for both components.
2
Evaluate the scope of Compute Savings Plans and EC2 Instance Savings Plans.
Confirm that Savings Plans apply only to compute services (EC2, Fargate, Lambda) and do not apply to Amazon RDS.
This rules out using Savings Plans to discount the RDS database tier.
3
Select the appropriate purchasing strategies for each service.
Apply Compute Savings Plans to the EC2 instances and purchase RDS Reserved Instances for the RDS database.
This combination maximizes the discount for both resource types based on a 3-year commitment.

Anahtar Kavram

Compute Savings Plans vs RDS Reserved Instances scope
Tahmini Süre:1m 30s
Soru 694Soru

A global company hosts a dynamic financial API across Application Load Balancers (ALBs) in the us-east-1 (primary) and eu-west-1 (secondary standby) Regions. The API requires ultra-low latency SSL/TLS handshakes, protection against Layer 7 SQL injection attacks, and immediate failover to the secondary region if the primary region's ALB starts returning HTTP 502 or 504 errors. The failover process must occur within seconds without relying on client-side DNS updates, and operational complexity must be kept to a minimum. Which of the following combinations of actions should the solutions architect take to meet these requirements? (Select TWO.)

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Cevabı ve açıklamayı göster

Cevap: Create an Amazon CloudFront distribution and configure an origin group containing the us-east-1 ALB as the primary origin and the eu-west-1 ALB as the secondary origin, setting the failover criteria to include 502 and 504 status codes.; Associate an AWS WAF web ACL directly with the Amazon CloudFront distribution to inspect incoming requests at the edge before they reach the ALBs.

Cevap

The solutions architect should create an Amazon CloudFront distribution with an origin group containing the primary us-east-1 ALB and the secondary eu-west-1 ALB (with failover criteria for 502 and 504 errors), and associate an AWS WAF web ACL directly with the CloudFront distribution.
Configuring CloudFront Origin Groups ensures that failover between the primary ALB in us-east-1 and the standby ALB in eu-west-1 happens within seconds at the CDN edge level, bypassing client-side DNS caching. Associating AWS WAF with CloudFront provides L7 security inspection at the edge, reducing latency and operational complexity by avoiding the management of multiple regional WAF ACLs.

Adım Adım Çözüm

1
Analyze the requirements for edge caching, low-latency handshakes, second-level failover, and Layer 7 protection.
Identify that DNS-based failover (Route 53) is too slow (minutes) due to TTL caching, whereas CloudFront Origin Groups handle failover at the CDN layer within seconds.
Choosing the correct failover mechanism is critical to meet the strict recovery time objective (seconds) and minimize handshake latency globally.
2
Select the edge-level resiliency configuration.
Determine that a CloudFront distribution with origin groups configured for failover on HTTP 502 and 504 codes matches the requirements.
This allows CloudFront to immediately retry requests on the secondary origin when the primary returns error responses, without requiring client DNS updates.
3
Evaluate security requirements for Layer 7 SQL injection protection.
Select AWS WAF associated directly with the CloudFront distribution to inspect traffic at the edge.
This provides L7 protection before traffic reaches the ALBs, reduces origin load, and simplifies operations compared to deploying regional WAFs on individual ALBs. AWS Shield Standard does not provide Layer 7 application filtering.

Anahtar Kavram

CloudFront Origin Groups provide sub-second failover for origin endpoints, while AWS WAF at the edge provides centralized Layer 7 protection and reduces latency by filtering requests before they reach regional infrastructure.
Soru 695Soru

A company is hosting a production web application on AWS that uses an Amazon RDS for MySQL DB instance. The database must be designed to survive the failure of a single Availability Zone (AZ) with minimal downtime and automatic failover. Additionally, the application requires read scaling to handle a high volume of reporting queries.

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

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Cevabı ve açıklamayı göster

Cevap: Deploy the RDS DB instance in a Multi-AZ configuration; Create one or more RDS Read Replicas for the database

Cevap

Deploy the RDS DB instance in a Multi-AZ configuration and create one or more RDS Read Replicas for the database.
To achieve high availability and automatic failover, the RDS instance should be deployed in a Multi-AZ configuration. To scale read traffic, one or more Read Replicas should be created.

Adım Adım Çözüm

1
Address the high availability and automatic failover requirement.
Identify that configuring the RDS instance for Multi-AZ deployment will automatically provision a synchronous standby replica in another Availability Zone, enabling automated failover.
Multi-AZ is the native AWS solution for high availability and automatic failover of RDS databases.
2
Address the read scaling requirement.
Identify that adding RDS Read Replicas allows the application to route read-heavy reporting queries to the replicas, reducing load on the primary DB instance.
Read Replicas asynchronously replicate data from the primary instance to support scaling read traffic.

Anahtar Kavram

High availability is achieved through Multi-AZ deployments, while read performance is scaled through Read Replicas.
Soru 696Soru

A company is deploying a media processing application on a fleet of Amazon EC2 instances. The application requires a high-performance, shared storage solution that supports POSIX-compliant file operations and can be accessed concurrently by all instances. Which two AWS storage services should the company use to meet these requirements? (Select TWO.)

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Cevabı ve açıklamayı göster

Cevap: Amazon Elastic File System (Amazon EFS); Amazon FSx for NetApp ONTAP

Cevap

Amazon Elastic File System (Amazon EFS) and Amazon FSx for NetApp ONTAP
The correct options are the Elastic File System and FSx for NetApp ONTAP. Both are native AWS shared file systems that support POSIX-compliant file operations, allowing multiple EC2 instances to read and write to the same storage space concurrently.

Adım Adım Çözüm

1
Identify that the workload requires a shared, POSIX-compliant file system accessible by multiple EC2 instances concurrently.
Identified the requirement for native file storage rather than block or object storage.
This helps narrow down the choices to shared file systems like Amazon EFS and Amazon FSx.
2
Evaluate the block storage options (Amazon EBS gp3 and st1).
Determined that standard EBS volumes are block storage designed for single-instance attachment.
This rules out EBS options as they cannot natively act as shared, multi-instance file systems.
3
Evaluate the object storage option (Amazon S3 Standard-IA).
Determined that Amazon S3 is object storage and does not support POSIX-compliant file operations natively.
This rules out S3 for this active file system workload.
4
Select the correct file storage solutions.
Selected Amazon EFS and Amazon FSx for NetApp ONTAP.
Both services are designed to offer high-performing, POSIX-compliant, concurrent shared file access for EC2 instances.

Anahtar Kavram

Distinguishing between block, file, and object storage requirements, and selecting native AWS shared file systems (Amazon EFS and Amazon FSx) for multi-instance POSIX-compliant concurrent access.
Soru 697Soru

A healthtech startup has migrated its core application platform to AWS and wants to establish the most cost-optimized compute purchasing strategy. The application workload consists of:

* An API tier running on Amazon ECS using AWS Fargate that requires a continuous, predictable baseline of 1.50perhourincomputecosts,24/7.AdatabasetierrunningonAmazonRDSforMySQLthatrequiresacontinuous,predictablebaselineof1.50 per hour in compute costs, 24/7. * A database tier running on Amazon RDS for MySQL that requires a continuous, predictable baseline of 2.00 per hour in database compute costs, 24/7.
* A daily data transformation process running on Amazon ECS using AWS Fargate that is highly fault-tolerant, runs for 2 hours every night, and can scale up to 50 tasks dynamically.
* An ad-hoc analytics training model running on Amazon EC2 GPU instances for exactly 6 hours every Saturday, which must run to completion without interruption.

Which strategy meets these requirements at the lowest cost?

Cevabı ve açıklamayı göster

Cevap: Purchase a Compute Savings Plan to cover the baseline Fargate API tier. Purchase Amazon RDS Reserved Instances to cover the database tier. Use Fargate Spot for the daily data transformation tasks, and use On-Demand Instances for the weekly EC2 GPU analytics training.

Cevap

Purchase a Compute Savings Plan to cover the baseline Fargate API tier, purchase Amazon RDS Reserved Instances for the database tier, use Fargate Spot for the daily data transformation tasks, and use On-Demand Instances for the weekly EC2 GPU analytics training.
The correct strategy leverages the appropriate discount mechanism for each service type and workload characteristic. A Compute Savings Plan is selected for the baseline AWS Fargate API tier. Amazon RDS Reserved Instances are selected for the database tier since database compute is excluded from Compute Savings Plans. Fargate Spot is chosen for the daily data transformation process as it is fault-tolerant and containerized. On-Demand instances are chosen for the weekly GPU analytics training because its low duty cycle (6 hours per week) makes a 24/7 Savings Plan commitment economically inefficient, and its requirement to run to completion without interruption rules out Spot instances.

Adım Adım Çözüm

1
Analyze the API tier requirements.
The API runs on AWS Fargate 24/7. Since this is a continuous, predictable compute workload, a Compute Savings Plan is the ideal purchasing model, offering up to 66% savings over On-Demand.
Baseline 24/7 compute workloads benefit most from Savings Plans.
2
Analyze the database tier requirements.
The database runs on Amazon RDS 24/7. Compute Savings Plans do not cover Amazon RDS. Instead, RDS Reserved Instances must be purchased to secure a discount on this steady-state database workload.
Savings Plans and Reserved Instances have distinct scopes.
3
Analyze the daily data transformation process.
The process runs on Fargate for 2 hours daily and is highly fault-tolerant. Fargate Spot is the most cost-effective option here, providing up to 70% discount compared to standard Fargate.
Fault-tolerant, containerized batch workloads are a perfect fit for Spot capacity.
4
Analyze the weekly GPU analytics training.
The training runs on EC2 GPU instances for only 6 hours a week and cannot be interrupted. Because it cannot be interrupted, Spot Instances cannot be used. Because it runs for only 6 hours out of 168 hours in a week, committing to a Savings Plan would result in paying for 162 hours of idle time. Therefore, On-Demand is the most cost-effective choice.
Intermittent, non-interruptible workloads with low weekly utilization should use On-Demand rather than commitments.

Anahtar Kavram

Selecting cost-optimized compute types and purchasing models based on workload predictability, execution duration, and service type.
Tahmini Süre:3m 0s
Soru 698Soru

A company hosts a website with static images stored in an Amazon S3 bucket and uses an Amazon DynamoDB table to store product catalog details. The company wants to optimize performance by caching both static and database content to reduce read latency for users. Which two configurations should the solutions architect recommend to meet these requirements?

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Cevabı ve açıklamayı göster

Cevap: Deploy an Amazon CloudFront distribution to cache and serve the static assets from the Amazon S3 bucket.; Implement Amazon DynamoDB Accelerator (DAX) in front of the database to cache read requests.

Cevap

Deploy an Amazon CloudFront distribution to cache and serve the static assets from the Amazon S3 bucket, and implement Amazon DynamoDB Accelerator (DAX) in front of the database to cache read requests.
Deploying Amazon CloudFront in front of the Amazon S3 bucket caches static assets at edge locations closer to users, reducing latency. Implementing Amazon DynamoDB Accelerator (DAX) provides an in-memory cache directly in front of DynamoDB tables, reducing database read latencies from milliseconds to microseconds.

Adım Adım Çözüm

1
Identify the caching mechanism needed for static assets hosted in Amazon S3.
Amazon CloudFront distribution caches static assets at edge locations close to users.
This reduces read latency and offloads requests from the origin S3 bucket.
2
Identify the caching mechanism needed for Amazon DynamoDB read queries.
Amazon DynamoDB Accelerator (DAX) caches read requests in-memory.
This provides microsecond latency for frequent read operations without overhead on the main table.

Anahtar Kavram

Using Amazon CloudFront and Amazon DynamoDB Accelerator (DAX) to implement high-performing, multi-tiered caching for static assets and database reads.
Soru 699Soru

A self-driving vehicle company is running deep learning model training workloads on a cluster of GPU-enabled Amazon EC2 instances. The training jobs process a shared dataset of 60 TB60\text{ TB} consisting of millions of small image files. The storage solution must provide a POSIX-compliant filesystem, support concurrent read and write access from all EC2 instances, deliver aggregate throughput of up to 15 GB/s15\text{ GB/s} with sub-millisecond latencies, and integrate directly with Amazon S3 to load and unload data.

Which storage solution should a solutions architect recommend to meet these requirements?

Cevabı ve açıklamayı göster

Cevap: Configure an Amazon FSx for Lustre SSD-backed file system linked to the Amazon S3 bucket containing the dataset.

Cevap

Configure an Amazon FSx for Lustre SSD-backed file system linked to the Amazon S3 bucket containing the dataset.
The correct option correctly recommends Amazon FSx for Lustre SSD-backed storage because it is optimized for high-performance computing (HPC) and deep learning workloads. It supports POSIX compliance, concurrent access from many GPU instances, sub-millisecond latencies, high throughput scaling, and native bi-directional integration with S3.

Adım Adım Çözüm

1
Analyze the workload characteristics and requirements.
The workload requires a POSIX-compliant shared file system, concurrent read/write from multiple EC2 instances, very high aggregate throughput (15 GB/s15\text{ GB/s}), sub-millisecond latencies for processing millions of small files, and S3 integration.
Identifying these key requirements helps filter out block storage and standard general-purpose file storage systems.
2
Evaluate Amazon FSx for Lustre against the requirements.
FSx for Lustre provides a POSIX-compliant file system optimized for parallel computing, machine learning, and high-throughput workloads. SSD-backed deployment delivers sub-millisecond latencies. It integrates natively with S3 to load and write back data automatically.
This confirms that FSx for Lustre is the ideal architectural fit.
3
Evaluate and rule out EFS, EBS, and S3 Glacier options.
EFS does not meet the latency and throughput profile for millions of small files in GPU training. EBS gp3 does not support Multi-Attach. AWS File Gateway with S3 Glacier Instant Retrieval is not built for high-performance local cluster processing.
Ensuring other options are incorrect validates the final recommendation.

Anahtar Kavram

Selecting high-performance and scalable shared storage for ML/HPC workloads using Amazon FSx for Lustre.
Soru 700Soru

A real-time bidding application uses Amazon DynamoDB to track active auctions. During peak bidding hours, the write volume spikes to 120,000120,000 writes per second, causing some write requests to fail with `ProvisionedThroughputExceededException` errors, even though the total provisioned write capacity is sufficient for the workload. Additionally, the application requires microsecond-latency reads to retrieve auction details, and concurrent analytics queries are degrading the write performance of active auctions.

Which two actions should the solutions architect take to resolve these performance issues? (Select TWO.)

Geçerli olan tümünü seçin

Cevabı ve açıklamayı göster

Cevap: Deploy an Amazon DynamoDB Accelerator (DAX) cluster to handle read requests for auction details with microsecond latency.; Redesign the partition key schema by appending a random suffix to the auction ID to distribute write requests evenly across partitions.

Cevap

Deploying an Amazon DynamoDB Accelerator (DAX) cluster to handle read requests and redesigning the partition key schema by appending a random suffix to the auction ID.
The correct response involves deploying an Amazon DynamoDB Accelerator (DAX) cluster to cache read requests, reducing read latency to microseconds and offloading read traffic from the table to prevent read contention. It also requires redesigning the partition key schema to append a random suffix to the partition keys, which implements write sharding and distributes the highly concentrated write load across multiple partition keys, thereby preventing write bottlenecks on a single hot partition.

Adım Adım Çözüm

1
Analyze the database performance bottleneck under the high write volume of 120,000120,000 writes per second.
Identify that the throttling errors, despite sufficient total provisioned capacity, are caused by uneven access patterns resulting in one or more hot partitions.
DynamoDB distributes data across partitions based on the partition key value, so sequential or concentrated keys overload individual partitions.
2
Determine the correct strategy to mitigate hot partition keys and distribute write operations.
Select the option to append a randomized suffix (sharding) to the partition key (auction ID).
This distributes the writes for the same auction across multiple physical partitions, utilizing the provisioned throughput of the entire table.
3
Analyze the read performance requirement of microsecond-level latency and read contention from reporting queries.
Select Amazon DynamoDB Accelerator (DAX) to serve reads directly from an in-memory cache.
DAX provides microsecond latency for cached reads and offloads read requests from the DynamoDB table, preventing read contention from degrading write performance.

Anahtar Kavram

Mitigating DynamoDB partition write bottlenecks (hot keys) and improving read latency using in-memory caching (DAX).
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