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1462 questions

Question 621Question

A healthcare provider is designing a resilient, highly available architecture on AWS for its critical patient imaging system. The system consists of: (1) A database layer that requires automated, immediate failover with zero data loss in the event of an Availability Zone outage. (2) A shared file storage system to host active image files that must be concurrently read and written by multiple Amazon EC2 instances across three Availability Zones. (3) An archiving solution for older images that requires retrieval in under 10 minutes for emergency cases. Which combination of storage and database configurations will meet these requirements? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: Configure the database using Amazon RDS Multi-AZ DB clusters to provide automatic failover and synchronous replication across Availability Zones.; Use Amazon EFS as the shared file system for active image files, and archive historical images in Amazon S3 Glacier Flexible Retrieval using Expedited retrievals.

Answer

Configure the database using Amazon RDS Multi-AZ DB clusters to provide automatic failover and synchronous replication across Availability Zones, and use Amazon EFS as the shared file system for active image files while archiving historical images in Amazon S3 Glacier Flexible Retrieval using Expedited retrievals.
Deploying the database using Amazon RDS Multi-AZ DB clusters provides high availability, synchronous replication, and automated failover across multiple Availability Zones, which addresses the zero data loss and automated failover requirement. Utilizing Amazon EFS as a shared file system allows multiple EC2 instances to concurrently read and write files with high availability across three Availability Zones. Furthermore, archiving historical images in Amazon S3 Glacier Flexible Retrieval and using Expedited retrievals allows the company to meet the RTO requirement of under 10 minutes, as Expedited retrievals make data available within 1 to 5 minutes.

Step-by-Step Solution

1
Analyze the database resilience requirements: automated, immediate failover with zero data loss in the event of an AZ outage.
Identify Amazon RDS Multi-AZ DB clusters or standard Multi-AZ deployments as the correct choice since they support synchronous replication and automated failover.
To ensure high availability and prevent data loss during an AZ outage.
2
Analyze the shared storage requirements: active image files must be concurrently read/written by multiple EC2 instances across three AZs.
Identify Amazon EFS (Elastic File System) as the correct shared file system since it natively supports multi-AZ concurrent access.
EBS volumes cannot be mounted concurrently across multiple AZs under these constraints.
3
Analyze the archive retrieval requirements: historical images must be retrieved in under 10 minutes.
Select S3 Glacier Flexible Retrieval using Expedited retrievals, which completes in 1-5 minutes.
Standard retrievals take 3-5 hours, which violates the RTO target.

Key Concept

Designing resilient storage and database architectures involves matching application workloads with the correct storage service (e.g., EFS for concurrent multi-AZ file access) and retrieval configuration (e.g., Expedited retrievals for tight RTOs), while using Multi-AZ replication to ensure database resilience.
Estimated Time:2m 0s
Question 622Question

An enterprise organization is migrating a high-volume PostgreSQL database to AWS. The application demands a multi-region disaster recovery architecture that can survive a complete AWS Region outage. The business specifies a Recovery Point Objective (RPO) of less than 1 second and a Recovery Time Objective (RTO) of less than 2 minutes. Additionally, read requests from users in the recovery region must be served locally with sub-second latency to optimize user experience. Which combination of actions should a solutions architect recommend to satisfy these resilience and performance criteria? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: Create an Amazon Aurora PostgreSQL Global Database with the primary cluster located in the primary region and a secondary cluster in the recovery region.; In the event of a primary region outage, initiate a managed failover of the Aurora Global Database to promote the secondary cluster to primary.

Answer

Deploying an Amazon Aurora PostgreSQL Global Database and using managed failover during a regional outage satisfies the strict recovery and latency requirements.
Deploying an Amazon Aurora PostgreSQL Global Database ensures storage-level replication to the secondary region with lag typically below 1 second, which satisfies the sub-second RPO. The secondary cluster allows read requests in the backup region to be served locally with sub-second latency. In the event of a regional failure, initiating a managed failover promotes the secondary cluster to primary, maintaining the global database layout and meeting the RTO of under 2 minutes.

Step-by-Step Solution

1
Analyze recovery objectives and read latency constraints.
Identified RPO < 1 second, RTO < 2 minutes, and local read scaling in the recovery region.
This establishes the architectural boundary and eliminates low-performance backup or standard asynchronous replication models.
2
Evaluate database engine replication capabilities.
Amazon Aurora Global Database provides storage-level replication with lag under 1 second, supporting local read replicas in the secondary region.
Standard RDS replication has higher latency overhead and does not support native cross-region failover automation.
3
Identify failover mechanism to meet target RTO.
Managed failover of Aurora Global Database automates the promotion of the secondary cluster with minimal disruption.
Manual promotion of replicas takes longer and breaks the global database replication topology.

Key Concept

High availability and disaster recovery design using Amazon Aurora Global Databases.
Question 623Question

A company is deploying a big data analytics application on a fleet of Amazon EC2 instances. The application requires a shared, POSIX-compliant storage solution that allows all instances to read and write concurrently. The workload is highly unpredictable, and the storage must scale throughput automatically to handle sudden spikes in I/O demand. Which storage solution should a solutions architect recommend to meet these requirements?

Show answer & explanation

Answer: Amazon Elastic File System (Amazon EFS) configured with Elastic throughput

Answer

Amazon Elastic File System (Amazon EFS) configured with Elastic throughput
Amazon Elastic File System (Amazon EFS) configured with Elastic throughput is the correct choice because EFS is a fully managed, shared POSIX-compliant file system that multiple EC2 instances can access concurrently. The Elastic throughput mode automatically scales the file system's performance up and down to match workload spikes without administrative intervention.

Step-by-Step Solution

1
Identify the file system requirement
The application requires a shared, POSIX-compliant storage solution accessible concurrently by multiple EC2 instances, which points to a shared file system rather than block storage or archive storage.
Amazon EBS is designed as single-instance block storage (with limited Multi-Attach exceptions), while Amazon S3 Glacier is for archival storage.
2
Analyze the throughput scaling requirement
The throughput demands are highly unpredictable and require automatic scaling.
Amazon EFS with Elastic throughput automatically adjusts throughput capacity in response to dynamic workload activity, making it perfect for unpredictable workloads.

Key Concept

Shared POSIX storage with auto-scaling throughput
Estimated Time:1m 0s
Question 624Question

An enterprise is migrating a latency-sensitive high-performance compute (HPC) application to AWS. The workload runs on a cluster of Linux EC2 instances distributed across multiple Availability Zones in a Region. The application requires a shared file system that is POSIX-compliant, supports NFS, and must deliver consistent sub-millisecond latencies, up to 80,00080,000 IOPS, and 2 GB/s2\text{ GB/s} of throughput to handle concurrent read and write operations. Which storage solution should a solutions architect recommend to meet these requirements?

Show answer & explanation

Answer: Configure an Amazon FSx for NetApp ONTAP file system in a Multi-AZ deployment.

Answer

Configure an Amazon FSx for NetApp ONTAP file system in a Multi-AZ deployment.
The correct option is the FSx for NetApp ONTAP file system in a Multi-AZ deployment because it provides POSIX-compliant NFS shares across multiple Availability Zones with sub-millisecond latencies (leveraging NVMe caching) and easily scales to 80,00080,000 IOPS and 2 GB/s2\text{ GB/s} throughput.

Step-by-Step Solution

1
Analyze the availability zone and shared storage requirements.
The solution must support multiple EC2 instances across multiple Availability Zones simultaneously using a POSIX-compliant, NFS-supported file system.
This rules out single-AZ solutions or block storage that cannot span multiple Availability Zones.
2
Evaluate the performance constraints (sub-millisecond latency, 80,00080,000 IOPS, 2 GB/s2\text{ GB/s} throughput).
Amazon EFS is ruled out because it typically operates with low single-digit millisecond latency rather than sub-millisecond latency.
EFS does not meet the strict latency requirement of the HPC application.
3
Assess the multi-AZ and protocol capabilities of the remaining options.
Amazon EBS io2 with Multi-Attach is limited to a single AZ. Amazon FSx for Lustre only supports Single-AZ deployments. Amazon FSx for NetApp ONTAP supports Multi-AZ deployments with synchronous replication and delivers sub-millisecond latency via NVMe caching.
FSx for NetApp ONTAP is the only solution that satisfies all shared access, protocol, multi-AZ, and performance requirements.

Key Concept

Selecting high-performing, multi-AZ shared storage solutions based on latency, throughput, and protocol requirements.
Estimated Time:2m 30s
Question 625Question

A company needs to connect its on-premises office to a VPC in AWS using an AWS Site-to-Site VPN. The application requires a minimum network throughput of 2 Gbps2\text{ Gbps}. Which TWO configurations should a solutions architect implement to meet this requirement? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: Create an AWS Transit Gateway and attach the VPC and the VPN connection to it.; Enable Equal-Cost Multi-Path (ECMP) routing on the AWS Transit Gateway and establish multiple VPN tunnels.

Answer

The solutions architect must create an AWS Transit Gateway and attach both the VPC and the VPN to it, then enable Equal-Cost Multi-Path (ECMP) routing on the Transit Gateway while establishing multiple VPN tunnels.
To achieve a VPN throughput higher than the default limit of 1.25 Gbps1.25\text{ Gbps} per tunnel, you must deploy an AWS Transit Gateway, configure the VPN connections as attachments to it, and enable Equal-Cost Multi-Path (ECMP) routing. This allows the system to aggregate the throughput of multiple tunnels to meet the 2 Gbps2\text{ Gbps} requirement.

Step-by-Step Solution

1
Identify the maximum bandwidth capacity of a single AWS Site-to-Site VPN tunnel.
Each individual VPN tunnel has a hard throughput limit of 1.25 Gbps1.25\text{ Gbps}.
Since the requirement is a minimum of 2 Gbps2\text{ Gbps}, a single standard VPN tunnel cannot meet this demand.
2
Introduce a routing hub that supports multi-path routing.
Attach the VPC and the Site-to-Site VPN connection to an AWS Transit Gateway.
An AWS Transit Gateway is required to aggregate bandwidth across multiple active VPN connections/tunnels.
3
Enable Equal-Cost Multi-Path (ECMP) routing on the AWS Transit Gateway.
Traffic is dynamically distributed across multiple established VPN tunnels.
With ECMP enabled, multiple VPN tunnels can be utilized concurrently to scale total throughput beyond the 1.25 Gbps1.25\text{ Gbps} limit.

Key Concept

AWS VPN Tunnel Limits and Scaling with Transit Gateway ECMP
Question 626Question

A telemetry ingestion pipeline collects data from 100,000100,000 IoT sensors. Each sensor transmits a 1.5 KB1.5\text{ KB} payload every 10 seconds10\text{ seconds} to an Amazon Kinesis data stream configured with 1010 provisioned shards. During peak periods, downstream consumers experience data gaps, and the sensor applications log frequent `ProvisionedThroughputExceededException` errors. Which action should a solutions architect take to resolve this issue with the least operational overhead?

Show answer & explanation

Answer: Change the capacity mode of the Kinesis data stream to On-Demand.

Answer

Change the capacity mode of the Kinesis data stream to On-Demand.
The correct option is to change the capacity mode of the Kinesis data stream to On-Demand. The total ingestion requirements are 10,000 records/s10,000\text{ records/s} and 15 MB/s15\text{ MB/s} of throughput. Since a single shard is limited to 1 MB/s1\text{ MB/s} of write throughput, the stream requires a minimum of 1515 shards. The current configuration of 1010 shards is insufficient. Switching to On-Demand capacity mode enables automatic scaling of shards to accommodate the peak write rate, eliminating the ProvisionedThroughputExceededException errors with minimal administrative effort.

Step-by-Step Solution

1
Calculate the peak throughput and record rate of the IoT ingestion pipeline.
Record Rate = 10,000 records/s10,000\text{ records/s}. Throughput = 10,000 records/s×1.5 KB=15,000 KB/s=15 MB/s10,000\text{ records/s} \times 1.5\text{ KB} = 15,000\text{ KB/s} = 15\text{ MB/s}.
To determine the minimum shard capacity required for ingestion.
2
Compare the calculated requirement against the current stream capacity.
Current capacity is 10 MB/s10\text{ MB/s} and 10,000 records/s10,000\text{ records/s}. The required write throughput (15 MB/s15\text{ MB/s}) exceeds the provisioned capacity limit (10 MB/s10\text{ MB/s}).
To verify if the write throughput limit is being exceeded, causing the ProvisionedThroughputExceededException.
3
Choose the solution that resolves the limitation with the lowest operational overhead.
Select On-Demand capacity mode instead of manually resizing the stream or writing custom scaling automation.
On-Demand capacity mode requires zero administrative management and adapts dynamically to traffic peaks.

Key Concept

Kinesis Data Streams Capacity Planning and Auto-Scaling
Estimated Time:1m 30s
Question 627Question

A logistics company is designing the database architecture for a global fleet tracking system. The system uses a PostgreSQL database located in the eu-west-1 Region, with a disaster recovery (DR) target in the ap-southeast-1 Region. The system has a strict Recovery Time Objective (RTO) of under 5 minutes and a Recovery Point Objective (RPO) of under 1 minute. Local regional offices in the Asia-Pacific region must also run read-only telemetry reports with low latency, without affecting write performance in Europe.

Which database configuration will meet these requirements with the minimum operational complexity?

Show answer & explanation

Answer: Configure an Amazon Aurora PostgreSQL Global Database with the primary cluster in the eu-west-1 Region and a secondary cluster in the ap-southeast-1 Region. Use the secondary cluster's local endpoints for the Asia-Pacific telemetry reports, and perform a managed failover to promote the secondary cluster if the primary region fails.

Answer

Configure an Amazon Aurora PostgreSQL Global Database with the primary cluster in the eu-west-1 Region and a secondary cluster in the ap-southeast-1 Region. Use the secondary cluster's local endpoints for the Asia-Pacific telemetry reports, and perform a managed failover to promote the secondary cluster if the primary region fails.
The configuration utilizing Amazon Aurora Global Database is correct because it uses storage-level replication to achieve cross-region replication lag of less than 1 second, fulfilling the 1-minute RPO requirement. Furthermore, it supports managed failover, which promotes the secondary region to primary in less than a minute, meeting the 5-minute RTO. The local cluster in ap-southeast-1 provides local read endpoints for reporting workloads, keeping read latencies low and isolating reporting performance from primary write workloads.

Step-by-Step Solution

1
Analyze the disaster recovery constraints (RTO < 5 minutes, RPO < 1 minute).
Identify that the solution must support sub-minute replication lag (for RPO) and rapid failover (for RTO) across AWS Regions.
This rules out snapshot-based recovery (which has RTO in hours and RPO determined by snapshot intervals) and standard RDS replica promotion (which is manual and slow).
2
Analyze the read scalability and latency requirements (local Asia-Pacific reports with low latency, no impact on write performance).
Determine that a local read replica or secondary read-only database cluster must be placed in ap-southeast-1.
Routing read queries across regions from ap-southeast-1 to eu-west-1 would introduce unacceptable network latency.
3
Evaluate Amazon Aurora Global Database capabilities against the requirements.
Aurora Global Database replicates data storage-to-storage with a typical lag of under 1 second (meeting the RPO of < 1 minute) and supports managed failover with RTO of under 1 minute.
Aurora Global Database is the native AWS feature designed exactly for multi-region resilience and local read scaling under strict RTO/RPO limits.

Key Concept

Amazon Aurora Global Database provides storage-based cross-region replication for low-latency local reads, sub-minute replication lag, and rapid managed regional failover to meet strict RTO/RPO requirements.
Estimated Time:3m 0s
Question 628Question

A company is hosting a web application on multiple Amazon EC2 instances distributed across different Availability Zones. The application requires a highly available, shared file storage system where all EC2 instances can concurrently read and write uploaded user media files. Which storage solution should a solutions architect recommend to meet these requirements?

Show answer & explanation

Answer: Amazon Elastic File System (Amazon EFS)

Answer

Amazon Elastic File System (Amazon EFS)
Amazon Elastic File System (Amazon EFS) provides serverless, highly available, and resilient network file storage that can be concurrently mounted by EC2 instances across multiple Availability Zones via standard NFSv4 protocols.

Step-by-Step Solution

1
Analyze the storage requirements of the application.
The application needs shared file-level storage (not block or database) that supports concurrent read/write operations from multiple EC2 instances across multiple Availability Zones.
Identifying the data access pattern (concurrent file access) and geographic requirement (multi-AZ) helps narrow down the service options.
2
Compare the capabilities of available AWS storage services against these requirements.
Amazon Elastic File System (Amazon EFS) is built for POSIX-compliant shared file access across multiple Availability Zones concurrently, while EBS is block storage, S3 Glacier is for archives, and RDS is for structured relational data.
Choosing the service that matches both the concurrent file sharing model and the high availability needs is required for a resilient architecture.

Key Concept

Selecting highly available shared file storage for concurrent multi-instance access across multiple Availability Zones
Estimated Time:45s
Question 629Question

A company has two VPCs in the same AWS Region that need to share database replication traffic. The database replication requires high throughput and the lowest possible latency between the VPCs. Which network connectivity option should a solutions architect recommend to meet these performance requirements?

Show answer & explanation

Answer: Establish a VPC peering connection between the VPCs and update the VPC route tables to direct traffic.

Answer

Establish a VPC peering connection between the VPCs and update the VPC route tables to direct traffic.
The correct option is to establish a VPC peering connection. VPC peering allows direct routing of traffic between VPCs in the same Region using private IP addresses. Because it does not rely on physical gateways or VPN tunnels, it has no bandwidth bottlenecks, provides the lowest latency, and does not incur encryption overhead.

Step-by-Step Solution

1
Analyze the requirements for network connectivity between two VPCs in the same AWS Region.
The requirements demand high throughput and the lowest possible latency for database replication.
This helps narrow down the solutions to options that utilize the AWS internal network backbone without translation gateways or public internet transit.
2
Evaluate VPC peering against other options.
VPC peering connects the VPCs directly, allowing instances to communicate using private IP addresses at full network speed with no intermediate gateways.
This provides the lowest possible latency and supports high bandwidth.
3
Assess the performance limitations of alternative solutions.
A Site-to-Site VPN is limited to 1.25 Gbps1.25\text{ Gbps} per tunnel; Route 53 latency routing over the public internet increases latency; Network ACLs are security filters, not routing mechanisms.
This eliminates suboptimal or technically incorrect options.

Key Concept

VPC Peering for High-Performance Inter-VPC Connectivity
Question 630Question

A financial services company is migrating a high-frequency trading simulation platform to Amazon EC2. The platform consists of a cluster of Linux EC2 instances that require concurrent, shared access to a dataset via the NFS protocol. The workload demands sub-millisecond latencies for random file operations, sustained throughput of 4 GiB/s4 \text{ GiB/s} during peak hours, and up to 100,000100,000 IOPS. The storage solution must also support instantaneous, space-efficient file system snapshots and clones for testing runs.

Which combination of storage configurations and client-side settings will meet these requirements? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: Provision an Amazon FSx for NetApp ONTAP file system with SSD storage, configuring the throughput capacity and provisioned IOPS to meet the workload demands.; Mount the shared file system on the Linux EC2 instances using the NFS protocol with the 'nconnect' mount option enabled.

Answer

Provision an Amazon FSx for NetApp ONTAP file system with SSD storage and mount it using the NFS protocol with the 'nconnect' mount option enabled.
Provisioning an Amazon FSx for NetApp ONTAP file system is correct because it supports NFSv4, SSD storage with sub-millisecond latencies, and native features like snapshots and clones. Mounting the file system with the 'nconnect' option is correct because it enables the Linux NFS client to use multiple TCP connections, which is required to achieve the throughput of 4 GiB/s4 \text{ GiB/s} and 100,000100,000 IOPS that would otherwise be bottlenecked by a single TCP connection.

Step-by-Step Solution

1
Identify the protocol, performance, and features required by the workload.
The workload requires NFS protocol access, sub-millisecond latencies, 4 GiB/s4 \text{ GiB/s} throughput, 100,000100,000 IOPS, and instantaneous, space-efficient snapshots/clones.
This establishes the baseline criteria to filter out unsuitable storage services.
2
Evaluate Amazon FSx for NetApp ONTAP against these requirements.
FSx for ONTAP supports NFS, delivers sub-millisecond latency using SSD storage, supports high IOPS and throughput, and provides NetApp Snapshot and FlexClone features which are instantaneous and space-efficient.
FSx for ONTAP is the only AWS shared file system that natively supports all these enterprise storage features.
3
Determine client-side mount options required to achieve the throughput and IOPS targets.
Using the 'nconnect' NFS mount option allows the EC2 instances to parallelize network traffic across multiple TCP connections.
A single TCP connection is restricted by network limits and cannot achieve the 4 GiB/s4 \text{ GiB/s} throughput and 100,000100,000 IOPS requirements.

Key Concept

Amazon FSx for NetApp ONTAP offers sub-millisecond latencies, NFS compatibility, and advanced data management (snapshots/clones), which must be paired with client-side NFS tuning (such as the 'nconnect' mount option) to bypass single-TCP connection throughput limits.
Question 631Question

A company needs to ingest 3 MB/s3\text{ MB/s} of transaction records from an e-commerce website. The records must be processed in the exact order they are received to maintain inventory accuracy, and then saved to Amazon S3. Which AWS service configuration provides the most suitable ingestion pipeline with the least operational overhead?

Show answer & explanation

Answer: Amazon Kinesis Data Streams in On-Demand mode to ingest the records using partition keys, and Amazon Data Firehose to deliver the data to Amazon S3.

Answer

Amazon Kinesis Data Streams in On-Demand mode to ingest the records using partition keys, and Amazon Data Firehose to deliver the data to Amazon S3.
The correct answer combines Amazon Kinesis Data Streams in On-Demand mode with Amazon Data Firehose. Kinesis Data Streams in On-Demand mode automatically scales to accommodate the 3 MB/s3\text{ MB/s} data stream without manual intervention, while using partition keys ensures records are processed chronologically within the shard. Amazon Data Firehose handles data batching and delivery directly to Amazon S3 with minimal operational overhead.

Step-by-Step Solution

1
Determine throughput requirements and choose an appropriate stream capacity configuration.
The ingestion rate is 3 MB/s3\text{ MB/s}. Since a single Kinesis shard supports only 1 MB/s1\text{ MB/s} of write capacity, multiple shards are required. Selecting Kinesis Data Streams in On-Demand mode automatically handles scaling and dynamically allocates the required capacity without manual shard management.
To prevent throttling and eliminate operational overhead associated with manually scaling shards.
2
Select a mechanism to guarantee strict chronological message ordering.
Using a partition key (such as the transaction ID) ensures that records for the same transaction are routed to the same Kinesis shard and processed in the exact order they were received.
To satisfy the business requirement of maintaining inventory accuracy through chronological record processing.
3
Select the most efficient and lowest-overhead service to write the streaming data to Amazon S3.
Amazon Data Firehose is integrated natively with Amazon Kinesis Data Streams and automatically batches, compresses, and delivers data to Amazon S3 with zero server administration.
To minimize operational overhead as required by the business.

Key Concept

Selecting high-performance, serverless data ingestion solutions with strict ordering requirements.
Question 632Question

A logistics company is migrating its core shipment tracking system to AWS. The application uses a PostgreSQL database and must be resilient to a complete AWS Region outage. The solutions architect must design a disaster recovery (DR) strategy with a Recovery Time Objective (RTO) of less than 15 minutes and a Recovery Point Objective (RPO) of less than 10 seconds. Which configuration meets these requirements with the least operational overhead?

Show answer & explanation

Answer: Deploy an Amazon Aurora PostgreSQL Global Database with the primary cluster in the active Region and a secondary cluster in the recovery Region, using cross-Region replication.

Answer

Deploy an Amazon Aurora PostgreSQL Global Database with the primary cluster in the active Region and a secondary cluster in the recovery Region, using cross-Region replication.
The correct configuration uses Amazon Aurora Global Databases, which feature built-in, storage-based replication across AWS Regions. It achieves an RPO of less than 10 seconds because replication lag is typically less than one second. The secondary cluster can be promoted to a primary cluster with full read/write capabilities in less than 15 minutes, satisfying the RTO requirement with minimal operational overhead.

Step-by-Step Solution

1
Analyze RTO and RPO requirements.
RTO must be under 15 minutes, and RPO must be under 10 seconds. This demands a warm standby or active-passive cross-region database replication mechanism with sub-second replication lag.
Traditional backup and restore methods take too long to restore (exceeding RTO) and have data loss intervals larger than 10 seconds (exceeding RPO).
2
Evaluate cross-region capabilities of Amazon RDS vs. Amazon Aurora.
Amazon Aurora Global Database replicates data at the storage layer with typical latency of less than one second, allowing an RPO of under 10 seconds. It also supports quick promotion of secondary clusters (RTO under 15 minutes).
Amazon RDS for PostgreSQL cross-region replicas use logical/physical replication at the engine level, which incurs more overhead, and promotion requires custom orchestration.
3
Select the option that minimizes operational overhead.
Amazon Aurora Global Database is fully managed and requires no custom scripting to handle replication and failover promotion.
Using Aurora Global Database is the most native and reliable way to meet both strict RTO/RPO limits and minimize management complexity.

Key Concept

Disaster recovery replication and failover constraints for managed relational databases on AWS
Question 633Question

A clinical diagnostics company operates a containerized genomic analysis pipeline on Amazon Elastic Kubernetes Service (Amazon EKS) in the `eu-west-1` Region. The pipeline requires a shared, POSIX-compliant file storage layer that provides latencies of less than 11 millisecond for active DNA sequence processing, supports concurrent read/write access from hundreds of active pods across 33 Availability Zones, and guarantees a Recovery Point Objective (RPO) of 00 and a Recovery Time Objective (RTO) of near 00 in the event of an Availability Zone outage. For compliance, a copy of the processed genomic datasets must be archived in the `eu-central-1` Region with an RPO of less than 1515 minutes. If a disaster occurs in the primary Region, the archived datasets must be accessible in `eu-central-1` within a recovery RTO of 55 minutes. Which combination of storage configurations will meet these resilience and recovery requirements? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: Configure an Amazon Elastic File System (Amazon EFS) using the Regional (Standard) storage class in the primary Region.; Configure Amazon EFS Replication to asynchronously copy the file system to a destination EFS file system in the secondary Region.

Answer

Configure an Amazon Elastic File System (Amazon EFS) using the Regional (Standard) storage class in the primary Region, and configure Amazon EFS Replication to asynchronously copy the file system to a destination EFS file system in the secondary Region.
To build a highly available and resilient shared file system that supports POSIX-compliant operations with sub-millisecond latencies across multiple Availability Zones, the Regional (Standard) storage class of Amazon EFS must be used. To replicate this shared file system to a secondary Region while satisfying an RPO of under 1515 minutes and a recovery RTO of under 55 minutes, Amazon EFS Replication is the native feature that continuously synchronizes data and keeps the destination file system mount-ready.

Step-by-Step Solution

1
Evaluate the primary storage requirements for POSIX compliance, sub-millisecond latencies, and Multi-AZ concurrency.
Identify that Amazon EFS Regional (Standard) storage class is required to allow hundreds of pods to read/write concurrently across 33 Availability Zones.
EFS provides native POSIX-compliant shared file storage with automatic failover and replication across multiple Availability Zones in a Region, ensuring an RPO of 00 and near-zero RTO.
2
Determine the optimal cross-region replication method that satisfies the 1515-minute RPO and 55-minute recovery RTO.
Select Amazon EFS Replication to copy data to a destination EFS file system in the secondary Region.
EFS Replication is a fully managed, native feature that replicates changes asynchronously within minutes (meeting the 1515-minute RPO) and keeps the destination file system ready to mount immediately (meeting the 55-minute recovery RTO).

Key Concept

Amazon EFS Regional storage provides automatic Multi-AZ failover with zero data loss, while Amazon EFS Replication enables managed, low-latency cross-region disaster recovery.
Estimated Time:3m 0s
Question 634Question

A company has deployed 15 VPCs in the us-east-1 Region to connect different microservices for an application. Currently, the VPCs are connected using a full mesh of VPC Peering connections. The company plans to add 20 more VPCs and requires centralized traffic monitoring and security filtering through a dedicated inspection VPC. The current design is becoming difficult to manage and scale. Which solution should a solutions architect recommend to simplify the network architecture while maintaining high performance and scalability?

Show answer & explanation

Answer: Deploy AWS Transit Gateway, attach all VPCs to the Transit Gateway, and configure routing tables to route inter-VPC traffic through the dedicated inspection VPC.

Answer

Deploy AWS Transit Gateway, attach all VPCs to the Transit Gateway, and configure routing tables to route inter-VPC traffic through the dedicated inspection VPC.
The correct solution involves deploying AWS Transit Gateway to act as a centralized hub. Transit Gateway simplifies the network architecture by replacing a complex web of VPC Peering connections with a hub-and-spoke model. Because Transit Gateway supports transitive routing, it allows the organization to route all traffic between spoke VPCs through a dedicated inspection VPC, satisfying both the scalability and centralized security monitoring requirements.

Step-by-Step Solution

1
Identify the scalability and routing limitations of the current full mesh VPC Peering configuration.
A full mesh of 15 VPCs requires 105 peering connections, and expanding to 35 VPCs would require 595 connections, which is complex and difficult to manage. VPC Peering also does not support transitive routing, making centralized traffic inspection difficult.
Understanding the limits of VPC Peering guides the selection of a hub-and-spoke model.
2
Evaluate AWS services designed to simplify multi-VPC connectivity and support centralized traffic inspection.
AWS Transit Gateway acts as a central hub (cloud router) that supports transitive routing. Traffic can be easily directed from spoke VPCs to a central inspection VPC before reaching other spokes.
Transit Gateway simplifies the network topology from a full mesh to a hub-and-spoke model while maintaining high performance.
3
Verify that Transit Gateway meets the performance and management requirements.
Transit Gateway supports high throughput (up to 50 Gbps per VPC attachment by default) and reduces routing management overhead by using centralized route tables.
Confirming the throughput and routing features ensures the architecture scales efficiently without performance bottlenecks.

Key Concept

AWS Transit Gateway acts as a network transit hub, enabling transitive routing to simplify multi-VPC architectures and centralize traffic inspection while maintaining high performance.
Question 635Question

A company is migrating a legacy document management system to AWS. The system runs on a fleet of Amazon EC2 instances deployed across multiple Availability Zones in an Auto Scaling group. The system requires a shared, POSIX-compliant storage volume where multiple instances can concurrently read and write file data. The workload is highly unpredictable, with throughput demands spiking from a baseline of 10 MiB/s10\text{ MiB/s} up to 450 MiB/s450\text{ MiB/s} during business peak hours. The solution must deliver low latency and scale performance automatically without manual intervention or over-provisioning. Which storage configuration provides the highest performance and meets these scalability requirements?

Show answer & explanation

Answer: An Amazon EFS file system configured with Elastic throughput mode

Answer

An Amazon EFS file system configured with Elastic throughput mode
The correct option is Amazon EFS with Elastic throughput mode because it natively supports shared, concurrent POSIX file access across multiple Availability Zones. Elastic throughput automatically scales up and down based on real-time application demands, successfully supporting throughput spikes from 10 MiB/s10\text{ MiB/s} to 450 MiB/s450\text{ MiB/s} without manual capacity management or paying for idle provisioned capacity.

Step-by-Step Solution

1
Analyze the application's environment and access requirements.
The application runs on Amazon EC2 instances in an Auto Scaling group across multiple Availability Zones, requiring shared, POSIX-compliant storage with concurrent read/write access.
This rules out Amazon EBS because EBS volumes are single-AZ resources and do not provide a POSIX-compliant shared file system natively across multiple AZs.
2
Analyze the workload's performance profile and throughput variability.
Throughput demands are highly variable and unpredictable, spiking from 10 MiB/s10\text{ MiB/s} to 450 MiB/s450\text{ MiB/s}.
This points to Amazon EFS. To handle unpredictable spikes without over-provisioning, Elastic throughput mode is required, as it automatically scales throughput based on workload demand.
3
Compare Amazon EFS throughput modes to select the optimal solution.
Amazon EFS with Elastic throughput mode dynamically handles the 10 MiB/s10\text{ MiB/s} to 450 MiB/s450\text{ MiB/s} range automatically. Provisioned throughput at 450 MiB/s450\text{ MiB/s} would meet the demand but result in significant over-provisioning costs.
Elastic throughput matches both performance requirements and cost optimization guidelines by scaling dynamically without manual provisioning.

Key Concept

Amazon EFS with Elastic Throughput provides a shared POSIX file system across multiple Availability Zones that dynamically scales throughput to match unpredictable workloads without administrative overhead or over-provisioning.
Question 636Question

A global gaming company hosts a real-time multiplayer game on Amazon ECS clusters deployed behind Network Load Balancers (NLBs) in the `us-east-1`, `eu-west-1`, and `ap-southeast-1` Regions. The game clients communicate using UDP for state synchronization. Players are experiencing high jitter, packet loss, and latency fluctuations due to congestion on the public internet. The company requires a networking architecture that minimizes latency and packet loss by routing traffic over the AWS private network backbone, while providing a single set of static entry-point IP addresses.

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

Show answer & explanation

Answer: Deploy AWS Global Accelerator to provide static Anycast IP addresses, and configure the regional Network Load Balancers as endpoints. Configure the game clients to connect directly to these Anycast IP addresses.

Answer

Deploy AWS Global Accelerator to provide static Anycast IP addresses, and configure the regional Network Load Balancers as endpoints. Configure the game clients to connect directly to these Anycast IP addresses.
AWS Global Accelerator uses Anycast routing to ingest client traffic at the nearest AWS edge location and then routes it over the congestion-free, high-performance AWS global private network backbone directly to the Network Load Balancers. This significantly reduces latency, jitter, and packet loss for UDP traffic compared to routing over the public internet, while providing static Anycast IP addresses as a single entry point.

Step-by-Step Solution

1
Identify the key performance and architectural requirements.
Requirements are: route UDP traffic, minimize jitter and packet loss, bypass public internet congestion, and provide static entry-point IP addresses.
This establishes the constraints that any valid solution must satisfy.
2
Evaluate the routing path of AWS Global Accelerator.
Global Accelerator uses Anycast to ingest traffic at the closest edge location and routes it over the private AWS backbone to the regional NLB endpoints, supporting both TCP and UDP.
This validates if Global Accelerator can bypass public internet routing and support the game's protocols.
3
Assess the performance characteristics of the alternative options.
Route 53 latency routing still routes traffic over the public internet. A single VPN connection has a hard throughput limit of 1.25 Gbps1.25\text{ Gbps}. Network ACLs are stateless and cannot prioritize traffic.
This confirms that the other solutions are either technically impossible or do not solve the latency and jitter issues.

Key Concept

AWS Global Accelerator uses Anycast to route global user traffic over the AWS private network backbone, reducing latency, jitter, and packet loss for UDP/TCP workloads while providing static entry-point IP addresses.
Estimated Time:2m 0s
Question 637Question

A company runs an application with a database backend on an Amazon RDS for PostgreSQL DB instance. The solutions architect must configure the database to achieve high availability with automatic failover (Recovery Time Objective under 2 minutes) in the event of an Availability Zone outage. Additionally, the application requires read scaling to handle reporting queries during peak hours without impacting the performance of the write database. 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 RDS PostgreSQL DB instance as a Multi-AZ deployment.; Create one or more RDS Read Replicas to offload reporting queries.

Answer

Deploying the Amazon RDS PostgreSQL DB instance in a Multi-AZ configuration to support automatic failover and creating one or more RDS Read Replicas to handle reporting read queries.
To satisfy both requirements, the solutions architect must configure a Multi-AZ deployment to handle high availability and automatic failover in under 2 minutes, and create read replicas to handle the reporting read workload.

Step-by-Step Solution

1
Address the high availability and quick failover constraint.
An Amazon RDS Multi-AZ deployment is selected because it replicates data synchronously to a standby instance in a different Availability Zone and performs automatic failover when the primary instance fails.
This configuration provides an RTO of under 2 minutes without administrative intervention.
2
Address the read scaling performance constraint.
RDS Read Replicas are selected to host reporting queries.
By redirecting read traffic to the read replicas, the primary database's performance is preserved for write operations.

Key Concept

Configuring Amazon RDS for high availability using Multi-AZ deployments, and scaling read workloads separately using Read Replicas.
Question 638Question

A gaming company is developing a real-time multiplayer gaming analytics platform that receives gameplay telemetry from 800,000800,000 active concurrent players. The telemetry data stream is sent in JSON format, averaging 15 MB/s15\text{ MB/s} with peak volumes reaching 60 MB/s60\text{ MB/s} during global events. The platform must ingest this telemetry with sub-second latency, perform stateful anomaly detection and metrics aggregation over a sliding window of 5 minutes5\text{ minutes}, and save the transformed output in Apache Parquet format to Amazon S3 for long-term historical query access. The architecture must scale dynamically to handle peak volumes without manual intervention or administrative overhead.

Which combination of actions will meet these requirements? (Select two.)

Select all that apply

Show answer & explanation

Answer: Configure an Amazon Kinesis Data Stream with on-demand capacity mode to ingest the incoming gaming telemetry.; Deploy an Amazon Managed Service for Apache Flink application to process the telemetry stream, calculate sliding-window metrics, and output to an Amazon Data Firehose delivery stream for Parquet conversion and delivery to Amazon S3.

Answer

To meet the requirements, the solutions architect should configure an Amazon Kinesis Data Stream in on-demand capacity mode for the ingestion layer, and deploy an Amazon Managed Service for Apache Flink application for stateful sliding-window processing, sending the output to Amazon Data Firehose for format conversion and delivery to Amazon S3.
The correct solution involves configuring Amazon Kinesis Data Streams in on-demand mode and using Amazon Managed Service for Apache Flink with Amazon Data Firehose. Kinesis Data Streams in on-demand mode scales dynamically to handle write throughput up to 200 MB/s200\text{ MB/s} and 200,000200,000 records per second, which comfortably supports the peak throughput of 60 MB/s60\text{ MB/s} without manual administrative overhead. Amazon Managed Service for Apache Flink provides a fully managed, serverless platform for stateful stream processing, making it ideal for performing computations like 55-minute sliding-window aggregations. By routing the output of Flink to Amazon Data Firehose, the platform can utilize Firehose's native integration with AWS Glue Schema Registry to convert the JSON data to Apache Parquet format before writing it to Amazon S3, satisfying all performance, latency, and operational requirements.

Step-by-Step Solution

1
Determine the ingestion layer capability and scaling needs.
Peak traffic is 60 MB/s60\text{ MB/s} and average is 15 MB/s15\text{ MB/s}. A Kinesis Data Stream in on-demand mode can handle up to 200 MB/s200\text{ MB/s} of write throughput automatically, which fulfills the dynamic scaling and zero administrative overhead requirements.
Provisioned mode with a fixed shard count would either throttle or require complex custom scaling scripts.
2
Identify the stateful transformation requirements.
A 55-minute sliding window requires maintaining state across events in overlapping time windows.
Amazon Managed Service for Apache Flink is the native serverless solution for stateful, low-latency stream analytics.
3
Design the output conversion and storage strategy.
Output must be stored as Apache Parquet in Amazon S3.
Connecting the Flink output to Amazon Data Firehose allows serverless transformation from JSON to Parquet (integrating with AWS Glue Schema Registry) before writing to Amazon S3.

Key Concept

Serverless high-throughput real-time stream ingestion and stateful time-window transformation using Kinesis Data Streams, Managed Service for Apache Flink, and Amazon Data Firehose.
Question 639Question

A multiplayer gaming company is designing a high-performance ingestion pipeline to collect real-time player telemetry and match event data from millions of active game clients. At peak gaming hours, the telemetry stream reaches a throughput of 85 MB/s85\text{ MB/s} with a message count of approximately 90,000 messages/second90,000\text{ messages/second}.

The pipeline must satisfy the following architectural requirements:
* Automatically convert the incoming raw telemetry records to Apache Parquet format and store them in Amazon S3, partitioned by event date, within 55 minutes of ingestion.
* Handle sudden traffic spikes dynamically without manual intervention or custom scaling scripts.
* Maintain strict chronological sequencing of events for each individual player session when routing telemetry to downstream analytics engines.

Which combination of actions should a solutions architect select to build this pipeline? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: Configure an Amazon Kinesis Data Stream using on-demand capacity mode, and use the player session ID as the partition key for the incoming records.; Configure an Amazon Data Firehose delivery stream with the Kinesis Data Stream as the source, enable format conversion to Apache Parquet referencing an AWS Glue schema, and set the buffering hint to 300300 seconds before writing to the Amazon S3 bucket.

Answer

To build a high-performing ingestion and transformation pipeline that handles spikes automatically, maintains ordering per player session, and converts data format within the required time window, you should configure an Amazon Kinesis Data Stream in on-demand capacity mode using the player session ID as the partition key, and couple it with an Amazon Data Firehose delivery stream that converts the source stream's JSON records to Apache Parquet using AWS Glue before writing to Amazon S3 with a 300-second buffer interval.
Configuring an Amazon Kinesis Data Stream in on-demand capacity mode ensures the stream automatically scales to handle throughput spikes up to 200 MB/s200\text{ MB/s} and 200,000 records/second200,000\text{ records/second}, which easily accommodates the peak of 85 MB/s85\text{ MB/s} and 90,000 messages/second90,000\text{ messages/second} without manual intervention. Using the player session ID as the partition key ensures that all events for a specific player session are written to the same shard, preserving chronological ordering. Integrating Amazon Data Firehose with the Kinesis Data Stream allows direct ingestion, and Firehose's native integration with the AWS Glue Data Catalog allows it to convert JSON data into Apache Parquet format automatically. Setting the buffering hint to 300300 seconds meets the requirement to store the data in Amazon S3 within 55 minutes.

Step-by-Step Solution

1
Analyze stream throughput and ingestion scale.
Determine that the peak write throughput is 85 MB/s85\text{ MB/s} and the record rate is 90,000 messages/second90,000\text{ messages/second}. Kinesis Data Streams in on-demand capacity mode dynamically handles up to 200 MB/s200\text{ MB/s} and 200,000 records/second200,000\text{ records/second} for writes without pre-provisioning shards.
Using on-demand capacity mode eliminates the need to write custom autoscaling scripts and prevents throttling during sudden traffic spikes.
2
Ensure sequencing and message ordering requirements are met.
Select player session ID as the partition key. Because Kinesis Data Streams guarantees order within a specific shard, mapping session data to the same shard preserves chronological sequencing.
Downstream analytics engines rely on chronological transaction/action sequence to accurately model player behavior.
3
Select the high-performing transformation and delivery mechanism.
Utilize Amazon Data Firehose with the Kinesis Data Stream as the source. Enable format conversion to Parquet by referencing an AWS Glue Data Catalog schema, and set the buffering hint to 300300 seconds.
Firehose performs serverless, zero-maintenance format conversion and batching, delivering the converted Parquet files to Amazon S3 within the required 55-minute latency limit.

Key Concept

Combining Kinesis Data Streams on-demand mode with Amazon Data Firehose format conversion to deliver ordered, transformed analytics data to S3 at scale.
Question 640Question

An application running on an Amazon EC2 instance requires a block storage volume that can deliver a sustained performance of 12,000 IOPS12,000 \text{ IOPS} and 350 MiB/s350 \text{ MiB/s} of throughput. Which two Amazon EBS volume types can be configured to meet these requirements? (Select TWO.)

Select all that apply

Show answer & explanation

Answer: General Purpose SSD (gp3); Provisioned IOPS SSD (io2)

Answer

The application should use General Purpose SSD (gp3) and Provisioned IOPS SSD (io2) volumes because both types support provisioning throughput up to at least 1,000 MiB/s1,000 \text{ MiB/s} and IOPS up to at least 16,000 IOPS16,000 \text{ IOPS} per volume, satisfying the required 12,000 IOPS12,000 \text{ IOPS} and 350 MiB/s350 \text{ MiB/s}.
General Purpose SSD (gp3) and Provisioned IOPS SSD (io2) are the correct answers because both volume types support the configuration of up to 1,000 MiB/s1,000 \text{ MiB/s} of throughput and at least 16,000 IOPS16,000 \text{ IOPS} (64,000 IOPS64,000 \text{ IOPS} for io2) per volume, satisfying the application's requirement for 12,000 IOPS12,000 \text{ IOPS} and 350 MiB/s350 \text{ MiB/s} of throughput.

Step-by-Step Solution

1
Analyze the workload's performance requirements.
The workload requires a block storage volume with 12,000 IOPS12,000 \text{ IOPS} and 350 MiB/s350 \text{ MiB/s} of throughput.
This establishes the minimum performance baseline that any selected storage volume must support.
2
Evaluate General Purpose SSD volumes.
General Purpose SSD (gp3) volumes can be provisioned with up to 16,000 IOPS16,000 \text{ IOPS} and 1,000 MiB/s1,000 \text{ MiB/s} throughput. General Purpose SSD (gp2) volumes have a maximum throughput limit of 250 MiB/s250 \text{ MiB/s}.
This identifies that gp3 is capable of meeting both performance metrics, while gp2 falls short on throughput.
3
Evaluate Provisioned IOPS SSD and HDD-based volumes.
Provisioned IOPS SSD (io2) volumes support up to 64,000 IOPS64,000 \text{ IOPS} and 1,000 MiB/s1,000 \text{ MiB/s} throughput. HDD-based volumes (st1 and sc1) are capped at 500 IOPS500 \text{ IOPS} and 250 IOPS250 \text{ IOPS} respectively.
This confirms io2 is a valid option, whereas st1 and sc1 cannot meet the IOPS requirements.

Key Concept

Selecting high-performance Amazon EBS volumes based on IOPS and throughput limitations.
Estimated Time:1m 0s
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