Tüm alıştırma soruları

1462 soru

Soru 741Soru

A smart home security company is designing a high-performing ingestion pipeline for security camera event logs. The pipeline must ingest log payloads from 100,000100,000 cameras, with each camera sending a 1 KB1 \text{ KB} JSON payload every 5 seconds5 \text{ seconds}. The solution must process these logs with sub-second latency to perform anomaly detection and trigger immediate alerts. Additionally, all raw logs must be archived in Amazon S3 for historical analysis, partitioned by date. Which two actions should a solutions architect recommend to meet these requirements with the lowest operational overhead? (Select two.)

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Cevabı ve açıklamayı göster

Cevap: Configure an Amazon Kinesis Data Stream in On-Demand capacity mode to ingest the camera event logs, and use an AWS Lambda function to process the stream for real-time anomaly detection.; Configure an Amazon Kinesis Data Firehose delivery stream that uses the Kinesis Data Stream as the source to batch and write the raw logs to Amazon S3, using custom prefixes for date-based partitioning.

Cevap

Configure an Amazon Kinesis Data Stream in On-Demand capacity mode to ingest the camera event logs, and use an AWS Lambda function to process the stream for real-time anomaly detection. Additionally, configure an Amazon Kinesis Data Firehose delivery stream that uses the Kinesis Data Stream as the source to batch and write the raw logs to Amazon S3, using custom prefixes for date-based partitioning.
The correct architecture leverages Amazon Kinesis Data Streams in On-Demand capacity mode to ingest the 20 MB/s20 \text{ MB/s} stream of security camera logs, which automatically scales to support 20,00020,000 records per second without administrative intervention. An AWS Lambda function consumes this stream to trigger anomalies with sub-second latency. To satisfy the archiving requirement, Amazon Kinesis Data Firehose reads from the same Kinesis Data Stream, batches the records, and writes them to Amazon S3 using date-based partitioning prefixes, optimizing both cost and operational complexity.

Adım Adım Çözüm

1
Calculate the ingestion throughput requirements.
The total ingestion rate is 100,000 cameras/5 seconds=20,000 records/second100,000 \text{ cameras} / 5 \text{ seconds} = 20,000 \text{ records/second}. The total bandwidth is 20,000 records/second×1 KB/record=20 MB/second20,000 \text{ records/second} \times 1 \text{ KB/record} = 20 \text{ MB/second}.
Determining the throughput ensures the chosen ingestion technology is scaled correctly.
2
Select the ingestion and real-time processing technology.
Amazon Kinesis Data Streams in On-Demand capacity mode automatically handles up to 200 MB/s200 \text{ MB/s} and 200,000200,000 records/second of write capacity. An AWS Lambda function is configured to read from this stream to achieve sub-second latency alerts.
On-Demand mode prevents ProvisionedThroughputExceededException and minimizes management overhead.
3
Select the historical archiving mechanism.
An Amazon Kinesis Data Firehose delivery stream is configured to consume the data from the Kinesis Data Stream and write it to Amazon S3 in batches.
Firehose handles partitioning and batching automatically with minimal operational effort.

Anahtar Kavram

Decoupling high-performance stream ingestion for real-time processing and managed archiving using Amazon Kinesis Data Streams and Amazon Kinesis Data Firehose.
Soru 742Soru

An e-commerce company is migrating its primary transactional database to Amazon RDS for MySQL. The database design must meet the following operational requirements:

* Within the primary AWS Region, the database must support automatic failover with a Recovery Time Objective (RTO) of less than 4040 seconds.
* The architecture must allow read workloads to scale horizontally across multiple Availability Zones in the primary Region without querying the primary writer instance.
* For disaster recovery, the database must support cross-Region replication to a secondary Region with a Recovery Point Objective (RPO) of less than 1515 minutes.

Which database configuration meets these requirements with the least operational complexity?

Cevabı ve açıklamayı göster

Cevap: Deploy an Amazon RDS Multi-AZ DB cluster containing one primary writer and two readable standby instances across three Availability Zones. Configure an asynchronous cross-Region read replica in the secondary Region.

Cevap

Deploy an Amazon RDS Multi-AZ DB cluster containing one primary writer and two readable standby instances across three Availability Zones. Configure an asynchronous cross-Region read replica in the secondary Region.
The configuration utilizing an Amazon RDS Multi-AZ DB cluster satisfies all operational requirements. It provides a primary writer and two readable standby instances across three Availability Zones. Failover in a Multi-AZ DB cluster is typically completed in under 3535 seconds (meeting the 4040-second RTO limit). Additionally, because both standby instances are readable, the application can scale read workloads without querying the primary writer. A cross-Region read replica provides asynchronous, near-real-time replication, meeting the RPO of less than 1515 minutes.

Adım Adım Çözüm

1
Analyze the local high availability and RTO requirement.
An RTO of less than 4040 seconds rules out standard RDS Multi-AZ DB instances (which take 6060 to 120120 seconds to failover) and Single-AZ instances. An RDS Multi-AZ DB cluster uses semi-synchronous replication with a failover time of under 3535 seconds, meeting the target.
Determining the correct local deployment configuration is critical to meeting the low RTO threshold.
2
Evaluate the read-scaling requirement in the primary Region.
Standard RDS Multi-AZ DB instances have a passive, non-readable standby. An RDS Multi-AZ DB cluster features two readable standby instances that can serve read traffic directly, reducing operational complexity compared to provisioning separate read replicas.
Identifying the scaling capabilities of readable standby instances versus passive standby instances ensures read requirements are met efficiently.
3
Evaluate the cross-Region disaster recovery and RPO requirement.
An RPO of less than 1515 minutes requires continuous or near-continuous replication. An asynchronous cross-Region read replica continuously replicates data from the primary cluster, providing a low RPO (usually seconds). Replicating snapshots every 1212 hours fails this RPO.
Verifying the replication mechanism ensures the RPO constraint is satisfied.

Anahtar Kavram

Selecting between Amazon RDS Multi-AZ DB instances, Multi-AZ DB clusters, and cross-Region read replicas to satisfy strict RTO, RPO, and read scaling requirements.
Tahmini Süre:2m 30s
Soru 743Soru

An enterprise is migrating a containerized microservices application to AWS. The architecture consists of a steady-state backend API running on Amazon Elastic Container Service (Amazon ECS) on AWS Fargate, a relational database running on Amazon RDS for PostgreSQL, and a data warehouse hosted on Amazon Redshift. The compute requirements are as follows:

- The ECS backend API requires a constant baseline of 80 vCPU80\text{ vCPU} and 320 GiB320\text{ GiB} of memory running 24/7.
- A nightly batch analytics job runs on ECS Fargate for 3 hours, requiring an additional 120 vCPU120\text{ vCPU} and 480 GiB480\text{ GiB} of memory. The batch job is fault-tolerant and can resume if interrupted.
- The RDS database requires a constant baseline of 16 vCPU16\text{ vCPU} and 64 GiB64\text{ GiB} of memory running 24/7.
- The Amazon Redshift cluster runs continuously to serve near-real-time business intelligence dashboards.

The enterprise wants to minimize costs over a 3-year period by committing to a purchasing strategy, while minimizing operational overhead.

Which purchasing strategy will achieve the lowest cost for these requirements?

Cevabı ve açıklamayı göster

Cevap: Commit to a 3-year Compute Savings Plan for the baseline ECS Fargate compute. Purchase 3-year Reserved Instances for both the RDS PostgreSQL database and the Amazon Redshift cluster. Run the nightly batch jobs using Fargate Spot.

Cevap

Commit to a 3-year Compute Savings Plan for the baseline ECS Fargate compute, purchase 3-year Reserved Instances for both the RDS PostgreSQL database and the Amazon Redshift cluster, and run the nightly batch jobs using Fargate Spot.
The correct strategy combines a 3-year Compute Savings Plan for AWS Fargate baseline compute, 3-year Reserved Instances/Nodes for RDS and Redshift (since they are out of scope for Compute Savings Plans), and Fargate Spot for the fault-tolerant nightly batch job to achieve the maximum discount without commitment waste.

Adım Adım Çözüm

1
Identify the steady-state and transient compute workloads.
Steady-state workloads: ECS Fargate API (24/7), RDS PostgreSQL (24/7), and Amazon Redshift (24/7). Transient workload: Nightly batch analytics job on ECS Fargate (3 hours/day).
Separating workloads helps determine where long-term commitment models apply versus flexible/spot models.
2
Select the correct purchasing model for the steady-state container compute.
A 3-year Compute Savings Plan is selected to cover the baseline ECS Fargate compute (80 vCPU80\text{ vCPU} and 320 GiB320\text{ GiB} of memory).
Compute Savings Plans apply to AWS Fargate, EC2, and Lambda, providing the maximum discount for continuous container workloads.
3
Determine the purchasing model for the database and data warehouse tiers.
Purchase a 3-year RDS Reserved Instance for the PostgreSQL database and a 3-year Redshift Reserved Node for the Redshift cluster.
Compute Savings Plans do not apply to RDS or Redshift. Dedicated Reserved Instances/Nodes must be purchased to reduce costs for these continuous database and data warehouse workloads.
4
Select the optimal purchasing model for the transient, fault-tolerant batch job.
Configure the nightly batch job to run on ECS Fargate Spot.
Since the batch job is fault-tolerant and runs for only 3 hours a day, Fargate Spot provides up to a 70% discount compared to On-Demand rates without incurring the 24/7 commitment costs of a Savings Plan.

Anahtar Kavram

Selecting cost-optimized compute purchasing strategies based on workload duration, service compatibility, and fault tolerance.
Tahmini Süre:3m 0s
Soru 744Soru

A logistics company is designing an ingestion pipeline for real-time tracking data from a fleet of 50,00050,000 delivery vehicles. Each vehicle transmits a 1.5 KB1.5\text{ KB} JSON location update every 5 seconds5\text{ seconds}. The company has two primary requirements: real-time route optimization calculations with a latency of less than one second, and storing the data in Amazon S3 in Apache Parquet format for long-term historical query analysis using Amazon Athena. Which combination of actions will meet these requirements with the highest performance? (Select two.)

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Cevabı ve açıklamayı göster

Cevap: Configure an Amazon Kinesis Data Stream with at least 15 shards to ingest the tracking data, and use a real-time consuming application to process the stream for route optimization.; Configure an Amazon Kinesis Data Firehose delivery stream with the Kinesis Data Stream as the source to convert the JSON payloads to Apache Parquet using AWS Glue, and deliver the data to Amazon S3.

Cevap

Configure an Amazon Kinesis Data Stream with at least 15 shards to ingest the tracking data for real-time processing, and configure an Amazon Kinesis Data Firehose delivery stream with the Kinesis Data Stream as the source to convert the data to Apache Parquet and deliver it to Amazon S3.
To process the ingestion of 10,00010,000 records/sec at 15 MB/sec15\text{ MB/sec}, Amazon Kinesis Data Streams is provisioned with at least 15 shards because each shard supports up to 1 MB/sec1\text{ MB/sec} write throughput or 1,0001,000 records/sec. A real-time consumer application processes the stream directly to achieve sub-second latency. To satisfy the storage and query optimization requirements, Kinesis Data Firehose is configured to read from the Kinesis Data Stream, convert the format to Apache Parquet using AWS Glue, and write the records to Amazon S3.

Adım Adım Çözüm

1
Calculate the required ingestion throughput and record rate to properly size the streaming service.
The fleet generates 10,00010,000 records per second (50,00050,000 vehicles / 55 seconds) and a total write throughput of 15 MB/sec15\text{ MB/sec} (10,000×1.5 KB10,000 \times 1.5\text{ KB}).
Correct sizing is necessary to avoid ingestion bottlenecks and scale limits.
2
Select the ingestion service that supports sub-second latency and multiple consumers.
Amazon Kinesis Data Streams is chosen with at least 15 shards, as each shard supports up to 1 MB/sec1\text{ MB/sec} or 1,0001,000 records/sec write throughput.
This meets the sub-second route optimization calculation latency requirement.
3
Select the component for long-term storage format conversion and S3 delivery.
Amazon Kinesis Data Firehose delivery stream is configured to consume from the Kinesis Data Stream, use AWS Glue Data Catalog for format conversion to Parquet, and write to S3.
This provides serverless, performant transformation and delivery without impacting the real-time consumer.

Anahtar Kavram

Designing high-performing real-time data ingestion pipelines with Kinesis Data Streams and Firehose, calculating shard requirements, and performing schema-based conversions.
Tahmini Süre:1m 30s
Soru 745Soru

A geographic information system (GIS) platform processes real-time satellite imagery using a fleet of Amazon EC2 instances launched in an Auto Scaling group across multiple Availability Zones. The instances require a highly available, shared file system that supports simultaneous read and write access with sub-millisecond latencies to coordinate mapping files. Additionally, the raw images must be backed up to a secondary AWS Region to comply with disaster recovery policies. The system must achieve a Recovery Point Objective (RPO) of 1515 minutes and a Recovery Time Objective (RTO) of 1010 minutes.

Which combination of AWS storage configurations will meet these requirements? (Select TWO.)

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Cevabı ve açıklamayı göster

Cevap: Configure an Amazon Elastic File System (Amazon EFS) file system to store the active mapping files, and mount it on the EC2 instances in each Availability Zone.; Store the raw images in an Amazon S3 bucket, and configure Cross-Region Replication (CRR) with S3 Replication Time Control (S3 RTC) enabled to the secondary Region.

Cevap

Configuring an Amazon EFS file system to store active mapping files and storing raw images in an Amazon S3 bucket with Cross-Region Replication (CRR) and S3 Replication Time Control (S3 RTC) enabled.
The correct configurations combine Amazon EFS and Amazon S3 with Cross-Region Replication (CRR) and S3 Replication Time Control (S3 RTC). Amazon EFS provides a serverless, highly available shared network file system that supports concurrent read and write access for EC2 instances across multiple Availability Zones with sub-millisecond latencies. Amazon S3 CRR with S3 RTC enabled replicates 99%99\% of objects to a secondary AWS Region within 1515 minutes, fulfilling the 1515-minute RPO. Because the replicated files are immediately readable in the destination bucket, the solution also easily meets the 1010-minute RTO.

Adım Adım Çözüm

1
Analyze the active shared file system requirements.
The file system must be accessible concurrently by multiple EC2 instances across different Availability Zones with low latency.
This identifies Amazon EFS as the correct solution because it is designed for multi-AZ, concurrent file system access, whereas EBS volumes are generally restricted to a single Availability Zone.
2
Analyze the disaster recovery replication requirements for raw images.
The backup must have an RPO of 1515 minutes and an RTO of 1010 minutes.
This establishes that replication must happen in near real-time and retrieval must be immediate.
3
Evaluate S3 Replication Time Control (S3 RTC) against the RPO.
S3 RTC guarantees replication of 99%99\% of objects within 1515 minutes, satisfying the RPO.
Standard Cross-Region Replication does not guarantee a replication window, making S3 RTC necessary to meet the strict SLA.
4
Evaluate the retrieval speed of the replica for the RTO.
Since S3 replicated data is immediately accessible as standard object storage in the destination Region, it satisfies the 1010-minute RTO.
This rules out S3 Glacier classes which introduce retrieval delays exceeding the RTO.

Anahtar Kavram

Designing highly available, multi-AZ shared file systems and cross-region replication configurations with tight RPO and RTO SLA bounds.
Tahmini Süre:2m 0s
Soru 746Soru

A company is deploying a new web application on AWS. The application consists of Amazon EC2 instances running a steady-state web server 24/7, and an Amazon DynamoDB table storing session data with highly spiky and unpredictable access patterns. Which TWO strategies should a solutions architect select to run this workload in the most cost-effective manner?

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Cevabı ve açıklamayı göster

Cevap: Purchase a Compute Savings Plan to cover the Amazon EC2 instances.; Configure the Amazon DynamoDB table to use On-Demand capacity mode.

Cevap

Select the option to purchase a Compute Savings Plan for the EC2 instances, and the option to configure the DynamoDB table to use On-Demand capacity mode.
Purchasing a Compute Savings Plan is the most cost-effective way to run the steady-state 24/7 EC2 instances because it offers significant discounts in exchange for a usage commitment. Additionally, configuring the DynamoDB table to use On-Demand capacity mode is optimal for spiky, unpredictable workloads, as it charges per request and avoids the waste of over-provisioning capacity that goes unused during low-traffic periods.

Adım Adım Çözüm

1
Analyze the compute requirements for the web server.
The web server runs 24/7 in a steady state, meaning it has a constant, baseline compute usage.
Identifying the workload behavior helps choose the appropriate purchasing option (e.g., Savings Plans or Reserved Instances rather than On-Demand or Spot).
2
Analyze the database requirements for the session data.
The DynamoDB table has highly spiky and unpredictable access patterns.
Determining traffic predictability is key to choosing between Provisioned and On-Demand capacity modes for DynamoDB.
3
Select the most cost-effective purchasing strategies for each component.
Apply a Compute Savings Plan to the EC2 instances to reduce steady-state costs, and use On-Demand capacity mode for DynamoDB to pay only for actual requests and avoid over-provisioning.
This combination minimizes costs while meeting performance requirements for both workloads without misapplying discount scopes.

Anahtar Kavram

Selecting cost-effective purchasing strategies (Compute Savings Plans vs. On-Demand vs. Provisioned Capacity) based on workload predictability and service compatibility.
Soru 747Soru

A company runs a financial transaction processing application on a fleet of containerized microservices using Amazon ECS on AWS Fargate. The containers are distributed across multiple Availability Zones for high availability. The application requires a shared, POSIX-compliant file system to store transaction logs and state information. The workload is highly unpredictable, with sharp traffic spikes during market open and close, requiring throughput to scale rapidly up to 3 GB/s3\text{ GB/s} during peak times while remaining minimal during off-hours. The storage solution must deliver consistent, sub-millisecond latencies for file operations. Which two actions should a solutions architect take to configure the storage solution for this application? (Choose two.)

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Cevabı ve açıklamayı göster

Cevap: Create an Amazon Elastic File System (Amazon EFS) file system; Configure the file system to use Elastic throughput

Cevap

To meet the requirements of a shared POSIX-compliant file system with sub-millisecond latencies and unpredictable throughput needs on AWS Fargate across multiple Availability Zones, the solutions architect should create an Amazon Elastic File System (Amazon EFS) and configure it to use Elastic throughput.
Creating an Amazon Elastic File System (Amazon EFS) file system provides a fully managed, shared network file system that natively integrates with Amazon ECS on AWS Fargate, allowing task containers in multiple Availability Zones to concurrently read and write data. Configuring the file system with Elastic throughput allows it to dynamically scale performance up to the required 3 GB/s3\text{ GB/s} without manual administrative overhead or over-provisioning cost, charging only for the data read and written.

Adım Adım Çözüm

1
Identify compute and connectivity requirements
The application runs on Amazon ECS with AWS Fargate across multiple Availability Zones, which requires a shared, POSIX-compliant network file system that supports concurrent read/write access from independent containers across different zones.
This rules out Amazon EBS, which is a block storage service restricted to a single Availability Zone and not natively shareable across tasks in different Availability Zones without specialized clustering software.
2
Select the correct file system service
Select Amazon Elastic File System (Amazon EFS), which natively integrates with Amazon ECS on AWS Fargate and allows concurrent mounts from multiple Availability Zones using the NFSv4 protocol.
EFS provides the standard POSIX-compliant shared file system interface required by the application.
3
Determine the optimal throughput mode based on performance and cost
Configure EFS with Elastic throughput mode to dynamically handle traffic spikes up to 3 GB/s3\text{ GB/s} without manual intervention, while minimizing costs during idle periods.
Elastic throughput scales performance resources automatically based on the workload demands, which is perfect for highly unpredictable transaction spikes, avoiding the high costs of Provisioned throughput.

Anahtar Kavram

Amazon EFS with Elastic Throughput provides a highly available, shared file system that dynamically scales performance to meet unpredictable spike demands for containerized workloads.
Soru 748Soru

A financial services company operates a risk analysis application on AWS. The application architecture consists of three main tiers:

* Web/API Tier: Containerized APIs running on Amazon ECS with AWS Fargate. The APIs run 24/7 with a steady-state baseline of 10 vCPU10\text{ vCPU} and 20 GB20\text{ GB} RAM, but dynamically scale up to 50 vCPU50\text{ vCPU} and 100 GB100\text{ GB} RAM during peak business hours.
* Batch Processing Tier: A nightly data reconciliation job running on Amazon EC2. The job runs for 33 hours daily, is highly fault-tolerant, and can easily resume from checkpoints if interrupted.
* Database Tier: A steady-state Amazon RDS for PostgreSQL instance running 24/7.

The company wants to optimize its AWS compute and database costs over a 11-year period. Which combination of purchasing options will provide the most cost-effective solution while meeting the application's operational requirements?

Cevabı ve açıklamayı göster

Cevap: Purchase a 11-year Compute Savings Plan to cover the baseline Fargate tasks, use Fargate On-Demand for the peak scaling container tasks, run the reconciliation job on EC2 Spot Instances, and purchase a 11-year RDS Reserved Instance.

Cevap

Purchase a 11-year Compute Savings Plan to cover the baseline Fargate tasks, use Fargate On-Demand for the peak scaling container tasks, run the reconciliation job on EC2 Spot Instances, and purchase a 11-year RDS Reserved Instance.
The correct option correctly combines a 11-year Compute Savings Plan to cover the Fargate baseline, Fargate On-Demand for the user-facing API scaling tasks to ensure availability, EC2 Spot Instances for the fault-tolerant nightly batch job to achieve up to 90% cost savings, and a 11-year RDS Reserved Instance for the steady-state database.

Adım Adım Çözüm

1
Analyze the workload requirements of each tier to determine the baseline versus variable demands.
The Web/API tier has a steady 24/7 baseline (10 vCPU10\text{ vCPU}/20 GB20\text{ GB} RAM) and variable scaling (50 vCPU50\text{ vCPU}/100 GB100\text{ GB} RAM). The database is steady-state 24/7. The batch job is temporary (33 hours) but fault-tolerant.
Correctly categorizing workloads is necessary to match them with the right pricing model.
2
Select the appropriate savings vehicle for steady-state workloads.
Choose a Compute Savings Plan for the ECS Fargate baseline, and an RDS Reserved Instance (RI) for the steady-state PostgreSQL database.
Compute Savings Plans offer up to 66% savings on EC2, Fargate, and Lambda. RDS RIs offer up to 69% savings on steady-state databases, whereas Compute Savings Plans do not cover RDS.
3
Determine the purchasing model for the temporary and fault-tolerant batch reconciliation job.
Select EC2 Spot Instances for the 33-hour nightly batch job.
Spot Instances offer up to 90% savings over On-Demand and are ideal for workloads that can tolerate interruption, such as checkpoints-enabled batch processing.
4
Select the purchasing model for the scaling portion of the Web/API tier.
Use Fargate On-Demand for the peak scaling tasks.
Since the Web/API tier is user-facing, using Fargate Spot for scaling could result in container termination and degrade user experience. Fargate On-Demand ensures high availability for the spiky web traffic.

Anahtar Kavram

Selecting cost-optimized compute purchasing strategies requires matching the availability, execution duration, and service type of each workload component with the correct AWS savings model (Compute Savings Plans vs. Instance Savings Plans vs. Reserved Instances vs. Spot Instances).
Soru 749Soru

A healthcare provider manages an application that uploads files to an Amazon S3 bucket. The data consists of three types of files:

- Clinical images: Average size of 1212 MB. These files are accessed frequently during the first 3030 days, after which they are rarely accessed but must be available for millisecond-level retrieval by physicians for up to 180180 days before deletion.
- Patient telemetry logs: Average size of 250250 KB. These files are accessed frequently during the first 1010 days and can be permanently deleted after 2525 days.
- Daily check-in metadata: Average size of 88 KB. These files are accessed frequently for the first 3030 days, and then accessed occasionally for another 120120 days before deletion.

Which S3 lifecycle configuration represents the most cost-effective storage strategy for these files?

Cevabı ve açıklamayı göster

Cevap: Transition the clinical images to S3 Standard-IA after 30 days, and delete them after 180 days. Keep the patient telemetry logs and daily check-in metadata in S3 Standard for their entire lifecycles, deleting them after 25 days and 150 days respectively.

Cevap

Transition the clinical images to S3 Standard-IA after 30 days, and delete them after 180 days. Keep the patient telemetry logs and daily check-in metadata in S3 Standard for their entire lifecycles, deleting them after 25 days and 150 days respectively.
The correct option transitions the clinical images (which are large and stored for a long duration) to S3 Standard-IA, while keeping the small daily check-in metadata and short-lived patient telemetry logs in S3 Standard. This avoids both the 128 KB minimum billable object size overhead and the 30-day minimum storage duration penalty of S3 Standard-IA, achieving the lowest overall cost.

Adım Adım Çözüm

1
Analyze the access and retention requirements of the clinical images.
The files are large (12 MB) and require millisecond-level retrievals for 150 days (days 30 to 180).
Transitioning to S3 Standard-IA after 30 days is cost-effective because the file size is above 128 KB, the duration is longer than 30 days, and S3 Standard-IA supports millisecond-level retrieval.
2
Evaluate the patient telemetry logs access and retention pattern.
The files are 250 KB and are deleted after 25 days.
If transitioned to S3 Standard-IA at day 10, they would only stay there for 15 days (day 10 to day 25). This is less than the 30-day minimum storage duration of S3 Standard-IA, incurring a prorated storage charge penalty. Thus, they must remain in S3 Standard.
3
Evaluate the daily check-in metadata access and retention pattern.
The files are small (8 KB) and are deleted after 150 days.
If transitioned to S3 Standard-IA, they would be billed for 128 KB per object due to the minimum billable object size constraint. This increases the billable size by 16 times, offsetting any per-GB storage savings. Thus, they must remain in S3 Standard.

Anahtar Kavram

Cost-optimized storage tiering constraints including minimum billing size limits and minimum storage duration penalties in S3 Standard-IA.
Soru 750Soru

A company is planning to deploy a new web application that consists of a 24/7 continuous backend API and a separate daily batch data processing job that is fault-tolerant and can be run at any time. The solutions architect needs to design a cost-optimized compute strategy for these workloads. Which combination of compute selection and purchasing strategies will meet these requirements at the lowest cost? (Select TWO.)

Geçerli olan tümünü seçin

Cevabı ve açıklamayı göster

Cevap: Commit to a Compute Savings Plan to cover the continuous 24/7 backend API baseline.; Utilize Amazon EC2 Spot Instances to run the daily batch data processing jobs.

Cevap

Commit to a Compute Savings Plan to cover the continuous 24/7 backend API baseline, and utilize Amazon EC2 Spot Instances to run the daily batch data processing jobs.
The correct strategy combines a Compute Savings Plan to cover the continuous, predictable 24/7 backend API baseline with EC2 Spot Instances for the daily, fault-tolerant batch processing. This leverages the high discount of Spot Instances (up to 90%) for flexible workloads while securing a baseline discount (up to 66%) for the steady-state API component.

Adım Adım Çözüm

1
Analyze the workload requirements of the two components to determine their execution patterns.
The backend API runs continuously (24/7) representing a steady-state workload, while the batch job is fault-tolerant, daily, and flexible on when it runs.
Identifying the workload characteristics allows matching them to the most cost-effective AWS compute purchasing model.
2
Select the optimal purchasing model for the steady-state API workload.
A Compute Savings Plan is chosen for the continuous backend API, offering up to 66% discounts for a 1-year or 3-year commitment.
Steady-state, predictable workloads are best optimized using Savings Plans or Reserved Instances to lower baseline costs.
3
Select the optimal purchasing model for the fault-tolerant batch processing workload.
Amazon EC2 Spot Instances are chosen for the daily batch jobs, offering up to 90% savings compared to On-Demand rates.
Workloads that are fault-tolerant, flexible, and interruptible can safely leverage the steep discounts of Spot Instances.

Anahtar Kavram

Selecting the most cost-effective compute purchasing models (Savings Plans vs Spot Instances) based on workload predictability and fault tolerance.
Tahmini Süre:1m 0s
Soru 751Soru

A medical diagnostics company has deployed a global imaging application on AWS. The application stores high-resolution digital scans in an Amazon S3 bucket. Medical personnel globally access these scans frequently within 48 hours of creation, after which access drops significantly. The scans must be delivered with the lowest possible latency and maximum security. The company must ensure that only authorized clinicians can access the scans, and wants to minimize requests to the S3 origin.

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

Geçerli olan tümünü seçin

Cevabı ve açıklamayı göster

Cevap: Configure an Amazon CloudFront distribution with the S3 bucket as the origin, and restrict bucket access using Origin Access Control (OAC).; Use CloudFront signed URLs or signed cookies to authorize client access to the scans, and configure a custom cache policy with a default TTL of 172,800 seconds.

Cevap

Configure an Amazon CloudFront distribution with the S3 bucket as the origin, restrict bucket access using Origin Access Control (OAC), and use CloudFront signed URLs or signed cookies to authorize client access to the scans while configuring a custom cache policy with a default TTL of 172,800 seconds.
The correct solution involves configuring an Amazon CloudFront distribution with Origin Access Control (OAC) to restrict access to the underlying S3 bucket, ensuring users cannot bypass the CDN. Access authorization is handled at the edge using CloudFront signed URLs or signed cookies, while a default TTL of 172,800 seconds (48 hours) keeps the files cached during their high-access window, reducing latency and S3 origin requests.

Adım Adım Çözüm

1
Analyze access patterns and caching requirements.
Scans are static assets that are highly requested for 48 hours, meaning we should cache them at the edge with a default TTL of 48 hours (172,800 seconds) to minimize S3 origin requests.
Correctly identifying the high-frequency access window allows for configuration of the optimal TTL to maximize cache efficiency.
2
Determine origin security and client authorization mechanism.
Use Origin Access Control (OAC) to secure the S3 origin, and employ CloudFront signed URLs or signed cookies to restrict file access to authorized clinicians.
OAC prevents direct access to the S3 bucket, while signed URLs or cookies allow authorized access control at the edge before content is served.
3
Evaluate and discard inefficient storage and network paths.
Avoid S3 Standard-IA transitions immediately after upload due to high retrieval fees, and avoid NAT Gateways for S3 retrieval to prevent high data processing charges.
This step ensures that the architecture is cost-efficient and does not introduce unnecessary performance bottlenecks or cost penalties.

Anahtar Kavram

Multi-tier secure caching for high-performance content delivery using CloudFront, S3, OAC, and Signed URLs/Cookies.
Soru 752Soru

A digital marketing agency serves promotional HTML newsletters and CSS stylesheets to subscribers globally. The files are hosted in an Amazon S3 bucket behind an Amazon CloudFront distribution. A solutions architect reviews the CloudFront reports and finds that the cache hit ratio is 0%, leading to high latency for users and unexpected S3 data transfer charges. Which configuration issue is the primary cause of this behavior?

Cevabı ve açıklamayı göster

Cevap: The cache behavior for the newsletter and stylesheet files has its Minimum TTL, Default TTL, and Maximum TTL set to 0 seconds.

Cevap

The cache behavior for the newsletter and stylesheet files has its Minimum TTL, Default TTL, and Maximum TTL set to 0 seconds.
The correct answer is configuring the Minimum TTL, Default TTL, and Maximum TTL to 0 seconds. When these parameters are set to 0, CloudFront does not store the files in its edge caches and instead forwards all requests directly to the Amazon S3 origin, resulting in a cache hit ratio of 0% and elevated latency.

Adım Adım Çözüm

1
Analyze the symptom of a 0% cache hit ratio and high data transfer/request charges on the Amazon S3 origin.
The symptom indicates that CloudFront is not caching the content at edge locations, prompting it to request the files from S3 on every user request.
Understanding why the CDN cache is bypassed is key to resolving the performance and cost issues.
2
Evaluate the TTL settings of the CloudFront cache behavior configured for the files.
If the Minimum, Default, and Maximum TTL are set to 0 seconds, CloudFront treats the content as expired immediately and fetches a fresh copy from the origin for every incoming request.
TTL settings directly control how long objects remain cached in CloudFront before a revalidation or fetch from the origin is required.

Anahtar Kavram

CloudFront TTL Configuration
Soru 753Soru

An online education company stores popular static media assets, such as course images and stylesheets, in an Amazon S3 bucket. During peak enrollment periods, the S3 bucket experiences performance degradation due to high request volumes from global users. The company wants to reduce latency for users, protect the S3 bucket from overloading, and minimize operational complexity. Which configuration should the solutions architect choose?

Cevabı ve açıklamayı göster

Cevap: Configure an Amazon CloudFront distribution with the Amazon S3 bucket as the origin, caching the static assets at edge locations with default Time to Live (TTL) settings.

Cevap

Configure an Amazon CloudFront distribution with the Amazon S3 bucket as the origin, caching the static assets at edge locations with default Time to Live (TTL) settings.
Configuring Amazon CloudFront with the S3 bucket as the origin allows CloudFront to cache static assets (like images and stylesheets) at global edge locations. This reduces latency for users worldwide by serving content from the nearest edge location and protects the origin S3 bucket from high request volumes by serving cached copies, thereby increasing resiliency and reliability.

Adım Adım Çözüm

1
Identify the primary requirements: reduce latency for global users accessing static S3 assets and protect the origin bucket from request overload.
A caching mechanism at edge locations is needed to serve content closer to users and offload traffic from the S3 bucket.
Serving cached static content at edge locations reduces network round-trip time and prevents origin degradation.
2
Evaluate the capabilities of Amazon CloudFront.
Amazon CloudFront is a content delivery network that caches files at edge locations when non-zero TTL settings are active.
CloudFront acts as an edge caching layer that directly solves latency issues and shields the origin S3 bucket from high request volumes.
3
Compare CloudFront options against Route 53 and AWS Shield alternatives.
CloudFront with default TTL settings meets the requirement, whereas setting TTL to zero disables caching. Route 53 latency routing and AWS Shield do not cache content.
This step eliminates incorrect architectures that fail to provide edge caching.

Anahtar Kavram

Edge caching with Amazon CloudFront
Soru 754Soru

A media production studio is deploying a collaborative video rendering pipeline on AWS using a fleet of 150150 Amazon EC2 instances. The rendering nodes require concurrent read/write access to a shared file system. The storage solution must deliver sub-millisecond latencies, scale up to 12 GiB/s12\text{ GiB/s} of aggregate throughput, and support millions of IOPS. The studio's source assets are currently stored in an Amazon S3 bucket, and all rendered outputs must be automatically exported back to the same S3 bucket. Which combination of actions should a solutions architect take to meet these requirements? (Select TWO.)

Geçerli olan tümünü seçin

Cevabı ve açıklamayı göster

Cevap: Provision an Amazon FSx for Lustre file system using SSD storage, and configure it with a Persistent-2 deployment type.; Configure a Data Repository Association (DRA) between the Amazon FSx for Lustre file system and the Amazon S3 bucket.

Cevap

Provision an Amazon FSx for Lustre file system using SSD storage with a Persistent-2 deployment type, and configure a Data Repository Association (DRA) between the FSx for Lustre file system and the Amazon S3 bucket.
To meet the demands of a collaborative media rendering fleet of 150150 EC2 instances, a parallel file system like Amazon FSx for Lustre is required. Configuring it with SSD storage and a Persistent-2 deployment type delivers sub-millisecond latencies, millions of IOPS, and allows scaling aggregate throughput to 12 GiB/s12\text{ GiB/s} or more. Creating a Data Repository Association (DRA) between the FSx for Lustre file system and the S3 bucket automates the lifecycle of importing assets and exporting rendered files back to S3 asynchronously.

Adım Adım Çözüm

1
Analyze workload requirements and scale constraints.
The requirements include a shared parallel file system supporting 150 instances, sub-millisecond latency, 12 GiB/s12\text{ GiB/s} throughput, millions of IOPS, and bidirectional S3 synchronization.
Determines the threshold limits for storage volume, file system type, and interface capabilities.
2
Evaluate candidate shared storage architectures.
EBS Multi-Attach is ruled out due to its 16-instance limit. EFS is ruled out because its Elastic throughput limit (10 GiB/s10\text{ GiB/s} read, 3 GiB/s3\text{ GiB/s} write) falls short of the 12 GiB/s12\text{ GiB/s} target. FSx for Lustre SSD satisfies the performance and scale parameters.
Isolates the storage engine that matches high-performance computing and media rendering profiles.
3
Select data synchronization mechanisms.
FSx for Lustre's Data Repository Association (DRA) natively links to S3 for automated, low-overhead file ingestion and export, whereas FSx for OpenZFS or EFS would require complex, manual tooling.
Identifies the mechanism that fulfills the S3 integration requirement with the lowest operational overhead.

Anahtar Kavram

High-Performance Shared Parallel Storage with Amazon FSx for Lustre and S3 Integration
Tahmini Süre:2m 30s
Soru 755Soru

A financial company stores monthly transaction reports in an Amazon S3 Standard bucket. The reports have an average size of 15 MB15\text{ MB} each. These reports are accessed frequently by the auditing team for the first 3030 days after generation. After 3030 days, the reports are rarely accessed but must be kept for an additional 6060 days to meet compliance requirements. During this compliance period, the reports must be available for immediate retrieval in the event of an audit. After a total of 9090 days, the reports must be permanently deleted.

Which combination of Amazon S3 Lifecycle actions should a solutions architect implement to meet these requirements in the most cost-effective manner? (Select TWO.)

Geçerli olan tümünü seçin

Cevabı ve açıklamayı göster

Cevap: Transition the reports to Amazon S3 Standard-Infrequent Access (S3 Standard-IA) after 3030 days; Configure a lifecycle rule to permanently delete the reports after 9090 days

Cevap

Transition the reports to Amazon S3 Standard-Infrequent Access (S3 Standard-IA) after 3030 days and configure a lifecycle rule to permanently delete the reports after 9090 days.
The correct lifecycle strategy is to transition the reports to Amazon S3 Standard-Infrequent Access (S3 Standard-IA) after 3030 days, and configure a rule to permanently delete them after 9090 days. This ensures that the reports remain in S3 Standard-IA for 6060 days, which satisfies the 3030-day minimum storage duration charge for S3 Standard-IA. S3 Standard-IA also meets the requirement of immediate (millisecond) retrieval for audits. Finally, deleting the reports at 9090 days complies with the data retention policy and stops further storage charges.

Adım Adım Çözüm

1
Analyze the access pattern and lifecycle stages of the reports.
The reports require high-availability storage with frequent access for the first 3030 days, followed by 6060 days of rare access with immediate retrieval capability (days 3030 to 9090), and permanent deletion at day 9090.
This establishes the timeline and constraints for configuring the S3 Lifecycle policy.
2
Select the appropriate storage tier for the rare access phase.
S3 Standard-IA is selected over S3 Standard for the compliance phase because it offers lower storage costs and meets the requirement for immediate (millisecond) retrieval. S3 Glacier options are ruled out due to retrieval delays or duration charges.
Transitioning at day 3030 ensures the reports spend 6060 days in S3 Standard-IA, which comfortably exceeds the 3030-day minimum storage duration billing requirement of S3 Standard-IA.
3
Select the end-of-life action.
Configure a lifecycle expiration rule to permanently delete the objects after 9090 days.
This terminates storage billing once the 9090-day retention period ends, satisfying the compliance requirement.

Anahtar Kavram

Amazon S3 Lifecycle rules can automate transitioning and deleting objects to optimize costs. When transitioning to tiers like S3 Standard-IA or S3 Glacier, solutions architects must respect minimum storage duration requirements (e.g., 3030 days for S3 Standard-IA, 9090 days for Glacier) to avoid unexpected billing penalties.
Soru 756Soru

A company hosts a financial reporting application on AWS. The application uses Amazon EC2 instances behind an Application Load Balancer (ALB) to query an Amazon RDS for PostgreSQL database. Users run complex, repetitive SQL queries that retrieve historical transaction records. During month-end reporting cycles, the database CPU utilization reaches 100%100\%, leading to query timeouts and slow response times. The database records are updated only once per day. Which architectural solution should a solutions architect implement to resolve the database bottleneck with the lowest latency?

Cevabı ve açıklamayı göster

Cevap: Deploy an Amazon ElastiCache for Redis cluster. Configure the application to implement a cache-aside pattern to check the cache before querying the database, and write query results to the cache.

Cevap

Deploy an Amazon ElastiCache for Redis cluster, and configure the application to check the cache before querying the database, writing query results to the cache (cache-aside pattern).
The correct answer provides an in-memory caching layer (Amazon ElastiCache for Redis) directly in front of the RDS database. Implementing the cache-aside pattern ensures that repetitive, resource-intensive queries are served from memory with sub-millisecond latency. This completely offloads the database from processing redundant queries, resolving the 100%100\% CPU utilization bottleneck.

Adım Adım Çözüm

1
Analyze the workload characteristics and bottlenecks.
The workload consists of complex, repetitive SQL queries on data that is only updated once per day, causing 100%100\% CPU utilization on the RDS PostgreSQL database.
Since the queries are identical and run repeatedly, caching the results will prevent the database from executing the same complex SQL queries repeatedly.
2
Select the appropriate caching technology.
Amazon ElastiCache for Redis is selected to cache PostgreSQL database query results at the application layer.
ElastiCache provides sub-millisecond in-memory storage suitable for relational database query results, unlike CloudFront which caches HTTP traffic at edge locations.
3
Implement the caching pattern in the application logic.
Configure the cache-aside (lazy loading) pattern: application checks ElastiCache first; on a cache miss, it queries RDS PostgreSQL, populates the cache with a daily TTL, and returns the result.
This guarantees that subsequent repeated queries within the day bypass the database completely, resolving the CPU bottleneck.

Anahtar Kavram

Database query caching using ElastiCache to offload complex relational query execution from Amazon RDS.
Soru 757Soru

A genomic research laboratory runs sequencing pipelines on Amazon EC2 instances in a private subnet. The pipelines generate raw sequence files of approximately 150 MB150\text{ MB} each, which are stored in an Amazon S3 bucket. The data is accessed frequently and must be available immediately for the first 15 days15\text{ days}. After 15 days15\text{ days}, the files are rarely accessed but must be retained for at least 120 days120\text{ days} to meet regulatory compliance requirements. Audits can tolerate a retrieval time of up to 5 hours5\text{ hours}.

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

Geçerli olan tümünü seçin

Cevabı ve açıklamayı göster

Cevap: Create an S3 Lifecycle rule to transition the objects to Amazon S3 Glacier Flexible Retrieval 15 days15\text{ days} after creation.; Create an S3 Lifecycle rule to expire the objects 120 days120\text{ days} after creation.

Cevap

To meet the requirements cost-effectively, the solutions architect should use S3 Lifecycle rules to transition the objects to Amazon S3 Glacier Flexible Retrieval 15 days15\text{ days} after creation, and expire the objects 120 days120\text{ days} after creation.
Transitioning files to Amazon S3 Glacier Flexible Retrieval after 15 days15\text{ days} is the most cost-effective tier because it meets the requirement of keeping files available immediately for the first 15 days15\text{ days} and allows standard retrievals within 3 to 5 hours3\text{ to }5\text{ hours}, well within the 5-hour5\text{-hour} audit limit. Expiring the objects after 120 days120\text{ days} ensures that they are deleted once the compliance retention period is reached, stopping all storage charges.

Adım Adım Çözüm

1
Identify the storage requirements for the active data phase.
Data must be stored in a tier that provides immediate and frequent access for the first 15 days15\text{ days}.
Since the genomic sequencing files must be accessed frequently and immediately during the initial phase, they should remain in Amazon S3 Standard for the first 15 days15\text{ days} before transition.
2
Evaluate the optimal archive tier for the inactive phase based on cost and access requirements.
Amazon S3 Glacier Flexible Retrieval is chosen instead of S3 Standard-IA or S3 Glacier Deep Archive.
The files are rarely accessed after 15 days15\text{ days} and can tolerate a retrieval time of up to 5 hours5\text{ hours}. S3 Glacier Flexible Retrieval (standard retrieval of 3 to 5 hours3\text{ to }5\text{ hours}) meets this recovery window at a much lower cost than S3 Standard-IA, while S3 Glacier Deep Archive (up to 12 hours12\text{ hours}) is too slow.
3
Define the expiration rule for regulatory compliance.
The files are set to expire 120 days120\text{ days} after creation.
The regulatory compliance rules require retaining files for at least 120 days120\text{ days}, after which they are no longer needed, so an expiration rule stops ongoing storage costs.

Anahtar Kavram

Selecting the most cost-effective S3 storage tier based on access patterns, retrieval times, minimum storage durations, and expiration requirements.
Tahmini Süre:2m 0s
Soru 758Soru

A software-as-a-service (SaaS) company is building a real-time collaborative whiteboarding application. The application requires a database to store user session states across two AWS Regions: uswest2us-west-2 and eucentral1eu-central-1. The architecture must support active-active writes in both Regions to ensure sub-millisecond write latencies for local users. The database must automatically replicate data bi-directionally with a Recovery Point Objective (RPO) of less than 11 second and a recovery time objective (RTO) of near zero during a regional outage. Which combination of configurations must a solutions architect implement to achieve this resilient database architecture? (Select TWO.)

Geçerli olan tümünü seçin

Cevabı ve açıklamayı göster

Cevap: Create a primary Amazon DynamoDB table in one Region and enable DynamoDB Streams with the "New and Old Images" setting.; Add a replica table in the secondary AWS Region to convert the existing table into a DynamoDB global table.

Cevap

The correct configurations are enabling DynamoDB Streams with New and Old Images on the primary table and adding a replica table in the secondary Region.
To achieve an active-active, multi-region architecture with sub-second bi-directional replication and sub-millisecond write latencies, Amazon DynamoDB global tables should be used. The solutions architect must first enable DynamoDB Streams with New and Old Images on the primary table, then add the replica table in the secondary Region.

Adım Adım Çözüm

1
Analyze the requirements for active-active multi-region write access, sub-millisecond latency, and low RTO/RPO.
Identify that a multi-region active-active database engine is required, which rules out Amazon RDS and standard Amazon Aurora configurations since they use active-passive write architectures.
This narrows down the database solution to Amazon DynamoDB global tables, which natively support active-active configurations across multiple Regions.
2
Identify the prerequisite configurations to deploy Amazon DynamoDB global tables.
DynamoDB Streams with the New and Old Images setting must be enabled on the primary table before replica tables can be added.
DynamoDB uses the stream to track and replicate data changes across Regions to maintain consistency.
3
Select the configuration step that completes the creation of the global table.
Add a replica table in the secondary Region (eu-central-1).
This establishes bi-directional replication between the two Regions, allowing local reads and writes.

Anahtar Kavram

Amazon DynamoDB global tables provide a fully managed, multi-region, active-active database solution that replicates data with low latency, meeting high availability and resilient disaster recovery requirements.
Soru 759Soru

A company hosts a legacy inventory management application on AWS. The architecture consists of a steady-state fleet of Amazon EC2 instances running 24/724/7 and an Amazon RDS for PostgreSQL database instance that also runs continuously. The company wants to minimize costs for both the EC2 instances and the RDS database with a 11-year commitment. Which combination of purchasing options will provide the most cost-effective solution?

Cevabı ve açıklamayı göster

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

Cevap

Purchase a Compute Savings Plan for the Amazon EC2 instances, and purchase Amazon RDS Reserved Instances for the database instance.
Purchasing a Compute Savings Plan for the Amazon EC2 instances provides a flexible discount on the compute workload, and purchasing Amazon RDS Reserved Instances provides a dedicated discount for the RDS database instance. Compute Savings Plans apply automatically to EC2, Fargate, and Lambda, while RDS Reserved Instances are required to reduce the cost of the RDS database instance.

Adım Adım Çözüm

1
Identify the distinct AWS resources in the architecture.
The workload consists of Amazon EC2 instances and an Amazon RDS database instance.
Different AWS services have separate pricing structures and cost optimization models.
2
Determine the optimal purchasing strategy for the Amazon EC2 instances.
Because the EC2 instances run steady-state 24/724/7, a Savings Plan (Compute or EC2 Instance) is suitable to reduce costs.
Savings Plans offer significant discounts over On-Demand rates in exchange for a commitment.
3
Determine the optimal purchasing strategy for the Amazon RDS database instance.
Amazon RDS cannot be covered by Compute Savings Plans and requires RDS Reserved Instances.
Savings Plans are scoped to compute services (EC2, Fargate, Lambda) and do not apply to RDS.

Anahtar Kavram

Compute Savings Plans apply to EC2, Fargate, and Lambda, whereas Amazon RDS requires RDS Reserved Instances for cost optimization.
Soru 760Soru

A global logistics company has deployed a fleet-tracking application that ingests real-time telemetry data from vehicle sensors using a proprietary TCP-based protocol. The backend application is hosted on Amazon EC2 instances in an Auto Scaling group behind an Application Load Balancer (ALB) in a primary AWS Region. The company requires a highly resilient architecture that minimizes latency for global clients, prevents packet loss over the public internet, and automatically fails over to a secondary Region in the event of an outage. Which architecture should a solutions architect recommend to meet these requirements?

Cevabı ve açıklamayı göster

Cevap: Create an AWS Global Accelerator accelerator, and associate the ALBs in both the primary and secondary Regions as endpoints. Configure the vehicle sensors to send telemetry data to the static IP addresses provided by the accelerator.

Cevap

Create an AWS Global Accelerator accelerator, associate the Application Load Balancers in both Regions as endpoints, and configure the vehicle sensors to send telemetry data to the accelerator's static IP addresses.
AWS Global Accelerator is the correct solution because it supports TCP and UDP protocols, routes traffic over the congestion-free AWS global network to minimize latency and packet loss, and provides automatic regional failover via health checks. Additionally, it offers static Anycast IP addresses, eliminating issues associated with DNS caching.

Adım Adım Çözüm

1
Analyze the application protocol and requirements.
Identify that the application uses a proprietary TCP-based protocol (non-HTTP/HTTPS) and requires low latency, prevention of packet loss, and multi-region failover.
This determines which edge service is capable of routing the traffic, as Amazon CloudFront and AWS WAF only support HTTP/HTTPS, whereas AWS Global Accelerator supports TCP/UDP.
2
Evaluate AWS Global Accelerator as a routing solution.
AWS Global Accelerator provides two static Anycast IP addresses that route traffic over the AWS global private network to the nearest regional endpoint.
Routing traffic over the AWS global backbone reduces network hops, minimizes latency, prevents packet loss over the public internet, and avoids DNS caching issues during failover.
3
Configure endpoint groups and health checks.
Associate the Application Load Balancers (ALBs) from both the primary and secondary Regions as endpoints within the accelerator.
Global Accelerator monitors endpoint health and automatically routes client traffic to the secondary Region in the event of an outage in the primary Region.

Anahtar Kavram

AWS Global Accelerator vs. Amazon CloudFront for non-HTTP protocols and multi-region resiliency.
Tahmini Süre:2m 30s
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Tüm alıştırma soruları — AWS Certified Solutions Architect - Associate | Examkin