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A startup needs to monitor its AWS costs to prevent unexpected spending. The startup wants to receive proactive email notifications when its monthly costs are forecasted to exceed a specific threshold. Additionally, the startup wants to view daily automated reports of their cost and usage breakdown sent to their inbox.

Which two options should the startup configure to meet these requirements? (Select TWO.)

Select all that apply

Create a cost budget in AWS Budgets with a threshold based on forecasted monthly costs.

Configure a daily scheduled report in AWS Cost Explorer.

Set up a Cost Explorer saved view with email alerts enabled for forecasted costs.

Use AWS Billing Conductor to set up a forecasted cost threshold notification.

Create a monthly budget in AWS Trusted Advisor to track and alert on forecasted costs.

Show answer & explanation

Answer: Create a cost budget in AWS Budgets with a threshold based on forecasted monthly costs.; Configure a daily scheduled report in AWS Cost Explorer.

Answer

Create a cost budget in AWS Budgets with a threshold based on forecasted monthly costs, and configure a daily scheduled report in AWS Cost Explorer.

The correct combination includes configuring a cost budget in AWS Budgets and scheduling a report in AWS Cost Explorer. AWS Budgets is the designated tool for defining cost thresholds and receiving proactive notifications when costs are forecasted to exceed those limits. AWS Cost Explorer is the correct tool for analyzing cost details and scheduling reports to be sent automatically on a daily basis.

Step-by-Step Solution

Identify the requirement for proactive alerts on forecasted monthly spending exceeding a threshold.

Determine that AWS Budgets is the correct service for setting custom budgets and receiving proactive alerts based on forecasted costs.

AWS Budgets natively supports threshold-based alerts for actual and forecasted spending.

Identify the requirement for receiving daily automated reports summarizing cost and usage breakdown.

Determine that AWS Cost Explorer can save custom reports and schedule them to be sent daily via email.

AWS Cost Explorer provides the daily scheduled reporting functionality for detailed visual breakdowns.

Key Concept

AWS Cost Monitoring, Budgeting, and Optimization Tool Analysis

Question 902Question →

An online education platform generates user session interaction logs that are stored in an Amazon S3 bucket. Each log file is approximately $200\text{ KB}$ in size. The logs are accessed frequently for analysis during the first $12$ days after creation. After $12$ days, access drops significantly, but the logs must be retained for troubleshooting purposes for a total of $25$ days from creation, after which they can be safely deleted. Which lifecycle configuration is the most cost-effective solution for managing these logs?

Keep the logs in Amazon S3 Standard, and configure a lifecycle rule to permanently delete the logs after 25 days.

Configure a lifecycle rule to transition the logs to Amazon S3 Standard-Infrequent Access (S3 Standard-IA) after 12 days and permanently delete them after 25 days.

Configure a lifecycle rule to transition the logs to Amazon S3 One Zone-Infrequent Access (S3 One Zone-IA) after 12 days and permanently delete them after 25 days.

Configure a lifecycle rule to transition the logs to Amazon S3 Glacier Instant Retrieval after 12 days and permanently delete them after 25 days.

Show answer & explanation

Answer: Keep the logs in Amazon S3 Standard, and configure a lifecycle rule to permanently delete the logs after 25 days.

Answer

Keep the logs in Amazon S3 Standard and delete them after 25 days using a lifecycle rule.

The correct answer is correct because keeping the logs in Amazon S3 Standard for the entire 25 days is the most cost-effective choice. Transitioning to any Infrequent Access or Glacier tier incurs a minimum storage duration fee (30 days for S3 Standard-IA/S3 One Zone-IA, and 90 days for S3 Glacier Instant Retrieval). Because the logs are deleted at day 25, they only spend 13 days in the target storage tier, which triggers early deletion charges. In addition, transitioning files introduces request costs that outweigh any potential storage savings.

Step-by-Step Solution

Calculate the time spent in the secondary storage tier if transitioned at day 12 and deleted at day 25.

The duration in the secondary tier is

25 - 12 = 13

days.

This determines whether the storage duration meets the minimum requirements of the target storage classes.

Evaluate the minimum storage duration requirements for S3 Standard-IA, S3 One Zone-IA, and S3 Glacier Instant Retrieval.

S3 Standard-IA and S3 One Zone-IA require a minimum of

30

days, while S3 Glacier Instant Retrieval requires

90

days.

If objects are deleted before the minimum duration, AWS bills for the remaining days of the minimum duration.

Compare the cost of keeping the objects in S3 Standard for 25 days against transitioning them at day 12.

Transitioning triggers an early deletion fee for the remaining days (e.g., 17 days for Standard-IA) plus transition request charges, which exceeds the cost of keeping the logs in S3 Standard for the entire 25 days.

This identifies the most cost-effective lifecycle configuration for the given lifecycle timeline.

Key Concept

S3 lifecycle transition constraints and minimum storage durations

Estimated Time:1m 30s

Question 903Question →

A solutions architect is designing a database tier for a new high-throughput social networking application. The application requires microsecond read latency to serve a small list of popular trending profiles. The write volume is expected to scale up to $15,000$ transactions per second, and the architect must ensure that these write operations are evenly distributed to prevent partition bottlenecks on the underlying Amazon DynamoDB table.

Which TWO options should the solutions architect select to meet these performance requirements?

Select all that apply

Deploy an Amazon DynamoDB Accelerator (DAX) cluster to cache read requests for popular profiles.

Choose a high-cardinality attribute, such as a unique UserID, as the partition key.

Choose a monotonically increasing attribute, such as a registration timestamp, as the partition key.

Configure Amazon RDS Read Replicas to act as the primary write target during peak workloads.

Show answer & explanation

Answer: Deploy an Amazon DynamoDB Accelerator (DAX) cluster to cache read requests for popular profiles.; Choose a high-cardinality attribute, such as a unique UserID, as the partition key.

Answer

Deploying an Amazon DynamoDB Accelerator (DAX) cluster to cache read requests for popular profiles, and choosing a high-cardinality attribute, such as a unique UserID, as the partition key.

The correct architecture requires deploying a DynamoDB Accelerator (DAX) cluster to provide in-memory microsecond read responses for the trending profiles. It also requires selecting a high-cardinality partition key, such as UserID, to distribute the write load of

15,000

transactions per second evenly across partitions and avoid write bottlenecks.

Step-by-Step Solution

Evaluate read latency requirements

The application requires microsecond latency for hot read requests, indicating the need for an in-memory cache rather than direct database queries.

DynamoDB Accelerator (DAX) provides microsecond latency for read operations on DynamoDB tables.

Evaluate write distribution requirements

To support

15,000

transactions per second without partition limits being exceeded, the database must distribute writes uniformly.

Choosing a high-cardinality partition key like UserID prevents hot partitions by spreading writes across multiple physical partitions.

Key Concept

High-performing DynamoDB architectures rely on in-memory caching (DAX) for sub-millisecond read access and high-cardinality partition keys to distribute read/write throughput uniformly across partitions.

Estimated Time:1m 30s

Question 904Question →

A digital marketing platform is launching a real-time bidding and analytics engine. The system must process ad request queries with sub-millisecond read latency for user profiles. Additionally, the system needs to persist bid transaction logs, which experience highly unpredictable, spiky write traffic. A solutions architect is designing a high-performing, scalable database architecture to support these requirements.

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

Select all that apply

Use Amazon DynamoDB with Amazon DynamoDB Accelerator (DAX) to store and serve user profile data.

Configure Amazon DynamoDB with On-Demand capacity mode to store bid transaction logs.

Use Amazon DynamoDB with a partition key based on monotonically increasing transaction timestamps to store bid transaction logs.

Deploy an Amazon RDS PostgreSQL database with a read replica in a different Availability Zone to handle transaction logging and act as the primary write destination during failover.

Configure Amazon DynamoDB with Provisioned Capacity Mode and set static Read and Write Capacity Units to handle the bid transaction logs.

Show answer & explanation

Answer: Use Amazon DynamoDB with Amazon DynamoDB Accelerator (DAX) to store and serve user profile data.; Configure Amazon DynamoDB with On-Demand capacity mode to store bid transaction logs.

Answer

Use Amazon DynamoDB with Amazon DynamoDB Accelerator (DAX) to store and serve user profile data, and configure Amazon DynamoDB with On-Demand capacity mode to store bid transaction logs.

The correct architecture uses DynamoDB Accelerator (DAX) to deliver the required sub-millisecond (microsecond-level) read latency for user profiles by serving reads from an in-memory cache. Simultaneously, configuring DynamoDB with On-Demand capacity mode ensures that the system handles highly unpredictable, spiky write traffic for bid transaction logs without manual capacity management or performance throttling.

Step-by-Step Solution

Analyze the read latency requirement for user profiles.

The requirement specifies sub-millisecond read latency under high throughput.

DynamoDB Accelerator (DAX) is an in-memory cache that reduces DynamoDB response times to microseconds, satisfying this requirement.

Analyze the write traffic requirement for transaction logs.

The requirement specifies highly unpredictable and spiky write traffic that must be persisted.

DynamoDB On-Demand capacity mode is ideal for spiky workloads as it dynamically scales to accommodate write peaks without throttling or manual scaling configuration.

Evaluate the partition key design for the transaction logs.

Using monotonically increasing values like timestamps creates hot partitions.

High-performing DynamoDB designs require high-cardinality partition keys to distribute data and throughput evenly across partitions.

Key Concept

High-performing database architectures leverage caching (like DAX) for microsecond read latency and dynamic scaling modes (like DynamoDB On-Demand) to handle spiky, unpredictable write traffic without performance bottlenecks.

Estimated Time:2m 0s

Question 905Question →

An enterprise manages a multi-account environment consolidated under AWS Organizations. The company wants to implement a cost-governance strategy to proactively manage spending. Specifically, they need to detect sudden, unexpected spikes in daily spending across any of the accounts and alert the operations team. Additionally, they must ensure that individual product teams do not exceed their allocated monthly limits by receiving warning notifications when the teams are forecasted to exceed their budget based on their specific cost allocation tags. Which combination of AWS cost management tools and configurations should a solutions architect implement to meet these requirements? (Select TWO.)

Select all that apply

Create an AWS Cost Anomaly Detection monitor with a daily alert subscription connected to an Amazon SNS topic to identify and alert on sudden, unexpected spending spikes.

Configure AWS Budgets with custom cost budgets filtered by specific cost allocation tags, setting alerts when forecasted costs exceed 100% of the budgeted amount.

Set up a daily saved report in AWS Cost Explorer filtered by cost allocation tags to automatically notify the team leads via email if daily costs exceed the threshold.

Use AWS Billing Conductor to define custom billing groups and configure automated alerts when a billing group's actual daily usage exceeds the predefined budget.

Create a billing alarm in Amazon CloudWatch that monitors the overall consolidated charges metric and triggers a Lambda function to parse billing reports and alert on tag-based anomalies.

Show answer & explanation

Answer: Create an AWS Cost Anomaly Detection monitor with a daily alert subscription connected to an Amazon SNS topic to identify and alert on sudden, unexpected spending spikes.; Configure AWS Budgets with custom cost budgets filtered by specific cost allocation tags, setting alerts when forecasted costs exceed 100% of the budgeted amount.

Answer

Create an AWS Cost Anomaly Detection monitor with a daily alert subscription connected to an Amazon SNS topic, and configure AWS Budgets with custom cost budgets filtered by specific cost allocation tags to alert when forecasted costs exceed 100% of the budgeted amount.

The solution requires a combination of proactive and real-time monitoring tools. AWS Cost Anomaly Detection is the optimal choice for detecting unexpected spikes in spending using machine learning, sending alerts via Amazon SNS daily or immediately. AWS Budgets is the correct tool for setting proactive spending limits based on cost allocation tags, allowing alerts to trigger when forecasted costs exceed the budget before actual charges occur.

Step-by-Step Solution

Address the requirement to detect sudden, unexpected spikes in daily spending.

Create an AWS Cost Anomaly Detection monitor with daily alert subscriptions to an Amazon SNS topic.

AWS Cost Anomaly Detection is designed specifically to detect sudden, unexpected spend spikes using machine learning.

Address the requirement to warn teams when forecasted spending exceeds their specific budget tags.

Create cost budgets in AWS Budgets, filter them using specific cost allocation tags, and set alerts based on forecasted amounts.

AWS Budgets can monitor costs based on resource tags and proactively alert when forecasted amounts cross the defined budget limits.

Eliminate delayed or retrospective reporting tools.

Reject alternatives using AWS Cost Explorer, AWS Billing Conductor, or CloudWatch billing alarms.

These services do not support machine-learning-based real-time anomaly detection or proactive forecasting alerts for specific tags without significant delays.

Key Concept

Implementing proactive cost governance by combining machine-learning-based anomaly alerting (AWS Cost Anomaly Detection) with proactive, tag-based forecast budgeting (AWS Budgets).

Question 906Question →

A financial services firm processes two types of data files stored in a single Amazon S3 bucket:

* Transaction logs: Average size of $15\text{ KB}$ . These files are accessed frequently for the first $30\text{ days}$ after creation, and then must be retained for $7\text{ years}$ for auditing. When needed for audits, they must be retrievable within minutes.
* Monthly statements: Average size of $5\text{ MB}$ . These files are accessed frequently for the first $30\text{ days}$ after creation, occasionally accessed for the next $60\text{ days}$ (requiring millisecond access times), and then must be retained for $7\text{ years}$ with an acceptable retrieval time of up to $5\text{ hours}$ .

Which combination of S3 Lifecycle configuration actions will meet these requirements in the most cost-effective manner? (Select TWO.)

Select all that apply

Configure a lifecycle policy for the transaction logs to retain them in Amazon S3 Standard for the entire

7\text{-year}

duration.

Configure a lifecycle policy for the monthly statements to transition them to Amazon S3 Standard-Infrequent Access (S3 Standard-IA) after

30\text{ days}

, and to Amazon S3 Glacier Flexible Retrieval after

90\text{ days}

Configure a lifecycle policy for the monthly statements to transition them to Amazon S3 Standard-IA after

30\text{ days}

, and then to Amazon S3 Glacier Flexible Retrieval after

45\text{ days}

Configure a lifecycle policy for the monthly statements to transition them to Amazon S3 Standard-IA after

30\text{ days}

, and then to Amazon S3 Glacier Deep Archive after

90\text{ days}

Configure a lifecycle policy for the transaction logs to transition them to Amazon S3 Standard-IA after

30\text{ days}

Show answer & explanation

Answer: Configure a lifecycle policy for the transaction logs to retain them in Amazon S3 Standard for the entire $7\text{-year}$ duration.; Configure a lifecycle policy for the monthly statements to transition them to Amazon S3 Standard-Infrequent Access (S3 Standard-IA) after $30\text{ days}$ , and to Amazon S3 Glacier Flexible Retrieval after $90\text{ days}$ .

Answer

The correct strategy is to retain the transaction logs in Amazon S3 Standard for the entire duration, and to transition the monthly statements to S3 Standard-IA after

30\text{ days}

and then to S3 Glacier Flexible Retrieval after

90\text{ days}

For the monthly statements, transitioning to S3 Standard-IA after

30\text{ days}

provides the required millisecond access. Waiting until day

90

to transition them to S3 Glacier Flexible Retrieval ensures the files remain in S3 Standard-IA for

60\text{ days}

, satisfying the

30\text{-day}

minimum duration and avoiding any early transition penalties. For the transaction logs, keeping them in S3 Standard for the entire period is most cost-effective. Transitioning these

15\text{ KB}

logs to S3 Standard-IA would force billing at the

128\text{ KB}

minimum size, and transitioning them to S3 Glacier Flexible Retrieval adds

40\text{ KB}

minimum size billing plus a combined

40\text{ KB}

of metadata overhead, making both transitions more expensive than keeping them in S3 Standard.

Step-by-Step Solution

Analyze file sizes and access patterns to identify constraints.

Transaction logs are very small (

15\text{ KB}

) and need rapid retrieval. Monthly statements are larger (

5\text{ MB}

) and require millisecond access for the first

90\text{ days}

, followed by retrieval within

5\text{ hours}

for

7\text{ years}

Correctly identifying object sizes and access patterns determines whether transition rules will trigger size-based cost penalties.

Evaluate the cost impact of S3 Standard-IA and Glacier metadata constraints on transaction logs.

Transitioning

15\text{ KB}

transaction logs to S3 Standard-IA triggers the

128\text{ KB}

minimum billing size constraint. Transitioning them to Glacier Flexible Retrieval incurs a

40\text{ KB}

minimum billing size along with

32\text{ KB}

Glacier metadata and

8\text{ KB}

Standard metadata charges per object. This combined overhead makes transition more expensive than keeping them in S3 Standard.

Avoiding storage class transitions for objects significantly smaller than the minimum billing threshold is a critical cost-optimization best practice.

Determine the optimal transition schedule for monthly statements.

Transitioning to S3 Standard-IA at day

30

and then to S3 Glacier Flexible Retrieval at day

90

keeps the statements in S3 Standard-IA for

60\text{ days}

(which exceeds the

30\text{-day}

minimum storage duration) and provides

3

5\text{ hour}

retrieval times (via standard retrieval) for long-term archiving.

This satisfies the access patterns while avoiding the early transition charge associated with the

30\text{-day}

minimum storage duration of S3 Standard-IA.

Key Concept

S3 storage class cost-efficiency is heavily influenced by minimum object storage sizes, minimum storage durations, and metadata overhead, particularly for small objects.

Estimated Time:2m 0s

Question 907Question →

A financial technology organization operates its production workloads across multiple AWS accounts within an organization in AWS Organizations. The cloud operations team wants to implement a cost-governance strategy to address two specific requirements:

First, they need to identify unusual spending patterns in raw data transfer costs as soon as they occur and receive notifications.

Second, they must ensure that a sandbox environment (tagged `Environment: Sandbox`) does not exceed its monthly budget, and automatically apply a restrictive Service Control Policy (SCP) to prevent further resource provisioning if the sandbox spending exceeds 120% of the budgeted amount.

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

Select all that apply

Configure AWS Cost Anomaly Detection with a Service monitor to identify anomalies in AWS service charges, and connect it to an Amazon SNS topic for immediate alert delivery.

Establish a tag-filtered cost budget in AWS Budgets targeting the `Environment: Sandbox` tag. Define a budget action that attaches a restrictive Service Control Policy (SCP) to the Sandbox Organizational Unit (OU) if actual costs reach 120% of the threshold.

Schedule a daily report delivery in AWS Cost Explorer to inspect data transfer costs, sending email notifications to the cloud operations team when costs exceed the previous day's baseline.

Purchase a Compute Savings Plan matching the sandbox's historical compute usage to automatically cap sandbox expenditures at 120% of the budgeted monthly limit.

Implement AWS Budgets for the sandbox environment, and configure an automated action utilizing the AWS account root user credentials to shut down all active EC2 instances when the cost threshold is breached.

Show answer & explanation

Answer: Configure AWS Cost Anomaly Detection with a Service monitor to identify anomalies in AWS service charges, and connect it to an Amazon SNS topic for immediate alert delivery.; Establish a tag-filtered cost budget in AWS Budgets targeting the `Environment: Sandbox` tag. Define a budget action that attaches a restrictive Service Control Policy (SCP) to the Sandbox Organizational Unit (OU) if actual costs reach 120% of the threshold.

Answer

The correct configuration consists of setting up AWS Cost Anomaly Detection with a Service monitor integrated with an Amazon SNS topic, and establishing a tag-filtered budget in AWS Budgets that triggers a Service Control Policy action at 120% of the budget threshold.

AWS Cost Anomaly Detection uses machine learning to identify unusual spending patterns in AWS services (such as data transfer) and can alert teams in near-real-time using Amazon SNS subscriptions. For strict budget enforcement, AWS Budgets allows you to monitor tag-filtered resource costs and configure automated budget actions. One supported budget action is applying a Service Control Policy (SCP) at the Organizational Unit (OU) level, which programmatically halts new resource provisioning when the actual spend threshold (120%) is crossed.

Step-by-Step Solution

Address the anomaly detection requirement by configuring AWS Cost Anomaly Detection with a Service monitor.

This monitors AWS services specifically (such as data transfer) and uses machine learning to identify unusual spending patterns.

Machine learning anomaly detection is proactive and runs automatically, satisfying the near-real-time warning requirement.

Configure an AWS Cost Anomaly Detection subscription targeting an Amazon SNS topic.

This sends alerts to the cloud operations team immediately upon detection of anomalous spend.

Integrating with SNS ensures automated and immediate alerting.

Address the monthly budget control requirement by creating a tag-filtered budget in AWS Budgets targeting the `Environment: Sandbox` tag.

This tracks expenditures specific to the sandbox environment.

AWS Budgets can monitor costs matching specific tags and supports automated administrative actions.

Define an AWS Budgets action configured to apply a restrictive Service Control Policy (SCP) to the Sandbox OU at 120% actual spend.

If actual costs reach 120% of the budget, the SCP is automatically applied, denying further resource creation.

AWS Budgets action can directly apply SCPs via AWS Organizations integration, meeting the control requirement.

Key Concept

Combining AWS Cost Anomaly Detection for proactive, machine-learning-based alerting with AWS Budgets Actions (SCPs) for tag-based budget enforcement.

Question 908Question →

A financial services firm is deploying a containerized risk-modeling application on Amazon ECS using the Amazon EC2 launch type. The ECS tasks run on the EC2 instances using the host network mode. The compute processes within the containers use the Message Passing Interface (MPI) to perform tightly-coupled parallel calculations across multiple container instances, which requires sub-millisecond node-to-node network latency. Client requests are routed to the application container on port 8443 via a Network Load Balancer (NLB). A separate health-reporting daemon runs on port 8088 on each EC2 instance. Currently, the inter-node MPI communication is slow, resulting in calculation timeouts, and the NLB is marking all target EC2 instances as unhealthy. Which combination of actions should a solutions architect take to resolve these issues?

Launch the EC2 container instances in a spread placement group. In the NLB target group settings, configure the health check port to explicitly query port 8088.

Launch the EC2 container instances in a cluster placement group. Leave the NLB target group health check port set to the default traffic-port.

Launch the EC2 container instances in a cluster placement group. In the NLB target group settings, configure the health check port to explicitly query port 8088.

Launch the EC2 container instances in a partition placement group. Leave the NLB target group health check port set to the default traffic-port.

Show answer & explanation

Answer: Launch the EC2 container instances in a cluster placement group. In the NLB target group settings, configure the health check port to explicitly query port 8088.

Answer

Launch the EC2 container instances in a cluster placement group. In the NLB target group settings, configure the health check port to explicitly query port 8088.

The correct option is to launch the EC2 container instances in a cluster placement group and configure the health check port to explicitly query port 8088. A cluster placement group packs instances close together within a single Availability Zone, which enables workloads to achieve the low-latency network performance required for Message Passing Interface (MPI) communication. Additionally, since the application receives traffic on port 8443 but the health-reporting daemon runs on port 8088, the target group's health check port must be explicitly configured to port 8088 instead of the default traffic-port.

Step-by-Step Solution

Analyze the inter-node network requirements for the tightly-coupled MPI calculations.

Identify that MPI requires low-latency, high-throughput node-to-node communication.

Choosing the correct placement group is essential to minimize network latency between EC2 container instances.

Select the appropriate EC2 placement group type.

Select a cluster placement group to group the instances close together within a single Availability Zone.

A cluster placement group enables low-latency network performance, which is required for tightly-coupled applications like MPI.

Analyze the Network Load Balancer target group health check configuration.

Identify that the application traffic is on port 8443, but the health status daemon is on port 8088.

By default, target groups use the traffic-port (8443) for health checks, which leads to failures since the health status service is listening on port 8088.

Reconfigure the health check port on the target group.

Explicitly define port 8088 as the health check port.

This allows the NLB to query the correct health daemon, successfully marking healthy instances as healthy.

Key Concept

Selecting cluster placement groups for low-latency node communication, and configuring custom health check ports in load balancer target groups.

Estimated Time:2m 0s

Question 909Question →

A media company is reviewing the network architecture of its analytics platform in the us-east-1 Region. The architecture consists of a primary processing VPC (VPC A) containing EC2 instances in private subnets, and a data warehouse VPC (VPC B) containing an Amazon Redshift cluster.

The EC2 instances in VPC A perform the following network operations monthly:
- Download $80\text{ TB}$ of raw datasets from an Amazon S3 bucket located in the us-east-1 Region.
- Upload $20\text{ TB}$ of cleansed datasets back to the same Amazon S3 bucket.
- Query and load $40\text{ TB}$ of aggregated results into the Amazon Redshift cluster in VPC B.
- Download $500\text{ GB}$ of software patches from external public internet repositories.

Currently, VPC A and VPC B are connected via an AWS Transit Gateway. The private subnets in VPC A route all non-VPC traffic ( $0.0.0.0/0$ ) through a NAT Gateway in a public subnet of VPC A.

Which network architecture configuration will meet these requirements while minimizing data transfer and routing costs?

Configure a Gateway VPC Endpoint for Amazon S3 in VPC A. Establish a VPC Peering connection between VPC A and VPC B, and configure the route tables to route traffic between the two VPCs through the VPC Peering connection. Retain the NAT Gateway in VPC A for external internet traffic.

Keep the existing AWS Transit Gateway connection and the NAT Gateway in VPC A. Route all Amazon S3 traffic through the NAT Gateway and route the database traffic to VPC B through the AWS Transit Gateway.

Establish a VPC Peering connection between VPC A and VPC B to route database traffic. Replace the NAT Gateway in VPC A with an Interface VPC Endpoint for Amazon S3, routing all S3 traffic through the Interface Endpoint, and configure a Network ACL to bypass data processing charges for S3 traffic.

Configure a Gateway VPC Endpoint for Amazon S3 in VPC A. Route database traffic to VPC B over a new AWS Site-to-Site VPN connection established between the two VPCs to avoid Transit Gateway costs, and route external internet traffic through the VPN connection.

Show answer & explanation

Answer: Configure a Gateway VPC Endpoint for Amazon S3 in VPC A. Establish a VPC Peering connection between VPC A and VPC B, and configure the route tables to route traffic between the two VPCs through the VPC Peering connection. Retain the NAT Gateway in VPC A for external internet traffic.

Answer

The correct architecture uses a Gateway VPC Endpoint for Amazon S3, which eliminates all NAT Gateway data processing charges for the

100\text{ TB}

of monthly S3 traffic because Gateway Endpoints are free. It also replaces the AWS Transit Gateway connection for inter-VPC database traffic with a VPC Peering connection, which removes the Transit Gateway data processing fee of

\$0.02

per GB. The NAT Gateway is kept only for the low-volume

500\text{ GB}

of external internet traffic, keeping NAT Gateway costs minimal.

Step-by-Step Solution

Analyze Amazon S3 traffic and costs.

Amazon S3 downloads and uploads total

100\text{ TB}

monthly. Routing this through the NAT Gateway costs

100 \times 1,024 \times 0.045 = \$4,608

in data processing fees.

Identifying the largest cost driver allows prioritizing the most effective solution, which is deploying a free S3 Gateway VPC Endpoint.

Analyze inter-VPC traffic and costs.

Database load traffic to VPC B totals

40\text{ TB}

monthly. Routing this through the AWS Transit Gateway costs

40 \times 1,024 \times 0.02 = \$819.20

in data processing fees.

Comparing Transit Gateway fees to VPC Peering (which has no data processing fees) shows that VPC Peering is significantly cheaper for high-throughput regional traffic.

Evaluate internet patch download requirements.

Patch traffic is only

500\text{ GB}

monthly, costing

500 \times 0.045 = \$22.50

via NAT Gateway.

Since the volume is very small, keeping the NAT Gateway for external internet traffic is cost-effective and avoids complex architectures.

Key Concept

Selecting the most cost-effective network routing path by replacing NAT Gateways and AWS Transit Gateway with Gateway VPC Endpoints and VPC Peering for high-volume internal data transfers.

Question 910Question →

A logistics enterprise is migrating its central shipping tracking application to AWS. The application runs on Amazon ECS container instances distributed across three Availability Zones. The storage solution for the application must provide concurrent read/write POSIX-compliant file system access, offer sub-millisecond latency for active shipping manifests, and deliver 99.99% availability. Additionally, compliance mandates that the manifests must be replicated to a secondary AWS Region with a Recovery Point Objective (RPO) of 15 minutes. Which combination of storage configurations will meet these requirements? (Select TWO.)

Select all that apply

Deploy Amazon Elastic File System (Amazon EFS) with the Standard storage class to provide shared, multi-Availability Zone storage.

Configure Amazon EFS Replication to automatically replicate the file system to the secondary AWS Region.

Provision Amazon EBS gp3 volumes with Multi-Attach enabled, and mount them across all ECS container instances in the three Availability Zones.

Deploy Amazon EFS using the One Zone storage class and use AWS Backup to schedule replication to the secondary AWS Region.

Store the active manifests in an Amazon S3 bucket and configure an S3 Lifecycle policy to transition them to the S3 Glacier Instant Retrieval storage class in the secondary AWS Region.

Show answer & explanation

Answer: Deploy Amazon Elastic File System (Amazon EFS) with the Standard storage class to provide shared, multi-Availability Zone storage.; Configure Amazon EFS Replication to automatically replicate the file system to the secondary AWS Region.

Answer

Deploying Amazon EFS using the Standard storage class and configuring Amazon EFS Replication to the secondary AWS Region.

Deploying Amazon EFS using the Standard storage class provides a highly available, multi-AZ, POSIX-compliant shared file system supporting concurrent access from multiple ECS instances with sub-millisecond latency. Configuring Amazon EFS Replication automatically replicates the data to a destination region with a typical replication delay of minutes, meeting the 15-minute RPO requirement.

Step-by-Step Solution

Analyze the file system and availability requirements.

Identify that the application requires concurrent, multi-AZ, POSIX-compliant access with sub-millisecond latency. Amazon EFS Standard meets this criteria.

EBS Multi-Attach cannot cross Availability Zones, and Amazon S3 does not natively support POSIX-compliant shared file mounting with concurrent read/writes.

Analyze the disaster recovery and RPO requirements.

Identify that the RPO requirement is 15 minutes, which requires a near real-time replication strategy. Amazon EFS Replication meets this requirement by automatically replicating changes within minutes.

Alternative backup tools like AWS Backup or manual snapshots do not support replication intervals that can guarantee a 15-minute RPO.

Key Concept

Amazon EFS replication provides cross-region replication for multi-AZ, POSIX-compliant shared file systems with low RPO targets.

Question 911Question →

A healthcare provider is deploying a critical patient scheduling web application on AWS that requires a highly resilient database tier. The database must support automatic failover with a Recovery Time Objective ( $RTO$ ) of less than 60 seconds and a Recovery Point Objective ( $RPO$ ) of $0$ (no data loss). Additionally, the application experiences read-heavy traffic spikes during morning scheduling hours that must be scaled efficiently.

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

Select all that apply

Deploy the database as an Amazon Aurora MySQL DB cluster with a primary DB instance and one or more Aurora Replicas in different Availability Zones.

Configure the application to connect to the database cluster's reader endpoint for read operations.

Deploy a single-instance Amazon RDS for MySQL database and configure an RDS Read Replica in a different Availability Zone to serve as the automatic failover target.

Set up an Amazon RDS for MySQL Multi-AZ DB instance deployment and configure the application to write to the secondary standby replica during peak hours to distribute write load.

Configure an Amazon Route 53 Latency routing policy to redirect database connection traffic to a backup database in a different AWS Region when the primary database is unhealthy.

Show answer & explanation

Answer: Deploy the database as an Amazon Aurora MySQL DB cluster with a primary DB instance and one or more Aurora Replicas in different Availability Zones.; Configure the application to connect to the database cluster's reader endpoint for read operations.

Answer

Deploy the database as an Amazon Aurora MySQL DB cluster with a primary DB instance and one or more Aurora Replicas in different Availability Zones, and configure the application to connect to the database cluster's reader endpoint for read operations.

Deploying an Amazon Aurora cluster with Replicas in different Availability Zones provides automated failover within 30 seconds without data loss because of its shared virtual storage volume, meeting both RTO and RPO requirements. Utilizing the reader endpoint allows the application to balance read requests across the replicas, solving the read scaling requirement.

Step-by-Step Solution

Evaluate the HA, RTO, and RPO requirements.

The requirement of automatic failover, RTO < 60s, and RPO = 0 points to Amazon Aurora's shared storage architecture with Aurora Replicas, which automatically handles failover in about 30 seconds with no data loss.

Standard RDS Multi-AZ DB instances provide HA but do not natively scale reads without adding separate Read Replicas, whereas Aurora integrates replica failover and cluster-wide read scalability out of the box.

Address the read scaling requirement.

Using the Aurora reader endpoint directs read traffic to the Aurora Replicas, offloading read-heavy queries from the primary writer instance.

This scales reads efficiently during morning traffic spikes without impacting write operations.

Analyze why other choices are incorrect.

Configurations relying on manual promotion of RDS Read Replicas or attempting to write directly to passive RDS standby replicas fail to meet high availability or operational guidelines.

RDS standby instances in a Multi-AZ deployment do not accept connections, and RDS Read Replicas are asynchronously replicated and cannot failover automatically.

Key Concept

High availability and read scaling in Amazon Aurora DB clusters

Question 912Question →

A media production team is deploying a collaborative video editing application on AWS. The application runs on a fleet of Amazon EC2 Linux instances that require concurrent read and write access to a shared directory. The workload is highly unpredictable, with aggregate throughput scaling rapidly from $50\text{ MB/s}$ to over $3\text{ GB/s}$ within seconds during active editing periods. The application requires latency of less than $1\text{ ms}$ for metadata operations and must not experience performance throttling during sudden spikes.

Which storage configuration meets these requirements with the lowest operational overhead?

Amazon Elastic File System (Amazon EFS) configured with General Purpose performance mode and Elastic throughput.

Amazon Elastic File System (Amazon EFS) configured with Max I/O performance mode and Provisioned throughput set to

3\text{ GB/s}

Amazon Elastic Block Store (Amazon EBS) gp3 volumes configured with EBS Multi-Attach enabled and formatted with a clustered file system.

Amazon FSx for Lustre persistent SSD file system configured with data repository integration to automatically sync with Amazon S3.

Show answer & explanation

Answer: Amazon Elastic File System (Amazon EFS) configured with General Purpose performance mode and Elastic throughput.

Answer

Amazon Elastic File System (Amazon EFS) configured with General Purpose performance mode and Elastic throughput.

The configuration of Amazon EFS with General Purpose performance mode and Elastic throughput satisfies all requirements. General Purpose mode ensures that metadata operations maintain sub-millisecond latencies. Elastic throughput is ideal for unpredictable workloads, automatically scaling up to

10\text{ GB/s}

for reads and

3\text{ GB/s}

for writes to accommodate sudden spikes without provisioning overhead.

Step-by-Step Solution

Analyze the access requirement.

The instances require concurrent read and write access to a shared directory, pointing to a shared file system solution such as Amazon EFS or Amazon FSx.

Amazon EBS volumes (except io1/io2 with Multi-Attach) cannot be attached to multiple instances simultaneously, and standard block storage is not a shared file system.

Evaluate latency and performance requirements.

Metadata operations must be under

1\text{ ms}

, which requires Amazon EFS General Purpose mode rather than Max I/O mode.

Max I/O mode trades higher metadata latencies for higher scale-out parallel throughput.

Select the appropriate throughput mode based on the scaling pattern.

The throughput is highly unpredictable, scaling rapidly up to

3\text{ GB/s}

. Elastic throughput handles this automatically without manual capacity management.

Elastic throughput automatically scales up and down to match workload demands, avoiding throttling and operational overhead.

Key Concept

Selecting and configuring the optimal Amazon EFS performance and throughput modes for low-latency, highly unpredictable shared storage workloads.

Estimated Time:2m 0s

Question 913Question →

A department within an enterprise is running a temporary proof of concept on AWS. The department manager wants to receive an email notification as soon as the actual accumulated cost for the current month exceeds a budget of $500. Which AWS service should a solutions architect use to configure these proactive alerts with minimal operational overhead?

AWS Budgets

AWS Cost Explorer

AWS Billing Conductor

AWS Pricing Calculator

Show answer & explanation

Answer: AWS Budgets

Answer

AWS Budgets

AWS Budgets is the standard tool to monitor costs proactively and send email notifications when costs exceed (or are forecasted to exceed) a user-defined threshold.

Step-by-Step Solution

Identify the primary requirement: receiving proactive email notifications when actual monthly costs exceed a specific threshold ($500).

The solution must support real-time threshold monitoring and automated email delivery.

This filters out tools that are purely retrospective or require manual intervention to check costs.

Evaluate AWS Budgets against the requirement.

AWS Budgets directly supports creating a cost budget, setting a threshold at $500, and assigning email recipients for notifications.

AWS Budgets is designed exactly for proactive threshold-based cost alerting.

Evaluate the other options to ensure they do not meet the criteria with less overhead.

AWS Cost Explorer is for retrospective analysis; AWS Billing Conductor is for custom billing rules; AWS Pricing Calculator is for pre-deployment estimates.

None of the other options provide native, simple email alerts for active account spending.

Key Concept

AWS Budgets provides proactive monitoring and alerting for cost thresholds, whereas other tools focus on historical analysis, custom pricing, or cost estimation.

Estimated Time:45s

Question 914Question →

A company is deploying a distributed financial transaction processing application on a cluster of Amazon EC2 instances. The nodes in the cluster must communicate with each other with the lowest possible network latency and the highest throughput. Which EC2 configuration should a solutions architect select to meet these networking requirements?

Launch the EC2 instances in a cluster placement group within a single Availability Zone.

Launch the EC2 instances in a spread placement group across multiple Availability Zones.

Launch the EC2 instances in a partition placement group to isolate the nodes onto separate logical partitions.

Deploy the EC2 instances behind an Application Load Balancer and configure the target group health check to query HTTP port 80 while the application service runs on port 8080.

Show answer & explanation

Answer: Launch the EC2 instances in a cluster placement group within a single Availability Zone.

Answer

Launch the EC2 instances in a cluster placement group within a single Availability Zone.

Launching the EC2 instances in a cluster placement group within a single Availability Zone is correct because it logically groups the instances on the same physical hardware backplane. This provides the minimum possible physical distance between the network interfaces, enabling low-latency, high-throughput node-to-node communication.

Step-by-Step Solution

Identify the workload's key performance requirements.

Recognize that the distributed cluster requires the lowest possible network latency and maximum node-to-node throughput.

This establishes that the physical proximity of the instances is the primary constraint.

Evaluate the available placement group configurations and load-balancing topologies.

Select the cluster placement group option over spread, partition, or load-balanced options.

Cluster placement groups are the only configuration designed specifically to pack instances close together on the underlying hardware to minimize network latency.

Key Concept

EC2 Placement Groups for High-Performing Compute

Question 915Question →

A company manages its multi-account environment using AWS Organizations. The company needs to implement a cost management strategy that achieves two goals:

1. Provide specific internal product teams with a customized view of their AWS bills that reflects their negotiated internal transfer pricing rates rather than standard AWS public pricing.
2. Proactively alert the operations team when a sudden, unexpected cost increase occurs due to abnormal resource provisioning, without the need to define static budget limits.

Which solution will meet these requirements with the least administrative effort?

Create billing groups and apply custom pricing rules in AWS Billing Conductor to reflect the internal transfer pricing rates. Configure AWS Cost Anomaly Detection with a monitor to alert the operations team of unexpected cost spikes.

Create custom billing reports in AWS Cost Explorer to display the negotiated internal rates. Configure an AWS Budgets alert with a forecasted threshold of 100% to identify abnormal resource provisioning.

Create billing groups and apply custom pricing rules in AWS Billing Conductor to reflect the internal transfer pricing rates. Configure a daily scheduled AWS Cost Explorer report to monitor cost changes and email the operations team.

Configure AWS Budgets to apply custom discount rates to member accounts. Configure AWS Cost Anomaly Detection to monitor consolidated spend and alert when costs deviate from historical averages.

Show answer & explanation

Answer: Create billing groups and apply custom pricing rules in AWS Billing Conductor to reflect the internal transfer pricing rates. Configure AWS Cost Anomaly Detection with a monitor to alert the operations team of unexpected cost spikes.

Answer

The correct solution uses AWS Billing Conductor to set custom pricing rules and billing groups for product teams, which directly supports internal showback and customized rate views. It also uses AWS Cost Anomaly Detection, which leverages machine learning to automatically establish baseline cost behaviors and proactively alert on unexpected anomalies without needing manual static thresholds.

Step-by-Step Solution

Analyze the requirement for customizing the billing view for internal teams to reflect negotiated rates.

Identify AWS Billing Conductor as the service designed to define custom billing groups, pricing rules, and showback/chargeback structures.

AWS Billing Conductor is the only service that can generate alternative billing outputs and custom rates separate from the AWS consolidated invoice.

Analyze the requirement for proactive, dynamic alerting on unexpected spending spikes without static thresholds.

Identify AWS Cost Anomaly Detection as the optimal service because it uses machine learning to model historical patterns and detect unusual spend.

AWS Budgets and Cost Explorer reports require manual configuration of static values and are retrospective, failing to catch unexpected spikes dynamically.

Select the option that combines AWS Billing Conductor for custom rates and AWS Cost Anomaly Detection for dynamic alerts.

Match these tools to the correct solution option.

This combination fulfills all requirements with minimal administrative overhead.

Key Concept

AWS Billing Conductor is used for custom rate modeling and showback workflows, while AWS Cost Anomaly Detection provides automated, machine-learning-driven alerting on cost spikes without static thresholds.

Estimated Time:2m 30s

Question 916Question →

A media production company needs to transfer large raw video files (averaging $50\text{ GB}$ each) from its on-premises editing studio to Amazon S3. The file transfer process requires a secure, encrypted connection over the internet with a minimum throughput of $2\text{ Gbps}$ to meet production deadlines. The solutions architect must also ensure that only the studio's public IP range ( $198.51.100.0/24$ ) can initiate inbound network connections to the destination resources in the VPC. Which configuration should the solutions architect recommend to meet these requirements with the highest network performance?

Establish an AWS Site-to-Site VPN connection to an AWS Transit Gateway with Equal-Cost Multi-Path (ECMP) routing enabled, using multiple VPN tunnels to distribute traffic. Configure stateful Security Groups on the destination resources to allow inbound traffic from the studio's IP range of

198.51.100.0/24

Establish a single AWS Site-to-Site VPN connection directly to a Virtual Private Gateway in the VPC to support the

2\text{ Gbps}

transfer. Configure stateful Security Groups on the destination resources to allow inbound traffic from the studio's IP range of

198.51.100.0/24

Establish an AWS Site-to-Site VPN connection to an AWS Transit Gateway with Equal-Cost Multi-Path (ECMP) routing enabled. Configure a stateless Network Access Control List (NACL) on the destination subnet to allow inbound traffic from the studio's IP range of

198.51.100.0/24

, relying on the stateless nature of the NACL to automatically permit all return traffic.

Establish an AWS Site-to-Site VPN connection to an AWS Transit Gateway with Equal-Cost Multi-Path (ECMP) routing enabled. Use Amazon Route 53 latency routing to distribute file upload requests across the VPN tunnels to optimize performance and ensure failover, without configuring Route 53 health checks.

Show answer & explanation

Answer: Establish an AWS Site-to-Site VPN connection to an AWS Transit Gateway with Equal-Cost Multi-Path (ECMP) routing enabled, using multiple VPN tunnels to distribute traffic. Configure stateful Security Groups on the destination resources to allow inbound traffic from the studio's IP range of $198.51.100.0/24$ .

Answer

The correct answer correctly addresses both the throughput and filtering constraints. To exceed the

1.25\text{ Gbps}

limit of a single AWS Site-to-Site VPN tunnel, you must deploy the VPN over an AWS Transit Gateway and enable Equal-Cost Multi-Path (ECMP) routing. This configuration scales bandwidth by allowing active-active routing over multiple tunnels. Additionally, utilizing stateful Security Groups ensures that inbound traffic is restricted to the studio's IP range while automatically allowing outbound responses without manually opening ephemeral port ranges.

Step-by-Step Solution

Evaluate the throughput requirement against AWS Site-to-Site VPN limitations.

Identify that a single AWS VPN tunnel has a hard limit of

1.25\text{ Gbps}

. Since the requirement is

2\text{ Gbps}

, a single standard VPN connection is insufficient.

Ensures that the design does not violate physical performance boundaries of AWS VPN endpoints.

Determine the routing mechanism to aggregate VPN throughput.

Select AWS Transit Gateway with Equal-Cost Multi-Path (ECMP) routing enabled, which dynamically balances traffic across multiple VPN tunnels, allowing throughput to scale beyond

1.25\text{ Gbps}

ECMP is required to bundle multiple tunnels and achieve active-active path distribution for high throughput.

Determine the network filtering security mechanism to restrict access while ensuring return traffic flow.

Choose stateful Security Groups to allow inbound traffic from

198.51.100.0/24

. Security Groups automatically track connection state and allow return traffic dynamically.

Avoids the configuration overhead and potential connection drop issues associated with stateless Network ACLs.

Key Concept

Scalable Hybrid Connectivity and Network Filtering Statefulness

Estimated Time:2m 0s

Question 917Question →

A financial analytics firm is deploying a high-performance computing (HPC) modeling workload on a fleet of Amazon EC2 Linux instances. The application requires a shared, POSIX-compliant storage system that can handle concurrent read and write operations from all instances, deliver sub-millisecond latencies, and scale throughput to at least $80\text{ GB/s}$ for processing large datasets. Which combination of steps should a solutions architect recommend to meet these requirements? (Select TWO.)

Select all that apply

Deploy an Amazon FSx for Lustre file system to store and serve the shared datasets.

Mount the shared file system on the Amazon EC2 instances using the Lustre client.

Configure an Amazon EFS file system with Elastic throughput mode and mount it on the instances.

Provision an Amazon EBS io2 Block Express volume with Multi-Attach enabled and mount it on all instances.

Deploy an Amazon S3 bucket and use AWS Transfer Acceleration to mount it as a local directory on the EC2 instances.

Show answer & explanation

Answer: Deploy an Amazon FSx for Lustre file system to store and serve the shared datasets.; Mount the shared file system on the Amazon EC2 instances using the Lustre client.

Answer

Deploying an Amazon FSx for Lustre file system and mounting it on the Amazon EC2 instances using the Lustre client.

Amazon FSx for Lustre is a high-performance parallel file system designed specifically for compute-intensive workloads such as machine learning and high-performance computing (HPC). It provides sub-millisecond latencies, supports concurrent access from hundreds of EC2 instances, and scales throughput to hundreds of gigabytes per second. To mount and interact with the parallel file system, the client instances must run the open-source Lustre client.

Step-by-Step Solution

Analyze the storage performance and access pattern requirements of the HPC workload.

The workload requires concurrent, POSIX-compliant access from a fleet of hundreds of instances, sub-millisecond latency, and at least

80\text{ GB/s}

of throughput scale.

Understanding these requirements is critical to selecting the appropriate AWS storage service.

Evaluate FSx for Lustre as the shared file system.

Amazon FSx for Lustre is a parallel file system designed for HPC workloads, supporting concurrent access by hundreds of instances and scaling to hundreds of gigabytes per second of throughput with sub-millisecond latencies.

It matches the scalability and performance requirements of the workload.

Determine the connection method for the EC2 fleet to the FSx for Lustre file system.

The open-source Lustre client must be installed on the Linux EC2 instances to mount the shared file system.

This allows the EC2 instances to interact with the file system concurrently with high performance.

Key Concept

HPC storage requirements and the application of Amazon FSx for Lustre to meet high-throughput parallel access demands.

Question 918Question →

An analytics firm wants to establish a secure, hybrid network connection between its on-premises database and a VPC on AWS to stream daily transactions. The transaction stream peaks at $2.0\text{ Gbps}$ of continuous bandwidth. The firm wants to leverage its existing internet connection and use IPSec VPN for security. Which TWO options should the solutions architect configure to establish a high-performing and scalable connection?

Select all that apply

Enable Equal-Cost Multi-Path (ECMP) routing on the AWS Transit Gateway.

Configure the customer gateway to establish multiple VPN connections terminating on the AWS Transit Gateway and advertise the same on-premises routes via Border Gateway Protocol (BGP).

Establish a single AWS Site-to-Site VPN connection to a virtual private gateway, since a single VPN tunnel dynamically scales to support up to 2.5 Gbps.

Configure stateful Network ACL rules on the target subnets to track and permit return traffic for the high-throughput streams.

Use Amazon Route 53 latency-based routing to distribute the replication traffic across multiple customer gateway IP addresses without configuring health checks.

Show answer & explanation

Answer: Enable Equal-Cost Multi-Path (ECMP) routing on the AWS Transit Gateway.; Configure the customer gateway to establish multiple VPN connections terminating on the AWS Transit Gateway and advertise the same on-premises routes via Border Gateway Protocol (BGP).

Answer

Enabling Equal-Cost Multi-Path (ECMP) routing on the AWS Transit Gateway and configuring the customer gateway to establish multiple VPN connections terminating on the AWS Transit Gateway and advertise the same on-premises routes via Border Gateway Protocol (BGP).

To achieve a network throughput exceeding

1.25\text{ Gbps}

over IPSec VPN, multiple VPN tunnels must be aggregated. AWS Transit Gateway supports Equal-Cost Multi-Path (ECMP) routing, which balances traffic dynamically across multiple tunnels. By configuring the customer gateway to establish multiple VPN tunnels and advertising identical prefixes via BGP, the Transit Gateway can distribute the

2.0\text{ Gbps}

load equally among the active tunnels.

Step-by-Step Solution

Identify the bandwidth constraint of a single AWS Site-to-Site VPN tunnel.

A single VPN tunnel has a maximum throughput of

1.25\text{ Gbps}

The peak bandwidth requirement is

2.0\text{ Gbps}

, which exceeds a single tunnel's capability.

Select the aggregation mechanism to scale VPN throughput.

AWS Transit Gateway with Equal-Cost Multi-Path (ECMP) routing enabled.

ECMP allows the network to distribute traffic across multiple active paths (tunnels) to achieve aggregate throughput greater than

1.25\text{ Gbps}

Configure routing on the customer gateway to support ECMP.

Establish multiple VPN connections terminating on the AWS Transit Gateway and advertise the same prefixes using Border Gateway Protocol (BGP).

The Transit Gateway requires BGP to dynamically balance traffic over multiple paths using ECMP.

Key Concept

Scaling VPN throughput using AWS Transit Gateway and Equal-Cost Multi-Path (ECMP) routing.

Estimated Time:2m 0s

Question 919Question →

A financial services company is redesigning a legacy batch-processing application to reduce costs and automate scaling. The application processes large transaction files uploaded to an Amazon S3 bucket. Each file contains sequential transaction records that must be processed in the exact order of their arrival to prevent account balance discrepancies. The processing logic is compute-intensive, taking between 20 to 45 minutes per file, and the workload is highly unpredictable, with hours of inactivity followed by sudden bursts of files. Which architecture is the most cost-effective and meets the requirements?

Configure Amazon S3 to send event notifications that directly trigger an AWS Lambda function for each uploaded file, adjusting the Lambda memory and ephemeral storage configurations to handle the compute-intensive load.

Configure Amazon S3 to send event notifications to a standard Amazon SQS queue. Deploy the processing application on Amazon EC2 Spot Instances in an Auto Scaling group, scaling the group size based on CPU utilization to minimize compute costs.

Configure Amazon S3 to send event notifications to an Amazon SQS FIFO queue. Deploy the processing application as an Amazon ECS service using AWS Fargate, and configure an AWS Application Auto Scaling policy based on the ApproximateNumberOfMessagesVisible metric to scale Fargate tasks from zero to match the queue depth.

Configure Amazon S3 to send event notifications to an Amazon SQS FIFO queue. Deploy the processing application as an Amazon ECS service on AWS Fargate in private subnets, routing all Amazon S3 file transfers through a NAT Gateway to ensure secure access while scaling Fargate tasks based on queue depth.

Show answer & explanation

Answer: Configure Amazon S3 to send event notifications to an Amazon SQS FIFO queue. Deploy the processing application as an Amazon ECS service using AWS Fargate, and configure an AWS Application Auto Scaling policy based on the ApproximateNumberOfMessagesVisible metric to scale Fargate tasks from zero to match the queue depth.

Answer

The most cost-effective and compliant architecture is to send S3 event notifications to an Amazon SQS FIFO queue, process the files using Amazon ECS tasks on AWS Fargate, and auto-scale the Fargate tasks from zero based on the queue depth metric.

The correct architecture combines Amazon SQS FIFO queues to satisfy the strict ordering requirements with Amazon ECS on AWS Fargate to handle execution times that exceed the 15-minute AWS Lambda timeout limit. Using AWS Application Auto Scaling to adjust tasks based on queue depth ensures that compute resources scale down to zero during idle periods, maximizing cost-efficiency.

Step-by-Step Solution

Evaluate the runtime limits of the compute options.

Identify that the file processing takes 20 to 45 minutes, which exceeds the 15-minute execution limit of AWS Lambda, requiring a containerized compute solution such as Amazon ECS on AWS Fargate.

This rules out direct AWS Lambda invocation as a viable option due to hard timeouts.

Analyze the message ordering requirements.

Identify that transaction records must be processed in the exact sequence they arrive to prevent data inconsistency.

This necessitates the use of an Amazon SQS FIFO queue rather than a standard SQS queue, which only offers best-effort ordering.

Select the scaling mechanism to optimize costs during idle periods.

Configure AWS Application Auto Scaling to adjust the number of ECS Fargate tasks based on the ApproximateNumberOfMessagesVisible metric of the SQS FIFO queue.

This allows the architecture to scale down to zero tasks when the queue is empty, eliminating idle compute costs during inactive periods.

Identify network cost optimization strategies.

Ensure that large data transfers to Amazon S3 do not route through a NAT Gateway, which charges data processing fees.

Routing traffic through a Gateway VPC Endpoint for S3 keeps S3 data transfers free of network charges, whereas a NAT Gateway introduces significant unnecessary costs.

Key Concept

Serverless and Automated Scaling Architectures for Cost Efficiency

Estimated Time:3m 0s

Question 920Question →

A company has two VPCs in the same AWS Region and needs to connect them to allow high-volume data transfers between applications. The company wants to minimize data transfer and connection infrastructure costs. Which two options should the solutions architect choose to meet these requirements? (Select TWO.)

Select all that apply

Establish a VPC peering connection between the two VPCs.

Configure the applications to communicate using private IP addresses.

Set up an AWS Transit Gateway to route traffic between the VPCs.

Route traffic through NAT Gateways deployed in public subnets in each VPC.

Route traffic over the internet using Elastic IP addresses assigned to the instances.

Show answer & explanation

Answer: Establish a VPC peering connection between the two VPCs.; Configure the applications to communicate using private IP addresses.

Answer

Establishing a VPC peering connection and configuring the applications to communicate using private IP addresses.

Establishing a VPC peering connection is the most cost-effective way to connect two VPCs in the same Region because VPC peering has no hourly charge and no data processing fees. Configuring applications to use private IP addresses ensures that traffic routes directly over the peering connection, avoiding the hourly and data processing costs of NAT Gateways or the egress costs of public internet routing.

Step-by-Step Solution

Analyze the requirements for connecting two VPCs in the same Region while minimizing cost.

Identify that the connection method must avoid unnecessary hourly resource fees and per-GB data processing fees.

This establishes the cost-minimization parameters for the connection.

Compare VPC Peering with AWS Transit Gateway and VPN connection options.

Determine that VPC peering is the most cost-effective connection type because it has no hourly setup fees or data processing charges, unlike Transit Gateway or VPN.

Selecting VPC Peering over Transit Gateway directly optimizes the connection infrastructure cost.

Determine the IP routing mechanism to minimize data transfer costs.

Determine that routing traffic using private IP addresses avoids NAT Gateway data processing charges and public internet egress fees.

Using private IPs keeps traffic internal to the AWS network backbone and avoids per-GB routing costs.

Key Concept

VPC Peering and private IP routing are the most cost-effective methods for inter-VPC communication within the same Region.

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