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Question 1241Question →

A company runs a read-heavy reporting application on AWS. The application uses an Amazon RDS for PostgreSQL DB instance to store analytical data. The database requires high read throughput during weekly reporting windows, but does not have strict high availability (HA) or automatic failover requirements for write operations. The database is currently configured as a Multi-AZ DB instance. A solutions architect needs to optimize the database configuration to reduce monthly costs while maintaining read performance.

Which TWO actions should the solutions architect take to achieve this goal? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: Modify the RDS DB instance from a Multi-AZ deployment to a Single-AZ deployment.; Create one or more RDS Read Replicas in different Availability Zones to handle the read-heavy reporting queries.

Answer

Modify the RDS DB instance from a Multi-AZ deployment to a Single-AZ deployment, and create one or more RDS Read Replicas in different Availability Zones to handle the read-heavy reporting queries.
The correct solution involves modifying the Amazon RDS DB instance to a Single-AZ deployment because the workload does not require high availability for write operations. To cost-effectively scale read throughput during weekly reporting windows, the solutions architect should deploy one or more RDS Read Replicas, which offload read queries from the primary instance.

Step-by-Step Solution

1
Analyze database write availability requirements
Identify that the application does not have strict high availability or automatic failover requirements for write operations.
This allows the removal of the synchronous Multi-AZ standby instance, which halves the base database instance costs.
2
Identify database read scaling requirements
Determine that read capacity needs to scale during weekly reporting windows.
Deploying cost-effective Read Replicas meets the read scaling requirements horizontally without paying for a full Multi-AZ write standby.
3
Evaluate and eliminate incorrect cost optimization options
Eliminate Compute Savings Plans (which do not apply to RDS) and DynamoDB (which requires schema redesign and has high costs for spiky workloads in Provisioned mode).
This confirms the selected options are the most cost-effective and operationally feasible solutions.

Key Concept

RDS Multi-AZ vs. Single-AZ with Read Replicas
Question 1242Question →

A digital media platform is designing an event-driven news publishing system. When an editor publishes or updates an article, the system must broadcast the event to two backend services: a real-time mobile push notification service and an article search indexing service. The push notification service can process events in any order. However, the search indexing service must process updates for each article in the exact chronological sequence they were published to avoid indexing stale data. The system must automatically scale to handle traffic spikes without administrative intervention. Which combination of actions should a solutions architect take to meet these requirements? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: Create an Amazon SNS FIFO topic and publish article update events to it, using the article ID as the message group ID.; Create two Amazon SQS FIFO queues, subscribe both queues to the SNS FIFO topic, and configure each backend service to consume from its respective queue.

Answer

Create an Amazon SNS FIFO topic with the article ID as the message group ID, and subscribe two Amazon SQS FIFO queues to it so each backend service can consume from its own dedicated queue.
To maintain message sequence across a fan-out architecture, an Amazon SNS FIFO topic must be paired with Amazon SQS FIFO queues. The SNS FIFO topic preserves the order of messages sent by the publisher, and specifying the article ID as the Message Group ID ensures that updates for the same article are processed in order. Since SNS FIFO topics only support SQS FIFO queues as subscribers, both subscription queues must be FIFO queues.

Step-by-Step Solution

1
Analyze the fan-out and ordering requirements.
The architecture requires sending the same publishing event to multiple consumers (fan-out), where one consumer requires strict sequence ordering per article.
Identifying that a single publisher needs to distribute messages to multiple decoupled consumers helps select a publish-subscribe pattern using Amazon SNS and Amazon SQS.
2
Determine the appropriate Amazon SNS topic configuration.
Select an Amazon SNS FIFO topic and publish events using the article ID as the Message Group ID.
Standard SNS topics do not guarantee ordering. An SNS FIFO topic ensures message ordering is preserved within a message group, preventing race conditions or stale updates for a given article.
3
Identify the queue subscription requirements.
Create two Amazon SQS FIFO queues and subscribe both to the SNS FIFO topic.
Amazon SNS FIFO topics only support Amazon SQS FIFO queues as subscribers. SQS Standard queues cannot be subscribed to an SNS FIFO topic, meaning both destination queues must be FIFO to maintain end-to-end ordered delivery.

Key Concept

Amazon SNS FIFO and Amazon SQS FIFO integration for ordered message fan-out.
Estimated Time:2m 0s
Question 1243Question →

A company operates a food delivery dispatch platform in the us-east-1 Region. The architecture utilizes Amazon ECS on AWS Fargate for the microservices and an Amazon RDS for PostgreSQL Multi-AZ DB instance for the transactional database. The company needs to implement a disaster recovery (DR) strategy in the us-west-2 Region. The DR solution must achieve a Recovery Time Objective (RTO) of 30 minutes, a Recovery Point Objective (RPO) of 5 minutes, and minimize ongoing running costs in the secondary Region. Which strategy should a solutions architect recommend to meet these requirements?

Show answer & explanation

Answer: Configure an RDS for PostgreSQL cross-region read replica in the us-west-2 Region. Deploy an Application Load Balancer (ALB) in us-west-2 and configure an ECS service with a desired task count of zero. Set up Amazon Route 53 with failover routing and health checks. During a disaster, promote the read replica to a standalone DB instance, update the ECS service desired count to match production levels, and let Route 53 redirect traffic to the secondary ALB.

Answer

Configure an RDS for PostgreSQL cross-region read replica, set the secondary ECS task count to zero, use Route 53 failover routing with health checks, and promote the replica and scale up tasks during a failover event.
The correct strategy uses a Pilot Light approach. A cross-region RDS read replica replicates data asynchronously, keeping the RPO to a few seconds, which satisfies the 5-minute requirement. Running the secondary ECS service with a desired task count of zero minimizes running costs. Promoting the database to primary status and scaling up the ECS service tasks to production levels can be done in a few minutes, satisfying the 30-minute RTO.

Step-by-Step Solution

1
Select database replication strategy based on the RPO of 5 minutes.
Determine that an RDS cross-region read replica is necessary to continuously replicate data, ensuring data loss remains under 5 minutes.
Hourly backups or snapshots copied to another region would violate the 5-minute RPO limit.
2
Select the compute layer deployment strategy to minimize standby costs while meeting the 30-minute RTO.
Deploy an ALB and configure the secondary Region's ECS service with a desired task count of 0.
An active but scaled-down fleet increases running costs needlessly. Launching and scaling ECS Fargate tasks can be completed within minutes during a failover, well within the 30-minute limit.
3
Configure the DNS routing and failover automation.
Configure Route 53 failover routing with health checks pointing to the primary ALB, and define the manual or scripted steps to promote the RDS read replica and scale up the ECS tasks.
Active-active latency routing without health checks fails to steer traffic away from the degraded primary region.

Key Concept

Disaster Recovery (DR) Pilot Light Pattern on AWS
Question 1244Question →

A technology company is deploying a self-managed distributed search engine cluster on Amazon EC2 instances. The cluster nodes must communicate with each other with the lowest possible network latency to ensure fast query indexing. Additionally, an Application Load Balancer (ALB) is used to expose an internal management dashboard that runs on port 8443 of the same instances, while the standard HTTP port 80 is closed on the instances' firewalls. Which combination of configurations will meet the performance requirements and prevent the instances from being falsely marked as unhealthy by the load balancer?

Show answer & explanation

Answer: Deploy the EC2 instances in a cluster placement group. Configure the ALB target group's health checks to use port 8443.

Answer

Deploying the EC2 instances in a cluster placement group and configuring the Application Load Balancer's target group health check to port 8443.
Deploying the EC2 instances in a cluster placement group provides low-latency, high-throughput communication by physically grouping instances within a single Availability Zone. Additionally, configuring the Application Load Balancer (ALB) health checks to target port 8443 aligns the health probes with the port where the management daemon is actually listening, ensuring the instances are not incorrectly marked as unhealthy due to port 80 being closed.

Step-by-Step Solution

1
Determine the placement strategy for the EC2 instances to achieve the lowest possible network latency.
A cluster placement group is selected as it groups instances within a single Availability Zone for low-latency node-to-node communication.
This provides the required low-latency performance for the search engine cluster.
2
Check where the web management dashboard is running and which ports are open.
The management service runs on port 8443, and port 80 is closed on the firewall.
This determines the correct port for the load balancer health checks to prevent false negatives.
3
Configure the Application Load Balancer's health checks.
The ALB successfully monitors the running service on port 8443.
This ensures the ALB registers the instances as healthy since the service is listening on port 8443.

Key Concept

Amazon EC2 Placement Groups and Elastic Load Balancing Health Checks
Estimated Time:1m 30s
Question 1245Question →

A company has a web application that processes user registration requests. The requests must be processed asynchronously in the exact order they are received to ensure proper database indexing. The workload is highly unpredictable with sudden, massive traffic spikes. A solutions architect needs to decouple the frontend application from the backend processing servers. Which solution meets these requirements with the least operational overhead?

Show answer & explanation

Answer: Configure the web application to send the requests to an Amazon SQS FIFO queue, and configure backend servers to process the messages.

Answer

Configure the web application to send the requests to an Amazon SQS FIFO queue, and configure backend servers to process the messages.
The correct option is the one that configures the application to use Amazon SQS FIFO queues. FIFO queues guarantee that messages are processed in the exact order they are sent, satisfying the indexing requirement. Because SQS scales automatically to absorb spikes, it buffers the load for the backend servers, meeting the decoupling and resilience goals with the least operational overhead.

Step-by-Step Solution

1
Analyze the requirement for message ordering.
The messages must be processed in the exact order they are received to ensure proper database indexing.
This requirement rules out standard queue systems that do not guarantee ordering.
2
Evaluate Amazon SQS queue types.
Amazon SQS FIFO queues guarantee first-in, first-out delivery and single execution.
FIFO queues meet the ordering requirement while decoupling the application components.
3
Verify handling of unpredictable traffic spikes.
Amazon SQS automatically scales to handle spikes in traffic without manual provisioning.
This provides a highly resilient architecture with minimal operational overhead.

Key Concept

Decoupling with ordered message processing using SQS FIFO queues
Question 1246Question →

A gaming company hosts its dedicated multiplayer session servers on Amazon EC2. While player traffic fluctuates, the company requires a constant baseline of 50 EC2 instances 24/7 to maintain minimum coverage. Additionally, the company runs a continuous background analytics pipeline on Amazon ECS using AWS Fargate that requires a stable allocation of 20 vCPUs and 80 GB of RAM. The backend database runs on Amazon RDS for PostgreSQL 24/7. Which combination of purchasing options will provide the most cost-effective solution for this architecture?

Show answer & explanation

Answer: Purchase a Compute Savings Plan to cover the baseline EC2 instances and AWS Fargate tasks, and purchase Amazon RDS Reserved Instances for the PostgreSQL database.

Answer

Purchase a Compute Savings Plan to cover the baseline EC2 instances and AWS Fargate tasks, and purchase Amazon RDS Reserved Instances for the PostgreSQL database.
The correct option is the strategy of purchasing a Compute Savings Plan to cover both the baseline EC2 instances and AWS Fargate tasks, combined with Amazon RDS Reserved Instances for the PostgreSQL database. Compute Savings Plans provide the flexibility to apply discounts across both EC2 and AWS Fargate compute types under a single commitment, while RDS Reserved Instances are the correct vehicle to discount the continuous database compute usage.

Step-by-Step Solution

1
Analyze the compute components of the architecture.
The architecture contains three main compute components: Amazon EC2 instances for gaming sessions, AWS Fargate tasks for analytics, and Amazon RDS for the PostgreSQL database.
Understanding each component's hosting model is required to choose the correct purchasing strategy.
2
Evaluate the coverage of AWS Savings Plans.
Compute Savings Plans apply to EC2 instance usage, AWS Fargate, and AWS Lambda. EC2 Instance Savings Plans apply only to EC2 instances. Neither plan covers Amazon RDS.
This determines which savings plan type is appropriate for the EC2 and Fargate workloads.
3
Evaluate the purchasing options for the Amazon RDS database.
Amazon RDS cost optimization requires purchasing RDS Reserved Instances, as Savings Plans do not apply to RDS.
RDS has its own separate reservation model for 1-year or 3-year commitments.
4
Combine the findings into a single cost-optimized strategy.
A Compute Savings Plan covers the EC2 and Fargate baseline, and RDS Reserved Instances cover the RDS database baseline.
This matches the services to their respective discount mechanisms to achieve maximum cost savings.

Key Concept

Compute Savings Plans cover EC2, Fargate, and Lambda usage, whereas Amazon RDS requires RDS Reserved Instances for reservation discounts.
Estimated Time:2m 0s
Question 1247Question →

A company hosts a web application in the us-east-1 Region. The application stores static media files in an Amazon S3 bucket and uses an Amazon RDS for PostgreSQL database. To prepare for a disaster recovery (DR) scenario, the company wants to implement a Backup and Restore DR strategy in the us-west-2 Region. Which TWO options should a solutions architect recommend to copy the S3 objects and database backups to the secondary region?

Select all that apply

Show answer & explanation

Answer: Enable Amazon S3 Cross-Region Replication (CRR) on the source S3 bucket to replicate new object uploads to a destination bucket in the secondary region.; Configure AWS Backup to automatically replicate Amazon RDS database backups and snapshots to the secondary region.

Answer

The correct options are enabling Amazon S3 Cross-Region Replication (CRR) and using AWS Backup to replicate database backups to the secondary region.
For a Backup and Restore disaster recovery strategy, the primary goal is to copy backups to a secondary region. Enabling Amazon S3 Cross-Region Replication (CRR) handles S3 objects automatically, while AWS Backup handles replicating RDS snapshots to the target region. Both solutions keep replication simple without requiring running database instances in the recovery region.

Step-by-Step Solution

1
Select the correct replication method for S3 data.
Identify that S3 Cross-Region Replication (CRR) automatically replicates objects across regions.
S3 CRR is the standard and most efficient way to keep static files synchronized across different regions with minimal operational overhead.
2
Select the correct replication method for database backups.
Identify that AWS Backup is the standard managed service to copy RDS backups across regions automatically.
Using AWS Backup simplifies cross-region copy operations and centralized backup compliance management.
3
Evaluate and eliminate incorrect architectures.
Eliminate options proposing automatic failover to read replicas, S3 Glacier for quick retrieval, and running a fully-scaled instance under a Pilot Light model.
These options contain configuration misconceptions regarding RDS cross-region behavior, Glacier retrieval latencies, and DR tier definitions.

Key Concept

Disaster recovery data replication
Estimated Time:1m 0s
Question 1248Question →

A logistics company is designing the database architecture for a new package tracking application. The application will receive rapid status updates from delivery drivers' handheld devices. The traffic profile consists of a stable baseline of approximately 200200 writes per second during business hours, but it experiences sudden, unpredictable spikes of up to 5,0005,000 writes per second when major distribution centers scan incoming shipments. The database must store these updates, which consist of simple key-value pairs of tracking ID, timestamp, and location. The company wants to minimize database costs while ensuring that no updates are throttled. Which database design and capacity configuration is the most cost-effective for this workload?

Show answer & explanation

Answer: Deploy an Amazon DynamoDB table configured in on-demand capacity mode.

Answer

Deploying an Amazon DynamoDB table in on-demand capacity mode is the most cost-effective design.
Deploying an Amazon DynamoDB table in on-demand capacity mode is the most cost-effective choice. The application data consists of simple key-value pairs, which is a perfect match for DynamoDB. Because the write spikes are sudden and unpredictable, on-demand capacity mode scales immediately to accommodate up to 5,0005,000 writes per second without throttling. This prevents the need to pay for statically provisioned peak capacity during baseline periods of 200200 writes per second.

Step-by-Step Solution

1
Analyze the database requirements and data model.
The application requires storing simple key-value pairs (tracking ID, timestamp, location), which aligns with NoSQL databases like Amazon DynamoDB rather than a more expensive relational database like Amazon RDS.
Choosing the correct database engine based on data structure is the first step in cost-optimization.
2
Evaluate the traffic patterns and scaling needs.
The traffic has a baseline of 200200 writes per second but experiences sudden, unpredictable spikes of up to 5,0005,000 writes per second.
Capacity planning requires selecting a scaling mechanism that matches the speed and predictability of workload spikes.
3
Compare DynamoDB capacity modes for cost and throttling prevention.
On-demand capacity mode scales instantly to handle the 5,0005,000 writes per second spike without throttling and charges only for consumed capacity. Provisioned capacity with Auto Scaling is too slow to react to sudden spikes, leading to throttling, while static provisioning of 5,0005,000 WCUs is highly wasteful.
On-demand mode eliminates idle capacity costs while meeting the high availability and zero-throttling requirements.

Key Concept

Selecting the cost-optimal database engine and capacity scaling mode based on workload data structure and predictability.
Question 1249Question →

A medical imaging provider hosts its diagnostic report processing application in the us-west-2 Region. The current architecture consists of EC2 instances in an Auto Scaling group behind an Application Load Balancer, and a multi-AZ Amazon Aurora PostgreSQL database. The provider needs to establish a disaster recovery (DR) strategy in the us-east-1 Region. The DR solution must achieve a Recovery Time Objective (RTO) of 15 minutes and a Recovery Point Objective (RPO) of 2 minutes, while minimizing ongoing infrastructure costs during normal operations. Which combination of actions should a solutions architect recommend to meet these requirements? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: Create an Amazon Aurora Global Database with the primary cluster in us-west-2 and a secondary cluster in us-east-1, configuring the secondary cluster to use Aurora Serverless v2 to scale down to a minimal configuration during idle periods.; Pre-provision an Application Load Balancer and an Auto Scaling group in us-east-1 with the minimum and desired capacity set to 0, and use an automated deployment script to scale out instances to match the primary region during a failover event.

Answer

The correct combination consists of creating an Amazon Aurora Global Database with a secondary cluster configured for Aurora Serverless v2, and pre-provisioning an Application Load Balancer and an Auto Scaling group in the recovery region with a minimum capacity of 0, which is scaled out via automation during failover.
The correct strategy combines database storage-level replication with a Pilot Light compute strategy. Amazon Aurora Global Database uses dedicated infrastructure to replicate data across regions with sub-second latency, satisfying the 2-minute RPO. Operating the secondary Aurora instances as Serverless v2 ensures they only consume minimal capacity when idle, keeping costs low. For the compute layer, pre-provisioning the Application Load Balancer and an Auto Scaling group with a capacity of 0 costs nothing for compute resources during normal operations, but keeps the infrastructure configuration warm. This allows automated scripts to scale the instances up within the 15-minute RTO during a disaster recovery event.

Step-by-Step Solution

1
Analyze RPO constraints
The target RPO is 2 minutes, which requires continuous database replication. Traditional snapshot copies copied every 15 minutes are insufficient.
Choosing a replication strategy with sub-second lag, such as Aurora Global Database, guarantees that data loss is minimized below the 2-minute window.
2
Analyze cost constraints for the database tier
Aurora Serverless v2 instances in the secondary region can scale down to a fraction of an ACU when idle, avoiding the high cost of provisioned instances.
This configuration provides the lowest standby cost while remaining ready to scale up immediately upon failover.
3
Analyze RTO and cost constraints for the compute tier
Setting up an Auto Scaling group with a minimum capacity of 0 in the recovery region ensures that no EC2 costs are incurred during normal operations.
Pre-provisioning the ALB and metadata allows the application to spin up instances quickly via scripts within the 15-minute RTO.

Key Concept

Disaster recovery designs (specifically Pilot Light) utilizing Aurora Global Database and scaled-down compute infrastructure to balance RTO/RPO targets against standby operational costs.
Question 1250Question →

A solutions architect is designing a database solution for a global fleet tracking application. The application must ingest real-time telemetry data from over 100,000 delivery vehicles, resulting in millions of write transactions per minute. The system requires consistent sub-millisecond write latency. The fleet operations are highly dynamic, with write traffic peaking heavily during business hours and dropping to near zero at night. Each telemetry record includes a unique vehicle identifier (VehicleID), a monotonically increasing timestamp (Timestamp), and location coordinates. The architect selects Amazon DynamoDB as the datastore. Which database design and configuration should the solutions architect implement to meet these requirements?

Show answer & explanation

Answer: Design the DynamoDB table with VehicleID as the partition key and Timestamp as the sort key, and configure the table with On-Demand capacity mode.

Answer

Design the DynamoDB table with VehicleID as the partition key and Timestamp as the sort key, and configure the table with On-Demand capacity mode.
Designing the table with VehicleID as the partition key provides high cardinality, distributing writes evenly across multiple partitions. Configuring On-Demand capacity mode ensures that the table automatically scales up and down to handle the dynamic traffic fluctuations between business hours and night hours without manual provisioning or throttling.

Step-by-Step Solution

1
Analyze the access pattern and cardinality of partition key candidates to prevent partition throttling.
Using VehicleID as the partition key provides high cardinality and distributes writes across multiple partitions, whereas a monotonically increasing Timestamp creates a hot partition bottleneck.
DynamoDB distributes data across partitions based on the partition key hash; high cardinality prevents hot partitions.
2
Evaluate the workload traffic pattern to determine the optimal capacity mode.
On-Demand capacity mode is chosen because traffic is highly dynamic and spikes during business hours.
On-Demand mode automatically scales read and write throughput instantly to handle unpredictable or sharp traffic spikes, preventing write throttling.

Key Concept

DynamoDB Partition Key Design and Capacity Modes
Question 1251Question →

A financial technology company operates a transaction validation service on AWS. The application consists of a processing tier running containerized microservices on Amazon ECS on AWS Fargate, which runs continuously 24/724/7 with a stable, predictable CPU and memory utilization. The backend database runs on Amazon RDS for PostgreSQL. The company wants to minimize its compute costs over a 11-year period. Which combination of purchasing strategies will provide the most cost-effective solution?

Show answer & explanation

Answer: Purchase a Compute Savings Plan for the Amazon ECS on AWS Fargate tasks, and purchase an Amazon RDS Reserved Instance for the database.

Answer

Purchasing a Compute Savings Plan for the Amazon ECS on AWS Fargate tasks, and purchasing an Amazon RDS Reserved Instance for the database.
The correct answer combination correctly matches the purchasing strategies to their supported services. A Compute Savings Plan is the most flexible savings plan that applies to EC2, Fargate, and Lambda workloads. Since Compute Savings Plans do not cover Amazon RDS, purchasing an Amazon RDS Reserved Instance for the database tier is the most cost-effective way to secure a commitment discount for the continuous PostgreSQL workload.

Step-by-Step Solution

1
Analyze the compute workload on AWS Fargate
Identify that the ECS on Fargate tasks run continuously 24/724/7 with stable usage, making them ideal for commitment-based discounts. Compute Savings Plans apply directly to AWS Fargate usage.
To apply commitment discounts to AWS Fargate, Compute Savings Plans are required since EC2 Instance Savings Plans do not cover serverless container execution.
2
Analyze the database workload on Amazon RDS
Identify that Amazon RDS operates 24/724/7 and is not covered by Compute Savings Plans.
Compute Savings Plans only apply to Amazon EC2, AWS Fargate, and AWS Lambda. A separate purchasing strategy is required for the database tier.
3
Select the appropriate discount model for Amazon RDS
Purchase an Amazon RDS Reserved Instance (RI) to cover the database instance.
RDS Reserved Instances provide significant discounts (up to 72%72\%) for a 11-year or 33-year commitment on predictable, continuous database workloads.

Key Concept

AWS Compute Savings Plans scope and RDS Reserved Instances compatibility
Estimated Time:1m 30s
Question 1252Question →

A healthcare provider plans to store daily database backup archives in a secondary AWS Region to support their disaster recovery strategy. The database administrator suggests using Amazon S3 Glacier Flexible Retrieval with standard retrieval options, assuming that the archived data can be restored immediately during an unexpected primary site outage. Why is this assumption incorrect?

Show answer & explanation

Answer: Standard retrievals in Amazon S3 Glacier Flexible Retrieval typically take 3 to 5 hours to complete, which introduces significant recovery delays and prevents immediate data access.

Answer

Standard retrievals in Amazon S3 Glacier Flexible Retrieval typically take 3 to 5 hours to complete, which introduces significant recovery delays and prevents immediate data access.
The correct option is correct because standard retrieval requests in Amazon S3 Glacier Flexible Retrieval typically take between 3 to 5 hours to complete. For disaster recovery scenarios that require rapid recovery, this time delay is unacceptable, meaning the assumption of immediate restoration is incorrect.

Step-by-Step Solution

1
Analyze the recovery requirements and the proposed AWS service.
The scenario asks why assuming immediate restore from Amazon S3 Glacier Flexible Retrieval with standard retrieval options is incorrect.
To evaluate the feasibility of the backup and restore solution, we must look at the retrieval latency of the selected storage class.
2
Evaluate the retrieval times of Amazon S3 Glacier Flexible Retrieval.
Amazon S3 Glacier Flexible Retrieval offers three retrieval options: Expedited (1-5 minutes), Standard (3-5 hours), and Bulk (5-12 hours).
Comparing these options reveals that the standard retrieval option does not allow for immediate restoration.
3
Identify the option that correctly states the limitation of the standard retrieval option.
The option stating that standard retrievals typically take 3 to 5 hours is correct.
This delay makes standard retrievals unsuitable for disaster recovery scenarios that require immediate, real-time data access.

Key Concept

Disaster Recovery Storage Retrieval Times
Question 1253Question →

A logistics tracking company hosts its web application on Amazon EC2 instances in an Auto Scaling group with an Amazon RDS for PostgreSQL DB instance. The company needs to design a disaster recovery (DR) strategy in a secondary AWS Region. The strategy must achieve a Recovery Point Objective (RPO) of 24 hours and a Recovery Time Objective (RTO) of 12 hours while keeping costs to a minimum.

Which combination of actions will meet these requirements at the lowest cost? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: Configure AWS Backup to schedule daily backups of the RDS DB instance and copy them to the secondary Region.; Copy the Amazon Machine Image (AMI) of the application EC2 instances to the secondary Region.

Answer

Configure AWS Backup to schedule daily database backups and copy them to the secondary Region, and copy the application server Amazon Machine Image (AMI) to the secondary Region.
To meet an RPO of 24 hours and RTO of 12 hours at the lowest cost, a Backup and Restore disaster recovery (DR) strategy is ideal. Configuring AWS Backup to schedule daily database backups and copying them to the secondary Region satisfies the 24-hour RPO. Copying the application AMI to the secondary Region ensures that compute resources can be provisioned quickly from the AMI during a disaster event to satisfy the 12-hour RTO. Both of these actions store data at rest and do not run compute or database instances continuously, minimizing costs.

Step-by-Step Solution

1
Identify the recovery requirements (RPO of 24 hours, RTO of 12 hours, minimum cost).
This indicates a Backup and Restore disaster recovery (DR) strategy is appropriate, as it is the most cost-effective and easily fits within a 12-hour window.
Backup and Restore does not require running active compute or database resources in the secondary Region, keeping idle costs at zero.
2
Select the database DR mechanism.
Configure AWS Backup to perform daily database backups and copy them to the secondary Region.
Daily database snapshots meet the 24-hour RPO and can be restored to a new RDS instance within the 12-hour RTO at minimal cost.
3
Select the compute DR mechanism.
Copy the application EC2 AMI to the secondary Region.
Having the AMI available in the secondary Region allows the Auto Scaling group to launch instances from the pre-configured image when failover is initiated, which can be done in minutes.

Key Concept

Backup and Restore is the most cost-effective disaster recovery strategy for scenarios with flexible RTO (e.g., 12-24 hours) and RPO (e.g., 24 hours), as it avoids ongoing compute and active database replica costs in the secondary region.
Question 1254Question →

A healthcare technology company hosts its core patient data processing application on AWS. The application has two main workloads:

1. A containerized backend service running on Amazon EC2 instances that processes transaction data continuously 24/7 with a predictable baseline utilization.
2. A relational database running on Amazon RDS for PostgreSQL that is also active 24/7 to support the application's transaction logging.

To meet regulatory compliance, the application must run continuously without any interruptions. The company wants to optimize its compute and database costs for these workloads.

Which two purchasing strategies should a solutions architect recommend to achieve the most cost-effective architecture? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: Purchase a Compute Savings Plan to cover the baseline usage of the Amazon EC2 instances.; Purchase Reserved Instances for the Amazon RDS DB instances.

Answer

The solutions architect should recommend purchasing a Compute Savings Plan to cover the Amazon EC2 instances, and purchasing Reserved Instances for the Amazon RDS DB instances.
To optimize costs for a 24/7 predictable EC2 compute baseline, a Compute Savings Plan offers significant discounts and flexibility. To optimize costs for the 24/7 RDS database, purchasing Reserved Instances is the appropriate strategy since Compute Savings Plans do not cover Amazon RDS.

Step-by-Step Solution

1
Analyze the compute workload requirement
The EC2 backend service runs 24/7 with a predictable baseline, making it ideal for a Savings Plan.
Savings Plans provide significant discounts compared to On-Demand rates in exchange for a commitment to a consistent amount of usage.
2
Analyze the database workload requirement
The RDS database runs 24/7, making it ideal for Reserved Instances.
Reserved Instances provide significant discounts for RDS databases that run continuously.
3
Evaluate the scope of Compute Savings Plans
Compute Savings Plans apply to EC2, Fargate, and Lambda, but do not apply to RDS databases.
RDS databases must be covered under RDS Reserved Instances, not Compute Savings Plans.

Key Concept

Compute Savings Plans apply to EC2, Fargate, and Lambda, while RDS instances require RDS Reserved Instances for cost optimization.
Estimated Time:1m 30s
Question 1255Question →

A retail company is launching a new flash sale application where customer transaction events are highly unpredictable and spiky. Each transaction must be processed asynchronously in the exact order it was received to ensure database consistency. Which configurations or services should a solutions architect select? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: Amazon SQS FIFO queues to guarantee that messages are processed in the strict order they are received; Message Group IDs to group messages that require sequential processing within the queue

Answer

Amazon SQS FIFO queues should be used to guarantee strict first-in-first-out ordering, and Message Group IDs should be configured to group related messages for sequential processing.
To process customer transaction events in strict order, Amazon SQS FIFO (First-In-First-Out) queues must be used. SQS FIFO queues ensure that the order in which messages are sent and received is strictly preserved. Additionally, Message Group IDs are required in FIFO queues to group messages that belong to a specific session or customer, allowing multiple consumers to process different groups in parallel while maintaining FIFO ordering within each group.

Step-by-Step Solution

1
Analyze the requirement for processing events in the exact order they are received.
Identify that a message queuing service with strict ordering guarantees is required.
Standard SQS queues only provide best-effort ordering, making SQS FIFO queues the correct choice for strict ordering.
2
Determine how to handle related transactions sequentially while allowing parallel processing.
Identify that Message Group IDs should be used to group related messages.
Message Group IDs ensure that messages within the same group are processed in order, while allowing messages in different groups to be processed concurrently.

Key Concept

Decoupling with ordered messaging using SQS FIFO queues and Message Group IDs.
Question 1256Question →

A smart home utility company is designing an architecture to ingest telemetry data from millions of smart meters. The telemetry readings from each individual smart meter must be processed in the exact chronological order in which they are generated. Additionally, the architecture must fan out these readings to two separate backend applications: a real-time billing service and an anomaly detection engine. Which combination of actions should the solutions architect recommend to decouple these services while preserving message ordering? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: Publish the smart meter telemetry readings to an Amazon SNS FIFO topic, using the unique smart meter identifier as the Message Group ID.; Create two separate Amazon SQS FIFO queues—one for the billing service and one for the anomaly detection engine—and subscribe both queues to the SNS FIFO topic.

Answer

The correct solution is to publish the smart meter telemetry readings to an Amazon SNS FIFO topic using the unique smart meter identifier as the Message Group ID, and to create two separate Amazon SQS FIFO queues subscribed to the SNS FIFO topic.
To achieve both decoupling (fan-out) and strict chronological ordering per device, the architecture must use Amazon SNS FIFO in combination with Amazon SQS FIFO queues. When publishing messages to the SNS FIFO topic, the unique smart meter identifier is designated as the Message Group ID. This ensures that all readings from a single device are kept in sequence. By subscribing separate SQS FIFO queues for the billing service and the anomaly detection engine to the SNS FIFO topic, each consumer application receives an independent copy of the message stream while strictly preserving the FIFO ordering within each device's message group.

Step-by-Step Solution

1
Select a message ingestion and fan-out mechanism that preserves ordering.
Amazon SNS FIFO is selected as it guarantees first-in, first-out ordering and message deduplication while allowing multiple subscribers.
Standard SNS topics do not guarantee message order, which is a key requirement of the scenario.
2
Configure the message grouping strategy.
The unique smart meter identifier is used as the Message Group ID.
This ensures that messages originating from the same physical meter are processed sequentially, while allowing parallel processing across different meters.
3
Decouple downstream consumers without losing the order guarantee.
Two SQS FIFO queues are created and subscribed to the SNS FIFO topic.
SNS FIFO topics can only fan out messages to SQS FIFO queues if end-to-end ordering needs to be maintained for the decoupled consumer services.

Key Concept

End-to-End FIFO Ordering in Decoupled Event-Driven Architectures
Question 1257Question →

A healthcare scheduling application stores doctor availability and booking details in an Amazon RDS for MySQL Multi-AZ DB instance. During peak morning hours, the system experiences a massive spike in read traffic from patients searching for open appointments, which drives the database's CPU utilization to 100% and causes query timeout errors. Write requests for booking appointments are low but require strict data consistency. Which two actions should a solutions architect take to resolve the database performance degradation?

Select all that apply

Show answer & explanation

Answer: Deploy Amazon RDS Read Replicas and configure the application to direct read-only queries to the read replica endpoints.; Create an Amazon ElastiCache for Redis cluster to cache frequently queried doctor availability schedules.

Answer

Deploy Amazon RDS Read Replicas to offload read-only traffic, and create an Amazon ElastiCache for Redis cluster to cache doctor availability schedules.
Deploying read replicas offloads read traffic from the primary database, while caching frequently read database queries using an ElastiCache Redis cluster reduces the total number of reads hitting the database entirely.

Step-by-Step Solution

1
Analyze database traffic characteristics
Identify that the bottleneck is caused by a high volume of read queries searching for availability, while write operations remain low.
This determines that scaling read capacity and implementing caching are the most effective performance optimization strategies.
2
Identify read-scaling options in RDS
Select Amazon RDS Read Replicas to handle read-only queries, rather than relying on the standby Multi-AZ instance which cannot serve reads.
Read replicas are designed specifically to scale read performance dynamically.
3
Implement a caching layer
Introduce Amazon ElastiCache for Redis to store search results for frequently queried availability schedules.
Caching avoids hitting the database altogether for repetitive queries, achieving sub-millisecond latency.

Key Concept

Scaling read capacity using RDS Read Replicas and offloading database queries via ElastiCache caching.
Question 1258Question →

A financial technology company is designing a serverless payment processing system. The system must process transactional ledger updates in the exact sequence they are received. The transaction volume is highly unpredictable, ranging from zero transactions for hours to sudden bursts of thousands of transactions per minute. Additionally, the system must run a nightly reconciliation report that processes all transaction data for the day. This report is computationally intensive and takes approximately 45 minutes to execute. Which two options should the solutions architect choose to design a highly cost-effective and automated scaling architecture? (Select two.)

Select all that apply

Show answer & explanation

Answer: Configure an Amazon SQS FIFO queue to receive the transactional ledger updates and trigger AWS Lambda functions for processing.; Run the nightly reconciliation report as a containerized task on Amazon ECS with AWS Fargate using Fargate Spot capacity providers.

Answer

Configure an Amazon SQS FIFO queue to receive the transactional ledger updates and trigger AWS Lambda functions for processing, and run the nightly reconciliation report as a containerized task on Amazon ECS with AWS Fargate using Fargate Spot capacity providers.
For the transaction updates, configuring an Amazon SQS FIFO queue ensures that messages are processed in strict chronological order, while AWS Lambda scales automatically to handle traffic spikes and costs nothing when there are no transactions. For the nightly reconciliation report, which runs for 45 minutes and is computationally intensive, Amazon ECS with AWS Fargate is ideal because Fargate only charges for resources while the container is running. Leveraging Fargate Spot capacity providers provides massive discounts, making it the most cost-effective option since the runtime exceeds AWS Lambda's 15-minute timeout.

Step-by-Step Solution

1
Analyze the ordering and scalability requirements for transactional updates.
The updates require strict sequential order and must handle highly unpredictable bursts.
Amazon SQS FIFO queues guarantee first-in, first-out ordering, and AWS Lambda scales automatically from zero to meet demand, offering cost-optimal serverless compute.
2
Analyze the execution duration and cost requirements of the nightly report.
The report runs for 45 minutes daily and is computationally intensive.
Since the runtime exceeds the 15-minute AWS Lambda timeout limit, containerized tasks on Amazon ECS with AWS Fargate must be used. Fargate Spot offers significant cost savings for fault-tolerant batch workloads.

Key Concept

Combining serverless message queues (SQS FIFO) and auto-scaling compute (Lambda and Fargate Spot) to design cost-efficient architectures based on execution duration and ordering constraints.
Question 1259Question →

An energy trading platform hosts its core transaction processing application in the us-east-1 Region. The architecture consists of an Auto Scaling group of Amazon EC2 instances behind an Application Load Balancer (ALB), and a Multi-AZ Amazon RDS for PostgreSQL DB instance. The company needs to design a disaster recovery (DR) solution in the us-west-2 Region. The solution must achieve a Recovery Time Objective (RTO) of 30 minutes and a Recovery Point Objective (RPO) of 5 minutes while minimizing ongoing running costs. Which strategy meets these requirements?

Show answer & explanation

Answer: Deploy an ALB and an Auto Scaling group in the us-west-2 Region with its desired capacity set to 0. Create an RDS for PostgreSQL cross-region read replica in us-west-2. In the event of a disaster, promote the read replica to a standalone DB instance, scale up the Auto Scaling group to its desired capacity, and update the Route 53 DNS records to point to the secondary ALB.

Answer

Deploy an ALB and an Auto Scaling group in the us-west-2 Region with its desired capacity set to 0, create an RDS read replica in the secondary region, promote the replica to standalone during disaster recovery, scale up the Auto Scaling group, and update Route 53 DNS records.
The correct strategy uses an RDS cross-region read replica to satisfy the 5-minute RPO via continuous asynchronous replication. Ongoing costs are minimized by using a Pilot Light strategy, keeping the secondary Auto Scaling group at zero capacity during normal operations. During a disaster, promoting the replica and scaling up the Auto Scaling group allows full system recovery within the 30-minute RTO.

Step-by-Step Solution

1
Set up database replication using an Amazon RDS for PostgreSQL cross-region read replica in the secondary region (us-west-2).
Database changes are replicated asynchronously with sub-second/sub-minute lag, meeting the 5-minute RPO.
Asynchronous cross-region replication is required to achieve the strict RPO without impacting the write latency of the primary database in the us-east-1 Region.
2
Deploy the application load balancer and the Auto Scaling group in the secondary region with the desired capacity set to 0.
The infrastructure is provisioned but runs at zero compute cost during normal operations, meeting the cost optimization requirement.
This implements the Pilot Light recovery pattern, which ensures infrastructure configuration is ready to scale up immediately without incurring continuous EC2 instance costs.
3
Define the disaster recovery failover workflow to promote the read replica to a standalone DB, scale up the Auto Scaling group, and update DNS records to point to the secondary ALB.
The application becomes fully functional in the secondary region within the 30-minute RTO limit.
Promoting an RDS read replica takes only a few minutes, and EC2 instances in the Auto Scaling group can boot and register with the ALB quickly, allowing recovery within the 30-minute target.

Key Concept

Using a cross-region RDS read replica combined with a Pilot Light application tier (zero-capacity Auto Scaling group) allows an architecture to meet low RTO and RPO requirements while keeping idle running costs to a minimum.
Question 1260Question →

A company hosts a real-time telemetry processing API on Amazon EC2 instances within an Auto Scaling group (ASG). The instances are located in private subnets and run behind a public-facing Application Load Balancer (ALB). The API is configured to listen on TCP port 8080. The ALB target group has a target port of 8080, but the health check port is explicitly configured to port 80. The network ACL associated with the private subnets allows inbound TCP traffic on port 8080 from the public subnets, and outbound TCP traffic on port 8080 to the public subnets. Currently, all EC2 instances are marked unhealthy by the ALB, causing the ASG to repeatedly terminate and launch new instances. Which two actions must the solutions architect take to resolve this issue and ensure the instances are marked healthy? (Select two.)

Select all that apply

Show answer & explanation

Answer: Modify the target group health check settings to use port 8080 or the traffic port.; Modify the outbound network ACL of the private subnets to allow TCP traffic to the public subnets on ephemeral ports (1024-65535).

Answer

Modify the target group health check settings to use port 8080 or the traffic port, and modify the outbound network ACL of the private subnets to allow TCP traffic to the public subnets on ephemeral ports (1024-65535).
To resolve the health check issues, two corrective configurations must be made. First, the target group's health check port must be changed to port 8080 (or the traffic port) to ensure the Application Load Balancer queries the actual port where the telemetry API is listening. Second, the outbound network ACL of the private subnets must be updated to allow traffic to ephemeral ports (1024-65535). Because network ACLs are stateless, return traffic from the EC2 instances back to the load balancer's dynamically allocated source ports will be dropped unless explicitly permitted by an outbound rule.

Step-by-Step Solution

1
Analyze the target group health check port configuration.
Identify that the health checks are directed to port 80, while the application is bound to port 8080.
Correcting the health check port to match the application port is necessary for the load balancer to receive a valid response.
2
Evaluate the network ACL rules of the private subnets hosting the instances.
Identify that the outbound network ACL only allows TCP port 8080, blocking the return traffic to the load balancer's source ephemeral ports.
Since network ACLs are stateless, return traffic must be explicitly allowed on the destination ports of the response, which are the ephemeral ports used by the ALB.
3
Apply the configuration updates to the health check settings and the outbound network ACL.
The instances successfully pass health checks and are registered as healthy by the Application Load Balancer.
This establishes complete bidirectional network communication required for health check validation.

Key Concept

Application Load Balancer health checks must target the port where the application service is listening, and stateless network ACLs require outbound rules that cover return traffic on ephemeral ports.
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