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Question 801Question →

An organization is designing a highly resilient, low-latency API gateway endpoint for a global mobile application. The backend microservices are deployed on Amazon ECS behind Application Load Balancers (ALBs) in the `us-east-1` and `eu-west-1` regions. The business requires that users are routed to the closest region under normal operating conditions. If the ECS tasks in a region fail, Route 53 must automatically route traffic away from that region. Additionally, the failover mechanism must verify that the API returns a specific JSON status payload containing \"status\": \"healthy\", which is returned by a deep health check endpoint. Which two configurations should a solutions architect implement to meet these requirements? (Select two.)

Select all that apply

Show answer & explanation

Answer: Create Route 53 HTTPS health checks with string matching configured to verify the string \"status\": \"healthy\" is present, ensuring the health check endpoint returns this payload within the first 51205{}120 bytes of the response.; Create Latency alias records in Route 53 pointing to the Application Load Balancer in each region, set Evaluate Target Health to Yes, and associate each record with the corresponding custom HTTPS health check.

Answer

The correct configurations are to create Route 53 HTTPS health checks with string matching for the specific JSON payload within the first 51205{}120 bytes, and to create Latency alias records pointing to each Application Load Balancer with Evaluate Target Health set to Yes, associated with the health checks.
The solution requires latency-based routing to ensure users are directed to the closest region under normal conditions. This is achieved by creating Latency alias records in Route 53 pointing to the Application Load Balancers (ALBs) in both regions. Setting 'Evaluate Target Health' to Yes ensures Route 53 automatically evaluates the health of the ALB and its targets. Furthermore, to verify the specific JSON response payload, a custom HTTPS health check with string matching must be associated with the records. Because Route 53 string matching only evaluates the first 51205{}120 bytes of a response body, the API status endpoint must return the required payload within this limit.

Step-by-Step Solution

1
Configure a custom Route 53 HTTPS health check with string matching.
A custom health check is created that monitors the deep health check endpoint and searches for the string \"status\": \"healthy\" within the first 51205{}120 bytes of the response body.
Route 53 string matching health checks are limited to searching the first 51205{}120 bytes of the response body, which matches the business requirement to verify the status payload.
2
Configure active-active latency-based routing with alias records and target health evaluation.
Latency alias records are created pointing to each regional Application Load Balancer with Evaluate Target Health set to Yes and associated with the custom health checks.
Alias records are required to use the Evaluate Target Health feature. Latency routing directs traffic to the closest region, and setting Evaluate Target Health to Yes ensures Route 53 shifts traffic away if the health check fails.

Key Concept

To implement active-active latency routing with deep health checking in Route 53, you must use Latency alias records (not CNAMEs) to support 'Evaluate Target Health', and configure custom HTTPS health checks with string matching that respects the 51205{}120-byte payload limit.
Question 802Question →

A retail company runs a production transaction-processing application on an Amazon RDS for MySQL DB instance. The database must be highly resilient to Availability Zone outages with a Recovery Time Objective (RTO) of less than 120 seconds. Additionally, the application requires read scaling to handle heavy reporting queries during business hours without impacting write operations on the primary database instance.

Which two database configurations should the solutions architect choose to meet these requirements? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: Deploy the Amazon RDS DB instance in a Multi-AZ deployment.; Create Amazon RDS Read Replicas and direct read traffic to the read replica endpoints.

Answer

Deploy the database in a Multi-AZ configuration to achieve high availability and low RTO, and create RDS Read Replicas to scale read performance.
To meet the requirements, the database must support automatic failover for high availability and read scaling. A Multi-AZ deployment creates a primary DB instance and a synchronous standby replica in a different Availability Zone. If the primary instance fails, RDS automatically performs a failover to the standby, achieving a low RTO. To scale read queries without affecting the primary write performance, creating RDS Read Replicas and directing reporting traffic to the read replica endpoints is the correct approach.

Step-by-Step Solution

1
Identify high availability and RTO requirements.
Determine that a Multi-AZ deployment is required to provide synchronous replication and automatic failover in under 120 seconds.
A single-AZ DB instance with read replicas does not support automatic, low-RTO failover.
2
Identify read scaling requirements.
Determine that RDS Read Replicas are needed to handle reporting queries and offload read traffic from the primary database.
The standby DB instance in a Multi-AZ DB instance configuration is passive and cannot serve read traffic.
3
Select the correct combination of configurations.
Combine a Multi-AZ deployment for failover/HA with one or more Read Replicas for read scaling.
This satisfies both the HA/failover RTO requirements and the read scalability constraints.

Key Concept

Distinguishing between RDS Multi-AZ deployments for high availability/failover and RDS Read Replicas for scaling read operations.
Question 803Question →

A ride-hailing company is experiencing performance issues with its backend application. The application requires sub-millisecond latencies when querying and updating active driver coordinates. Additionally, daily analytical reports running against the transaction log on an Amazon RDS for PostgreSQL DB instance are causing high CPU utilization and latency for online transactions. Which two database architectural decisions should the Solutions Architect implement to meet these performance requirements? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: Deploy Amazon ElastiCache for Redis to store and retrieve the real-time driver coordinates.; Create an Amazon RDS Read Replica to run the daily analytical reports instead of running them on the primary DB instance.

Answer

Deploy Amazon ElastiCache for Redis to store and retrieve real-time driver coordinates, and create an Amazon RDS Read Replica to run daily analytical reports.
Deploying Amazon ElastiCache for Redis provides sub-millisecond latencies required for driver coordinates, and creating an Amazon RDS Read Replica offloads analytical queries to prevent resource contention on the primary database.

Step-by-Step Solution

1
Analyze the latencies for coordinates queries.
The requirement is sub-millisecond latency for driver coordinates.
Relational databases cannot guarantee sub-millisecond latencies, whereas an in-memory cache like Amazon ElastiCache for Redis handles high-frequency coordinate queries within microseconds.
2
Address the analytical query performance bottleneck.
Create an RDS Read Replica.
Analytical reports generate complex read queries. Running them on a dedicated Read Replica prevents resource contention on the primary DB instance, which performs online transactions.
3
Evaluate the partitioning strategy for coordinates.
Avoid monotonically increasing keys (timestamps) for DynamoDB.
If DynamoDB were used, a timestamp key would direct all traffic to a single partition, violating the best practice of distributing traffic uniformly across partition keys.

Key Concept

Selecting and configuring high-performing database options by offloading read workloads with replicas and caching real-time data using in-memory databases.
Question 804Question →

An engineering company plans to run a tightly-coupled computational fluid dynamics (CFD) simulation. The software requires multiple Amazon EC2 instances to communicate with each other with the lowest possible network latency and high throughput.

Which EC2 placement strategy should be selected to meet this performance requirement?

Show answer & explanation

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

Answer

Configure the instances in a cluster placement group within a single Availability Zone.
The correct option is configuring the instances in a cluster placement group within a single Availability Zone. A cluster placement group is specifically designed for applications that require low network latency, high network throughput, or both. It achieves this by launching instances close together on the same physical hardware within a single Availability Zone.

Step-by-Step Solution

1
Identify the primary workload requirement.
The simulation is a tightly-coupled computational fluid dynamics workload requiring the lowest possible network latency and high network throughput for inter-node communication.
Understanding the core performance requirements allows for the selection of the correct EC2 placement strategy.
2
Evaluate the placement group strategies.
Cluster placement groups place instances physically close together on hardware in a single Availability Zone to maximize network performance, which matches the latency requirements. Spread and partition groups prioritize fault tolerance over low-latency network speeds.
Comparing different placement groups ensures the selected infrastructure configuration aligns with the application design constraints.

Key Concept

Selecting the correct EC2 placement group for low-latency, high-performance networking.
Question 805Question →

A company wants to configure an active-passive disaster recovery strategy for its web portal. The primary website is hosted behind an Application Load Balancer (ALB) in the us-east-1 Region. If the ALB becomes unhealthy, all traffic must be redirected automatically to a backup static maintenance site hosted on an Amazon S3 website endpoint in the us-west-2 Region. Which configurations must the Solutions Architect implement in Amazon Route 53 to achieve this behavior? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: Create an Alias A record for the portal domain pointing to the Application Load Balancer, configure it with a Failover routing policy as the Primary record, and enable Evaluate Target Health.; Create an Alias A record for the portal domain pointing to the Amazon S3 website endpoint, and configure it with a Failover routing policy as the Secondary record.

Answer

Configure a primary Route 53 Alias A record pointing to the Application Load Balancer with a Failover policy and 'Evaluate Target Health' enabled, and configure a secondary Route 53 Alias A record pointing to the Amazon S3 website endpoint with a Failover policy.
To set up active-passive failover to a static website on Amazon S3, you must use Route 53 Failover routing. The primary record must point to the Application Load Balancer using an Alias A record with 'Evaluate Target Health' enabled so that Route 53 can detect load balancer unhealthiness. The secondary record must be an Alias A record pointing to the S3 bucket website endpoint configured as a secondary failover target.

Step-by-Step Solution

1
Configure the primary DNS entry using an Alias record.
An A record with an Alias to the ALB is created.
Alias records are required to map the zone apex or domain name directly to AWS resources like ALBs and enable Route 53's 'Evaluate Target Health' feature.
2
Set up health check monitoring for the primary record by enabling Evaluate Target Health.
Route 53 automatically tracks the health of the ALB and its targets.
Enabling 'Evaluate Target Health' allows Route 53 to inherit the health status of the ALB without needing a custom Route 53 health check configuration.
3
Configure the secondary DNS entry using an Alias record pointing to the S3 bucket website endpoint.
A secondary A record with Failover routing is established.
This record serves as the passive target, which Route 53 will resolve only when the primary target is marked unhealthy.

Key Concept

Route 53 DNS Failover allows solutions architects to implement active-passive architectures using primary and secondary records. It requires Alias records to leverage target health evaluation for AWS resources.
Question 806Question →

A company runs a web application that stores user account transaction data in an Amazon RDS for PostgreSQL database and session data in an Amazon DynamoDB table. Users are experiencing slow page load times. A review reveals that the RDS database is overwhelmed with read-only reporting queries, and the DynamoDB table is facing write throttling due to uneven partition distribution. Which two database configurations should a solutions architect implement to resolve these performance issues? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: Create Amazon RDS read replicas to handle the read-only reporting queries.; Use a high-cardinality, randomized attribute as the Amazon DynamoDB partition key to distribute write traffic.

Answer

To resolve the performance issues, the solutions architect should create RDS read replicas to handle the read-only reporting queries, and use a high-cardinality, randomized attribute as the DynamoDB partition key to distribute write traffic.
Creating RDS read replicas allows the reporting queries to be directed away from the primary database, lowering CPU utilization on the writer instance. Implementing a high-cardinality partition key for DynamoDB ensures that write requests are spread evenly across multiple physical partitions, which eliminates write throttling.

Step-by-Step Solution

1
Analyze the database performance bottleneck for the Amazon RDS for PostgreSQL database.
The primary database instance is overloaded by read-only reporting queries.
To resolve read-heavy workload issues, read-only queries should be offloaded to dedicated read replicas.
2
Analyze the write throttling issue on the Amazon DynamoDB table.
The write traffic is unevenly distributed, causing a partition bottleneck.
To prevent write throttling, a high-cardinality key should be used instead of a monotonically increasing value to distribute writes evenly across partitions.

Key Concept

Scaling read workloads using RDS read replicas and designing DynamoDB partition keys to avoid partition throttling.
Question 807Question →

A solutions architect is optimizing a global news website. The application's static assets, such as CSS files and logos, are served from an Application Load Balancer (ALB) origin through an Amazon CloudFront distribution. During a performance review, the architect notices that the ALB continues to receive a high volume of requests for these static assets, causing unnecessary origin load. Investigation reveals that the CloudFront cache behavior for these assets has its Minimum TTL, Maximum TTL, and Default TTL all set to 0 seconds. Which configuration change should the solutions architect make to reduce the load on the origin ALB?

Show answer & explanation

Answer: Increase the Minimum TTL and Default TTL values in the cache behavior to allow CloudFront to cache the static assets at edge locations.

Answer

Increase the Minimum TTL and Default TTL values in the cache behavior to allow CloudFront to cache the static assets at edge locations.
The correct option identifies that increasing the Minimum TTL and Default TTL settings enables CloudFront to cache static files. When these settings are configured with positive values, CloudFront stores the files at edge locations and serves them directly to users, eliminating unnecessary requests to the origin Application Load Balancer.

Step-by-Step Solution

1
Analyze the current configuration and issue.
The CloudFront cache behavior has TTL values set to 0 seconds, which forces CloudFront to forward all requests to the Application Load Balancer (ALB) origin without caching.
Understanding why the origin is overloaded is the first step to resolving caching issues.
2
Determine the appropriate configuration to enable caching.
By increasing the Minimum TTL and Default TTL settings to positive values, CloudFront is instructed to cache the static assets at Edge locations.
Static assets like CSS files and logos do not change frequently and are ideal candidates for caching at the edge.
3
Apply the TTL change in the cache behavior.
Subsequent requests are served directly from CloudFront's edge cache, reducing origin request volume and lowering ALB load.
This implements the optimal caching architecture for static files.

Key Concept

Configuring Amazon CloudFront Time-to-Live (TTL) values to cache static content at edge locations and reduce load on origin servers.
Estimated Time:50s
Question 808Question →

A financial technology startup logs daily micro-transaction API audit payloads. The generated files average 50 KB50\text{ KB} in size and are stored in an Amazon S3 Standard bucket. The files are frequently accessed during the first 15 days15\text{ days} for compliance validation. From day 1616 to day 3535, the access rate drops significantly, but the files must still be accessible within milliseconds if requested. After 35 days35\text{ days}, the files are rarely accessed but must be securely archived for 3 years3\text{ years} to meet regulatory requirements, with retrieval times of up to 5 hours5\text{ hours} being acceptable. Which S3 lifecycle and storage tiering strategy is the most cost-effective for this scenario?

Show answer & explanation

Answer: Store the audit logs in Amazon S3 Standard, and configure a lifecycle policy to transition the objects directly to Amazon S3 Glacier Flexible Retrieval after 35 days35\text{ days}.

Answer

Storing the audit logs in Amazon S3 Standard and transitioning them directly to Amazon S3 Glacier Flexible Retrieval after 35 days35\text{ days}.
The correct strategy keeps the files in Amazon S3 Standard for the entire 35 days35\text{ days} and transitions them directly to Amazon S3 Glacier Flexible Retrieval. Since the files average 50 KB50\text{ KB}, they are below the 128 KB128\text{ KB} minimum billable size limit for S3 Standard-IA and S3 Glacier Instant Retrieval. Storing them in Standard-IA or Glacier Instant Retrieval would lead to paying for 128 KB128\text{ KB} per object. Additionally, because the intermediate access period lasts only 20 days20\text{ days} (day 1616 to 3535), transitioning them to Standard-IA (which has a 3030-day minimum duration) or Glacier Instant Retrieval (which has a 9090-day minimum duration) before archiving them would result in early deletion/transition penalties. S3 Glacier Flexible Retrieval has a 40 KB40\text{ KB} minimum billable size limit and a 9090-day minimum storage duration, both of which are satisfied by the 50 KB50\text{ KB} files and the 33-year retention requirement, making the direct transition the most cost-effective choice.

Step-by-Step Solution

1
Analyze the file size constraint against S3 storage class billing thresholds.
The files average 50 KB50\text{ KB}. S3 Standard-IA and S3 Glacier Instant Retrieval enforce a minimum billable object size of 128 KB128\text{ KB}, which would more than double the billing volume. Keeping files in S3 Standard avoids this penalty, and S3 Glacier Flexible Retrieval has a lower minimum limit of 40 KB40\text{ KB}, which accommodates the 50 KB50\text{ KB} files without a size penalty.
Choosing storage tiers that penalize small objects will increase overall costs instead of optimizing them.
2
Evaluate the transition timelines against minimum storage duration rules.
The files need millisecond access for only 20 days20\text{ days} (day 1616 to 3535) before archiving. Transitioning them to S3 Standard-IA or S3 Glacier Instant Retrieval for this short window triggers early transition charges due to their respective 3030-day and 9090-day minimum storage duration requirements.
Storage duration penalties must be computed to prevent unexpected charges during short-lived transitions.
3
Assess the suitability of S3 Intelligent-Tiering for small files.
S3 Intelligent-Tiering does not perform auto-tiering for files under 128 KB128\text{ KB}, meaning these files will never transition to cheaper tiers and will always incur S3 Standard rates.
Ensures automated tiering features are not misapplied to workloads containing small files.
4
Formulate the optimal storage tiering pathway.
Retain the files in S3 Standard (no size or duration limits) for the entire 35 days35\text{ days}, then transition directly to S3 Glacier Flexible Retrieval (where the 9090-day minimum duration is easily met by the 33-year retention requirement).
This direct transition path avoids both the 128 KB128\text{ KB} size penalty and short-term duration transition penalties.

Key Concept

Cost optimization of S3 storage lifecycles requires analyzing both object size thresholds and minimum storage durations to avoid billing penalties.
Question 809Question →

A financial services company is designing a cost-optimization strategy for its risk analysis platform. The platform consists of two main compute workloads: a containerized orchestration API running continuously on AWS Fargate, and a series of memory-intensive risk simulation workers running on Amazon EC2. The simulation workers are stateless, run in parallel for up to 44 hours at a time, and can be safely interrupted and restarted. The company also runs its primary database on Amazon RDS for PostgreSQL. The company wants to minimize compute costs over the next 33 years.

Which combination of purchasing strategies should a solutions architect recommend to meet these requirements most cost-effectively? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: Commit to a 33-year Compute Savings Plan to cover the baseline usage of the AWS Fargate API orchestration service.; Configure the risk-simulation worker workloads to run on Amazon EC2 Spot Instances.

Answer

To minimize compute costs, the solutions architect should recommend committing to a 33-year Compute Savings Plan for the baseline usage of the AWS Fargate API orchestration service, and configuring the risk-simulation worker workloads to run on Amazon EC2 Spot Instances.
The correct strategy combines a 33-year Compute Savings Plan to cover the continuous, steady-state baseline of the containerized API running on AWS Fargate, and utilizes Amazon EC2 Spot Instances for the risk-simulation workers. Since the simulation workers are stateless, parallel, and can tolerate interruptions, Spot Instances provide the most cost-effective model, offering up to 90% savings. Compute Savings Plans are ideal for Fargate as they automatically apply across Fargate deployments with a long-term commitment.

Step-by-Step Solution

1
Analyze the operational and architectural characteristics of the workloads.
The Fargate API orchestration service runs continuously (24/724/7), representing a steady-state compute pattern. The risk-simulation workers are stateless, parallel, fault-tolerant, and run for up to 44 hours at a time. The database runs on Amazon RDS.
Identifying workload patterns is the first step in matching them with correct AWS pricing models.
2
Select the optimal purchasing strategy for the steady-state containerized workload.
A Compute Savings Plan is selected for the AWS Fargate API because it provides significant discounts (up to 66%) for a 33-year commitment and automatically applies to Fargate container usage.
Savings Plans offer the best cost-reduction mechanism for predictable, long-term containerized workloads.
3
Select the optimal purchasing strategy for the fault-tolerant batch workloads.
Amazon EC2 Spot Instances are selected for the simulation workers because they offer up to 90% savings over On-Demand and match the stateless, interruptible nature of the 44-hour batch jobs.
Spot Instances provide the highest discount rate for compute resources that do not require high availability guarantees.
4
Evaluate and discard options that violate service limits or purchasing plan scopes.
AWS Lambda is excluded due to the 1515-minute timeout limit. A Compute Savings Plan cannot be applied to Amazon RDS. committing to EC2 Instance Savings Plans for spiky, intermittent compute is cost-ineffective compared to Spot Instances.
Ensures the recommended solution is both architecturally viable and financially optimal.

Key Concept

Matching AWS compute purchasing models (Savings Plans, Spot Instances) to distinct workload patterns (steady-state vs. stateless batch compute) while recognizing structural service limits (Lambda timeout) and plan scope constraints (RDS exclusion).
Question 810Question →

A company operates a high-performance web application that runs on a fleet of Amazon EC2 instances distributed across multiple Availability Zones. The instances require shared access to a common directory to read and write media assets concurrently with sub-millisecond latency. The storage solution must scale automatically as data volume increases without requiring manual provisioning. Which storage solution should a solutions architect recommend?

Show answer & explanation

Answer: Create an Amazon Elastic File System (Amazon EFS) file system and mount it on the EC2 instances.

Answer

Create an Amazon Elastic File System (Amazon EFS) file system and mount it on the EC2 instances.
The correct answer is to create an Amazon EFS file system and mount it on the EC2 instances. Amazon EFS provides serverless, fully managed elastic file storage that supports concurrent read and write access from multiple EC2 instances across multiple Availability Zones using the NFSv4 protocol, meeting the sub-millisecond latency and automatic scaling requirements.

Step-by-Step Solution

1
Analyze the application requirements: shared directory access, concurrent read and write operations, distribution across multiple Availability Zones, auto-scaling capability, and low latency.
The solution must support standard file protocol access (POSIX compliant) and multi-AZ concurrent mounts.
This filters out block storage solutions like standard EBS volumes that are single-AZ or single-instance restricted.
2
Evaluate Amazon EFS against the requirements.
Amazon EFS natively supports the Network File System (NFS) protocol, allows concurrent mounts from multiple AZs, scales storage automatically, and offers sub-millisecond latencies.
EFS fits the performance and scalability criteria perfectly.
3
Validate the alternative options to confirm their limitations.
EBS gp3 cannot be shared. EBS io2 Multi-Attach is restricted to a single AZ and requires specialized cluster software. Amazon S3 mounted via fuse lacks POSIX locks and does not meet sub-millisecond latency performance targets.
This confirms EFS is the correct and only viable architectural choice.

Key Concept

Shared file storage using Amazon Elastic File System (EFS) for multi-AZ EC2 fleets
Estimated Time:1m 30s
Question 811Question →

A company hosts a production application on AWS that uses Amazon EC2 instances for web servers and Amazon RDS for its relational database. Both services run continuously throughout the year. The company wants to reduce costs by purchasing a Compute Savings Plan. Which of the following statements is true regarding how this purchasing strategy will affect their billing?

Show answer & explanation

Answer: The Compute Savings Plan will apply discounts to the Amazon EC2 instances, but it will not apply any discounts to the Amazon RDS database.

Answer

The Compute Savings Plan will apply discounts to the Amazon EC2 instances, but it will not apply any discounts to the Amazon RDS database.
The correct option is that the Compute Savings Plan applies discounts to the Amazon EC2 instances but does not apply any discounts to the Amazon RDS database. This is because Compute Savings Plans cover EC2, AWS Fargate, and AWS Lambda usage, but do not extend to database services like Amazon RDS.

Step-by-Step Solution

1
Identify the services included in the company's architecture.
The architecture consists of Amazon EC2 instances and an Amazon RDS database.
To apply the correct purchasing model, we need to know which AWS services are in use.
2
Determine the coverage scope of a Compute Savings Plan.
Compute Savings Plans apply to EC2 instances (regardless of family, size, AZ, region, OS, or tenancy), AWS Fargate, and AWS Lambda.
Understanding what services are eligible for Savings Plans helps identify which part of the infrastructure will receive the discount.
3
Evaluate the eligibility of Amazon RDS for Compute Savings Plans.
Amazon RDS is a database service and is not covered by Compute Savings Plans. It requires RDS Reserved Instances (RIs) for commitment-based discounts.
Identifying the limitations of Compute Savings Plans ensures that the database is excluded from the Savings Plan discount.

Key Concept

Compute Savings Plans apply to EC2, Fargate, and Lambda, but do not cover database services like Amazon RDS.
Estimated Time:45s
Question 812Question →

A fintech enterprise hosts a containerized loan processing platform on Amazon ECS across three Availability Zones. The platform generates and modifies loan agreements that must be concurrently accessible by multiple containers in an active-active configuration. The platform's disaster recovery SLA requires a Recovery Point Objective (RPO) of 44 hours and a Recovery Time Objective (RTO) of 11 hour. The storage solution must be highly resilient, durable, and support automatic failover across all three Availability Zones. Which combination of storage and backup configurations should a solutions architect implement to meet these requirements? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: Configure an Amazon EFS file system using the Regional storage class, and mount it on the Amazon ECS tasks across all three Availability Zones.; Create an AWS Backup plan with a backup rule that runs every 44 hours, backing up the filesystem to a backup vault.

Answer

The correct configurations are mounting a Regional Amazon EFS file system on the ECS tasks and implementing an AWS Backup plan with a 44-hour schedule.
Mounting a Regional Amazon EFS file system provides concurrent, active-active file access across multiple Availability Zones, ensuring high availability and durability. Setting up AWS Backup to run every 44 hours ensures that recovery points are created frequently enough to satisfy the 44-hour RPO, and restores from AWS Backup can be completed well within the 11-hour RTO.

Step-by-Step Solution

1
Analyze shared storage and concurrency requirements across multiple Availability Zones.
Amazon EFS is selected because it supports active-active concurrent file access across multiple AZs, unlike Amazon EBS which is restricted to a single AZ or lacks multi-mount capabilities across AZs.
This establishes the high availability foundation required by the containerized ECS application.
2
Evaluate the RPO requirement of 44 hours.
AWS Backup is configured to take backups of the EFS filesystem every 44 hours.
This guarantees that the maximum data loss in a disaster scenario will not exceed the 44-hour threshold.
3
Evaluate the RTO requirement of 11 hour.
Confirming EFS restores via AWS Backup are fast enough to meet the 11-hour window, while rejecting Glacier Standard retrieval which takes 33 to 55 hours.
This ensures the recovery time remains within the SLA limits.

Key Concept

Designing highly available, multi-AZ shared file systems using Amazon EFS coupled with AWS Backup to meet specific RPO and RTO compliance metrics.
Question 813Question →

An enterprise runs a data-processing pipeline on Amazon EC2 instances located in private subnets across three Availability Zones in a VPC. The instances upload approximately 80 TB80\text{ TB} of raw data monthly to an Amazon S3 bucket in the same AWS Region. In addition, the pipeline replicates 15 TB15\text{ TB} of processed data monthly to another VPC within the same Region for analytics, and retrieves 5 TB5\text{ TB} of metadata monthly from an on-premises database via a backup AWS Site-to-Site VPN connection. The VPC also has an active 1 Gbps1\text{ Gbps} AWS Direct Connect connection currently used only for administrative traffic. The S3 traffic currently routes through NAT Gateways, and inter-VPC replication goes through an AWS Transit Gateway. Which combination of actions will reduce data transfer and processing costs the most?

Show answer & explanation

Answer: Create a gateway VPC endpoint for Amazon S3 in the VPC. Establish a VPC peering connection between the two VPCs and update the route tables to route the replication traffic directly. Update the routing configuration to send the on-premises metadata traffic over the AWS Direct Connect connection instead of the Site-to-Site VPN.

Answer

Create a gateway VPC endpoint for Amazon S3, establish a VPC peering connection for inter-VPC replication, and route the on-premises metadata traffic over the existing AWS Direct Connect connection.
The correct solution optimizes all three network paths for cost. First, routing the S3 uploads through a Gateway VPC Endpoint removes the high processing fees associated with NAT Gateways. Second, establishing VPC Peering instead of using Transit Gateway removes the processing fees per GB of data transferred between VPCs. Third, migrating the on-premises database traffic from the Site-to-Site VPN to the existing Direct Connect connection takes advantage of lower data transfer out fees on Direct Connect.

Step-by-Step Solution

1
Analyze the S3 data transfer cost path.
Transitioning the 80 TB/month S3 upload from NAT Gateways to a Gateway VPC Endpoint removes the 0.045/GBNATGatewayprocessingfee,reducingcostsby0.045/GB NAT Gateway processing fee, reducing costs by 3,600/month.
Gateway VPC Endpoints for S3 are free and do not incur processing or hourly fees.
2
Analyze inter-VPC replication cost path.
Transitioning the 15 TB/month inter-VPC replication from AWS Transit Gateway to a VPC Peering connection removes the Transit Gateway processing fee of 0.02/GB,saving0.02/GB, saving 300/month.
VPC Peering does not charge processing fees, unlike AWS Transit Gateway which charges per GB processed.
3
Analyze on-premises metadata retrieval cost path.
Routing the 5 TB/month metadata transfer over the existing AWS Direct Connect connection instead of the Site-to-Site VPN (which routes over the public internet) utilizes cheaper Direct Connect data transfer out pricing.
AWS Direct Connect data transfer out fees are lower than standard Internet/VPN egress fees, and utilizing the existing connection maximizes its value.

Key Concept

Data Transfer and Network Routing Cost Optimization
Question 814Question →

A genomic research institute runs weekly analysis pipelines that generate two types of files stored in a single Amazon S3 bucket:

- Raw genomic sequence files: These files average 250 MB250\text{ MB} in size. They are processed immediately upon upload. After the first 10 days10\text{ days} of processing, they are rarely accessed, but when requested, they must be retrieved within 5 hours5\text{ hours}. These files must be retained for a total of 120 days120\text{ days}.
- Daily analysis logs: These files average 15 KB15\text{ KB} in size. They are accessed frequently during the first 30 days30\text{ days}, after which they are accessed only occasionally for audit purposes. The logs must be retained for a total of 90 days90\text{ days}.

Which TWO actions should a solutions architect recommend to store these files in the most cost-effective manner?

Select all that apply

Show answer & explanation

Answer: Transition the raw genomic sequence files from S3 Standard to S3 Glacier Flexible Retrieval after 10 days10\text{ days} using an S3 Lifecycle policy.; Retain the daily analysis logs in S3 Standard for the entire 90 days90\text{ days}, rather than transitioning them to S3 Standard-IA.

Answer

The solutions architect should recommend transitioning the raw genomic sequence files from S3 Standard to S3 Glacier Flexible Retrieval after 10 days10\text{ days}, and retaining the daily analysis logs in S3 Standard for the entire 90 days90\text{ days} lifecycle.
The correct strategy transitions the large raw genomic sequence files to S3 Glacier Flexible Retrieval after 10 days10\text{ days} because it satisfies the 55-hour retrieval window at a lower cost than S3 Glacier Instant Retrieval and exceeds the 9090-day minimum storage duration constraint. It also retains the small daily analysis logs in S3 Standard because transitioning files smaller than 128 KB128\text{ KB} to S3 Standard-IA results in paying for the minimum 128 KB128\text{ KB} storage limit, which is less cost-effective than keeping them in S3 Standard.

Step-by-Step Solution

1
Analyze the access pattern and size of the raw genomic sequence files.
The files are large (250 MB250\text{ MB}) and require retrieval within 5 hours5\text{ hours} after 10 days10\text{ days} of active use. They must be kept for 120 days120\text{ days} total.
This helps select the most cost-effective archive tier that meets the 55-hour retrieval window without violating minimum storage duration rules.
2
Compare S3 storage classes for the genomic sequence files.
S3 Glacier Flexible Retrieval supports 3−53-5 hour retrievals, has a 9090-day minimum duration, and has a very low storage cost. Storing them in Glacier Flexible Retrieval for 110 days110\text{ days} meets the 120120-day total retention and avoids early deletion charges.
Choosing Glacier Flexible Retrieval over Glacier Instant Retrieval or Glacier Deep Archive minimizes costs while adhering to retrieval and retention constraints.
3
Analyze the access pattern and size of the daily analysis logs.
The files are very small (15 KB15\text{ KB}), accessed frequently for 30 days30\text{ days}, and kept for 90 days90\text{ days} total.
Small file sizes require careful consideration of the S3 Standard-IA 128 KB128\text{ KB} minimum billing size constraint.
4
Evaluate the cost impact of transitioning the daily analysis logs to S3 Standard-IA.
Because S3 Standard-IA bills a minimum of 128 KB128\text{ KB} per object, transitioning 15 KB15\text{ KB} files would result in paying for 128 KB128\text{ KB} of storage, which is more expensive than keeping them in S3 Standard for the entire 90 days90\text{ days}.
Determining that keeping the files in S3 Standard is the most cost-effective choice for small objects.

Key Concept

Cost optimization in S3 requires evaluating both object sizes (to avoid the 128 KB128\text{ KB} minimum billing size penalty of S3 Standard-IA) and storage durations (to avoid minimum storage duration penalties like the 3030-day minimum for S3 Standard-IA or 9090-day minimum for S3 Glacier Flexible Retrieval).
Question 815Question →

A financial technology enterprise runs a distributed transaction clearing simulation on AWS that requires high-throughput and sub-millisecond node-to-node latency for parallel processing. The workload runs on a fleet of compute-optimized EC2 instances. An internal Application Load Balancer (ALB) routes traffic to these instances. The clearing application listens and processes requests on TCP port 8443, but the target group's health check is left configured to the default HTTP port (80).

During testing, the solutions architect observes two major issues:
1. The load balancer marks all target instances as unhealthy, causing connection failures.
2. The processing nodes experience high network latency during synchronization phases, which limits the platform's overall throughput.

Which combination of actions will resolve both of these issues?

Show answer & explanation

Answer: Configure the target group to perform health checks on port 8443. Launch the EC2 instances in a cluster placement group within a single Availability Zone.

Answer

Configure the target group to perform health checks on port 8443, and launch the EC2 instances in a cluster placement group within a single Availability Zone.
The correct configuration involves modifying the target group's health check port to 8443, which aligns with the port where the backend transaction clearing daemon is listening. This allows the load balancer to successfully complete health checks and mark the instances as healthy. Additionally, placing the EC2 instances in a cluster placement group within a single Availability Zone ensures the instances are placed close together on physical hardware, providing the low latency and high network throughput required for tightly coupled processing.

Step-by-Step Solution

1
Identify the port mismatch in the target group health check configuration.
Determine that the ALB is sending health check requests to port 80, whereas the clearing application runs on port 8443.
To ensure the ALB can correctly monitor the health of the application, the health check port must match the port where the backend service is listening.
2
Update the target group health check port settings.
Configure the target group health checks to query port 8443 instead of the default port.
This allows the load balancer to receive successful health check responses and mark the target instances as healthy.
3
Analyze the node-to-node latency requirements.
Identify that the application requires sub-millisecond node-to-node latency for parallel transaction clearing.
Tightly coupled distributed applications need a specialized placement group strategy to minimize physical distance and network hops between hosts.
4
Select and configure the appropriate EC2 placement group.
Deploy the EC2 instances within a cluster placement group in a single Availability Zone.
A cluster placement group packages instances close together inside the same Availability Zone, enabling low-latency, high-throughput network performance.

Key Concept

Optimizing compute performance and resolving load balancer target health check issues by aligning application ports and using EC2 cluster placement groups.
Question 816Question →

A company runs a global API platform across three AWS Regions: us-east-1, eu-west-1, and ap-southeast-2. Each region has an Application Load Balancer (ALB) routing traffic to Amazon EC2 instances. To optimize performance, the company uses Amazon Route 53 Latency routing with 'Evaluate Target Health' enabled on the alias records. During a disaster recovery test, the database in us-east-1 is powered down. The EC2 instances in us-east-1 remain running but return HTTP 500 Internal Server Error to all API clients because they cannot access the database. However, Route 53 continues to route client traffic to the us-east-1 ALB. Which configuration change will resolve this issue and ensure that Route 53 fails over to the next closest region?

Show answer & explanation

Answer: Configure the Application Load Balancer's target group health check to query a deep health check endpoint that validates database connectivity rather than a static resource.

Answer

Configure the Application Load Balancer's target group health check to query a deep health check endpoint that validates database connectivity rather than a static resource.
The correct answer is to configure the Application Load Balancer's target group health check to query a deep health check endpoint that validates database connectivity. When Route 53's Evaluate Target Health is enabled on an alias record pointing to an Application Load Balancer, Route 53 relies on the health status of the registered targets in the ALB's target groups. If the targets are configured to verify health using a static resource, they will continue to report as healthy even if the database is offline. By changing the health check path to a deep health check endpoint that verifies backend database connectivity, the targets will be marked unhealthy when the database fails, causing Route 53 to failover traffic to the next closest region.

Step-by-Step Solution

1
Analyze the relationship between Route 53 'Evaluate Target Health' and the Application Load Balancer (ALB).
Identify that Route 53 determines the health of the ALB based on the health checks of its target group instances.
To find why Route 53 failed to detect the outage, we must trace how Route 53 gets health state data.
2
Evaluate the impact of the database outage on the existing target group health check configuration.
Determine that the targets are returning healthy status because the health check is hitting a static resource, ignoring the database status.
This explains why the EC2 instances are marked healthy by the ALB despite returning HTTP 500 to clients.
3
Formulate the correction to the target group health check.
Point the health check path to a deep health check endpoint that verifies database connection.
When the database goes down, this deep endpoint will return an unhealthy status, causing the target group to mark targets unhealthy, which prompts Route 53 to route traffic to the next closest region.

Key Concept

Route 53 routing policies evaluate target health based on the configured health checks of the target endpoint. For Application Load Balancers, this health state depends directly on the ALB target group's health checks. If target groups query a shallow endpoint (e.g. static file), Route 53 will remain unaware of database-level outages.
Question 817Question →

A smart home energy management company runs an analytical application on Amazon EC2 instances in a private subnet. The application downloads hourly aggregated consumption logs (average size 15 MB15\text{ MB} per file) from an Amazon S3 Standard bucket. The logs are analyzed frequently during the first 3535 days. After 3535 days, the logs are rarely accessed, but must be available for immediate retrieval during compliance audits for another 6060 days. After a total of 9595 days, the logs are no longer needed and can be deleted.

Which TWO actions should a solutions architect take to optimize storage and data transfer costs for this workload? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: Configure an S3 Lifecycle rule to transition the log files to Amazon S3 Standard-Infrequent Access (S3 Standard-IA) 3535 days after creation.; Create a Gateway VPC Endpoint for Amazon S3 in the VPC and associate it with the route tables of the private subnet.

Answer

Configure an S3 Lifecycle rule to transition the log files to Amazon S3 Standard-IA 3535 days after creation, and create a Gateway VPC Endpoint for Amazon S3 in the VPC associated with the private subnet's route tables.
The correct options are configuring the S3 Standard-IA transition at 3535 days and creating a Gateway VPC Endpoint. Standard-IA is ideal because the logs are rarely accessed after 3535 days, require immediate (millisecond) retrieval, and are stored in Standard-IA for 6060 days (which exceeds the 3030-day minimum). A Gateway VPC Endpoint is free and avoids the data processing fees of a NAT Gateway.

Step-by-Step Solution

1
Analyze storage access pattern, duration requirements, and file sizes.
The files are 15 MB15\text{ MB} (above the 128 KB128\text{ KB} S3 Standard-IA threshold), frequently accessed for 3535 days, then rarely accessed but require immediate retrieval for another 6060 days, and are deleted after 9595 days.
This determines that S3 Standard-IA is the correct target tier starting from day 3535 because it supports millisecond access and the files remain there for 6060 days, which is above the 3030-day minimum storage duration.
2
Evaluate network access path for private EC2 instances downloading from S3.
Data transfers from S3 through a NAT Gateway incur data processing fees, whereas a Gateway VPC Endpoint provides free, private connectivity.
This establishes that a Gateway VPC Endpoint is required to optimize data transfer costs.

Key Concept

Amazon S3 Standard-IA storage tiering constraints and Gateway VPC Endpoints for S3 traffic optimization.
Question 818Question →

A company hosts a global product search catalog API on Amazon API Gateway. The API invokes AWS Lambda functions to query a highly read-heavy Amazon DynamoDB table. During promotional events, search latency spikes significantly due to redundant queries for the same product categories, leading to read throttling on the database. The solutions architect must implement a caching solution that reduces end-to-end latency to under 50 milliseconds for repeat queries, maintains cost efficiency, and ensures catalog updates are visible globally within 5 minutes.

Which two configuration changes should the solutions architect recommend to satisfy these requirements? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: Enable API Gateway caching for the production stage, configure the cache keys based on search query string parameters, and set the Time-to-Live (TTL) to 300 seconds.; Deploy an Amazon DynamoDB Accelerator (DAX) cluster to cache database read operations, and modify the Lambda functions to use the DAX client SDK instead of the standard DynamoDB client.

Answer

Enabling API Gateway stage caching with query string parameter cache keys and a 300-second TTL, combined with deploying an Amazon DynamoDB Accelerator (DAX) cluster using the DAX SDK client.
Enabling caching at the API Gateway stage using the search query string parameters as cache keys allows identical user requests to be served directly from the API Gateway cache. This minimizes end-to-end response times to milliseconds and prevents backend Lambda invocations. The 300-second TTL aligns with the requirement that catalog updates are visible within 5 minutes. For API cache misses, deploying an Amazon DynamoDB Accelerator (DAX) cluster ensures that database read requests are served with microsecond latency, preventing DynamoDB read throttling and ensuring overall application performance.

Step-by-Step Solution

1
Analyze latency and database load requirements.
Identified the need to cache responses at the edge/API Gateway layer to minimize latency (under 50 ms) and to cache database queries to prevent throttling on DynamoDB.
This establishes a multi-tier caching strategy that offloads traffic before it hits compute and database layers.
2
Evaluate and configure API Gateway caching.
Enabling API Gateway caching with a 300-second (5 minutes) TTL caches GET requests globally, reducing both Lambda execution count and database reads.
API Gateway caching reduces end-to-end response times to milliseconds and satisfies the 5-minute global cache propagation requirement.
3
Evaluate and configure database caching.
Deploying Amazon DynamoDB Accelerator (DAX) caches read requests from the Lambda function, responding in microseconds for queries that miss the API Gateway cache.
DAX acts as a write-through cache that automatically manages database invalidation, avoiding the complexity of custom cache sync logic while protecting DynamoDB from throttling.

Key Concept

Multi-tier caching utilizing API Gateway stage caching and Amazon DynamoDB Accelerator (DAX) to optimize response times and protect downstream database resources.
Question 819Question →

A logistics company is designing an asset tracking system to ingest real-time location telemetry from a fleet of 50,00050,000 delivery vehicles. The system must support a write volume that is highly unpredictable and spiky, peaking at 20,00020,000 writes per second. Each telemetry message contains a timestamp, a unique vehicle identifier, and coordinate data. Lookups for the latest vehicle locations must achieve sub-millisecond latency. Which database design and configuration meets these performance requirements?

Show answer & explanation

Answer: Configure an Amazon DynamoDB table in On-Demand capacity mode using a partition key that combines the vehicle identifier and a date string (e.g., `VehicleID_YYYY-MM-DD`). Enable Amazon DynamoDB Accelerator (DAX) to cache read queries.

Answer

Configure an Amazon DynamoDB table in On-Demand capacity mode using a partition key that combines the vehicle identifier and a date string (e.g., `VehicleID_YYYY-MM-DD`), and enable Amazon DynamoDB Accelerator (DAX) to cache read queries.
The correct answer combines a high-cardinality partition key (`VehicleID_YYYY-MM-DD`) to distribute write operations evenly across partitions, DynamoDB On-Demand capacity mode to automatically and instantly scale to accommodate sudden and unpredictable write spikes, and Amazon DynamoDB Accelerator (DAX) to provide the required sub-millisecond read latency.

Step-by-Step Solution

1
Analyze the workload characteristics, specifically the highly unpredictable and spiky write traffic peaking at 20,00020,000 writes per second, and the need for sub-millisecond read latency.
Identify that the database must scale instantly to handle write spikes without throttling, and requires an in-memory caching layer for sub-millisecond reads.
Traditional provisioned database resources or standard RDS clusters cannot scale instantly or provide sub-millisecond read latencies without caching.
2
Determine the optimal database partition key design to prevent hot partitions.
Select a high-cardinality partition key like a combination of `VehicleID` and a date string (`VehicleID_YYYY-MM-DD`) instead of a sequential timestamp or static date.
Distributing the writes across partitions prevents write throttling on a single partition.
3
Determine the database capacity mode and read caching mechanism.
Select DynamoDB On-Demand capacity mode to handle unpredictable write traffic spikes, and deploy DynamoDB Accelerator (DAX) for sub-millisecond read caching.
On-Demand mode accommodates sudden traffic spikes immediately, and DAX delivers microsecond read response times.

Key Concept

Designing high-performing, scalable DynamoDB tables with appropriate partition keys, capacity modes, and caching to avoid bottlenecks and deliver low latency.
Question 820Question →

A genomics research institute runs sequencing pipelines on AWS and stores its output files in an Amazon S3 bucket. The data consists of two distinct categories:

* Alignment files (`.bam`): These files average `250250 MB` in size. They are accessed frequently during the first `1010 days` of a run, after which they are rarely accessed. They must be kept for exactly `4545 days` for quality control and then deleted.
* Variant call files (`.vcf`): These files average `6060 KB` in size. They are accessed less than once a year, but they must be retained permanently for compliance and must be available within minutes when requested.

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

Select all that apply

Show answer & explanation

Answer: Create an S3 Lifecycle rule to transition the alignment files to S3 Standard-Infrequent Access (S3 Standard-IA) after `1010 days`, and expire the files after `4545 days`; Create an S3 Lifecycle rule to transition the variant call files to S3 Glacier Flexible Retrieval after `3030 days`

Answer

The most cost-effective actions are: transition the alignment files to S3 Standard-IA after `1010 days` and expire them after `4545 days`; and transition the variant call files to S3 Glacier Flexible Retrieval after `3030 days`.
Transitioning the alignment files to S3 Standard-IA after `1010 days` and deleting them after `4545 days` is optimal because the files stay in S3 Standard-IA for `3535 days` (exceeding the `3030-day` minimum storage duration requirement), and their large size (`250250 MB`) avoids any minimum billing size penalties. Transitioning the variant call files to S3 Glacier Flexible Retrieval after `3030 days` is optimal because their size (`6060 KB`) exceeds Glacier's `4040 KB` minimum billing size, and Glacier Flexible Retrieval's Expedited retrieval option recovers files in `11 to 55 minutes`, meeting the requirement to access data within minutes.

Step-by-Step Solution

1
Evaluate lifecycle properties of the alignment files (`.bam`).
The files are `250250 MB` (exceeding S3 Standard-IA's `128128 KB` minimum billing size). Transitioning to S3 Standard-IA at day `1010` and expiring at day `4545` keeps the files in Standard-IA for `3535 days`.
Because the files reside in S3 Standard-IA for more than the `3030-day` minimum storage duration requirement, this transition is highly cost-effective and does not incur early deletion fees.
2
Evaluate lifecycle properties and access requirements of the variant call files (`.vcf`).
The files are `6060 KB`. Transitioning them to S3 Standard-IA or S3 Glacier Instant Retrieval would trigger a `128128 KB` minimum billing size penalty. S3 Glacier Flexible Retrieval has a `4040 KB` minimum billing size and supports Expedited retrievals (`11 to 55 minutes`).
Glacier Flexible Retrieval accommodates the `6060 KB` size without size-based billing overhead, keeps storage costs low for permanent retention, and satisfies the requirement to retrieve the files within minutes.
3
Select the two optimal lifecycle actions.
Transition alignment files to S3 Standard-IA after `1010 days` and expire after `4545 days` (Action 1). Transition variant call files to S3 Glacier Flexible Retrieval after `3030 days` (Action 2).
This combination minimizes storage costs by matching the workload requirements while avoiding size and duration penalties.

Key Concept

Aligning S3 Object sizes and lifecycle durations with the minimum billing sizes and minimum storage periods of S3 storage classes to avoid unexpected fees.
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