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A financial technology company is launching a real-time portfolio dashboard application on AWS. The application serves dynamic user portfolio data and stock price charts that are updated every 60 seconds. The application backend is hosted on Amazon EC2 instances behind an Application Load Balancer (ALB), with an Amazon Aurora PostgreSQL database as the primary storage. During peak market hours, the database CPU utilization spikes due to repetitive queries fetching identical stock price metrics. The company needs to design a caching architecture that reduces the load on the database and minimizes latency for users globally. Which TWO actions should the solutions architect take to meet these requirements?

Select all that apply

Deploy an Amazon CloudFront distribution in front of the ALB, and configure a cache behavior for the stock price chart API path with a Minimum TTL and Maximum TTL of 60 seconds.

Configure Amazon ElastiCache for Redis to cache database query results of common read-heavy user portfolio queries using a cache-aside strategy.

Configure Amazon CloudFront with both Minimum TTL and Maximum TTL set to 0 seconds in the cache behavior for static pricing assets to ensure clients always retrieve the latest data from the ALB.

Move the application's temporary short-lived static assets to an Amazon S3 bucket, and set up an S3 Lifecycle policy to transition them to Amazon S3 Standard-Infrequent Access (S3 Standard-IA) daily to reduce costs.

Configure Amazon Route 53 Latency Routing to distribute dynamic database queries directly to the Aurora read replicas to minimize latency, without configuring any health checks.

Show answer & explanation

Answer: Deploy an Amazon CloudFront distribution in front of the ALB, and configure a cache behavior for the stock price chart API path with a Minimum TTL and Maximum TTL of 60 seconds.; Configure Amazon ElastiCache for Redis to cache database query results of common read-heavy user portfolio queries using a cache-aside strategy.

Answer

The correct actions are to deploy an Amazon CloudFront distribution in front of the ALB with the cache behavior's Minimum and Maximum TTL set to 60 seconds, and to configure Amazon ElastiCache for Redis to cache database queries using a cache-aside strategy.

The correct combination uses Amazon CloudFront to cache the stock price charts at edge locations for 60 seconds, which directly matches the data update frequency and protects the origin servers from redundant request processing. Additionally, deploying Amazon ElastiCache for Redis provides a dedicated, in-memory cache to store database query results, resolving the CPU utilization spikes on the primary Aurora database.

Step-by-Step Solution

Analyze the bottlenecks and identify caching layers.

Identify that stock price charts update on a predictable 60-second interval, and database CPU spikes are due to repetitive read-heavy portfolio queries.

This allows separation of presentation caching (edge delivery) from application database query caching.

Implement edge caching using Amazon CloudFront.

Create a CloudFront distribution pointing to the ALB. Set the cache behavior for the charts API to have a TTL of 60 seconds.

This offloads repetitive chart requests from the ALB and EC2 servers, serving them from the edge for global users.

Implement database caching using Amazon ElastiCache.

Deploy an ElastiCache for Redis cluster. Update the application to check Redis before querying the Aurora database, and write query results back to Redis on a cache miss.

This dramatically reduces read-heavy query execution load on the Aurora database and decreases query latencies to sub-milliseconds.

Key Concept

Implementing a multi-tiered caching architecture using Amazon CloudFront for edge content delivery and Amazon ElastiCache for database query acceleration.

Estimated Time:3m 0s

Question 842Question →

A logistics company generates daily shipment tracking archives averaging $8\text{ MB}$ in size. These archives are stored in Amazon S3 Standard and are frequently accessed for the first $15$ days to verify delivery status. After $15$ days, the archives are rarely accessed and are permanently deleted after a total of $28$ days. Which lifecycle strategy is the most cost-effective for these archives?

Configure a lifecycle rule to transition the archives to S3 Standard-Infrequent Access (S3 Standard-IA) after

15

days, and expire them after

28

days.

Keep the archives in S3 Standard, and configure a lifecycle rule to expire the objects after

28

days.

Configure a lifecycle rule to transition the archives to S3 One Zone-Infrequent Access (S3 One Zone-IA) after

15

days, and expire them after

28

days.

Configure a lifecycle rule to transition the archives to Amazon S3 Glacier Flexible Retrieval after

15

days, and expire them after

28

days.

Show answer & explanation

Answer: Keep the archives in S3 Standard, and configure a lifecycle rule to expire the objects after $28$ days.

Answer

Keep the archives in S3 Standard, and configure a lifecycle rule to expire the objects after

28

days.

The correct strategy is to keep the archives in S3 Standard and delete them after

28

days. This is because transitioning the objects to S3 Standard-IA, S3 One Zone-IA, or S3 Glacier Flexible Retrieval after

15

days means the objects will spend only

13

days in those tiers before deletion. S3 Standard-IA and One Zone-IA have a

30

-day minimum storage duration charge, while S3 Glacier Flexible Retrieval has a

90

-day minimum storage duration charge. Deleting the objects early incurs a minimum storage duration charge penalty, making the transitions more expensive than keeping them in S3 Standard.

Step-by-Step Solution

Calculate the duration that objects would spend in the infrequent access tier.

The objects are transitioned after

15

days and deleted after

28

days. The duration in the transitioned tier is

28 - 15 = 13

days.

To evaluate if transitioning is cost-effective, we must check if the storage duration in the target tier meets its minimum storage duration constraint.

Compare the calculated duration against the minimum storage duration requirements for S3 Standard-IA, S3 One Zone-IA, and S3 Glacier.

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

30

days. S3 Glacier Flexible Retrieval requires a minimum of

90

days. The calculated duration (

13

days) is less than the minimum duration for all these tiers.

Amazon S3 charges a prorated deletion penalty for objects deleted before the minimum duration threshold of the tier.

Identify the most cost-effective strategy given the constraints.

Since transitioning to any cheaper tier incurs a minimum storage duration penalty, keeping the objects in S3 Standard for the entire

28

days and expiring them directly is the most cost-effective solution.

Avoiding the minimum storage duration penalty and transition fees makes S3 Standard the cheaper option overall.

Key Concept

S3 Lifecycle Minimum Storage Durations and Early Deletion Fees

Estimated Time:50s

Question 843Question →

A research institution is deploying a seismic data processing workload on AWS that requires high-performance computing (HPC) nodes. The nodes must exchange data frequently using Message Passing Interface (MPI) with node-to-node latency of less than $10\ \mu\text{s}$ . The workload is deployed on a fleet of memory-optimized Amazon EC2 instances managed by an Auto Scaling group. The Auto Scaling group registers the instances with a Network Load Balancer (NLB) that routes control plane traffic on port $9000$ . However, the application's internal status and health-reporting service runs on a separate monitoring daemon on port $8081$ . Which configuration combination should a solutions architect implement to ensure both optimal compute performance and accurate health monitoring of the instances?

Deploy the EC2 instances in a partition placement group. Configure the NLB target group health checks to use port

8081

Deploy the EC2 instances in a cluster placement group. Configure the NLB target group health checks to use port

8081

Deploy the EC2 instances in a cluster placement group. Configure the NLB target group health checks to use port

9000

Deploy the EC2 instances in a spread placement group. Configure the NLB target group health checks to use port

9000

Show answer & explanation

Answer: Deploy the EC2 instances in a cluster placement group. Configure the NLB target group health checks to use port $8081$ .

Answer

Deploy the EC2 instances in a cluster placement group and configure the NLB target group health checks to use port

8081

To achieve low-latency, high-throughput node-to-node communication required for MPI workloads, instances must be placed in close proximity. A cluster placement group packs instances close together within a single Availability Zone, enabling low-latency network performance. Additionally, because the application's health status is reported on port

8081

instead of the traffic port

9000

, the NLB target group health checks must be explicitly configured to query port

8081

. Otherwise, the load balancer will query the wrong port and fail to monitor the instance status correctly.

Step-by-Step Solution

Analyze the network requirements of the compute workload.

The workload uses MPI and requires low-latency, high-performance node-to-node communication (less than

10\ \mu\text{s}

latency).

Identifying the networking profile helps select the appropriate EC2 placement strategy.

Select the correct EC2 placement group type.

Choose a cluster placement group because it packs instances close together within a single Availability Zone, which minimizes latency and maximizes network performance.

Spread and partition placement groups are designed for fault isolation and introduce latency that is incompatible with tightly-coupled MPI requirements.

Identify the ports used for application traffic and health checks.

Application traffic is routed to port

9000

, while the health and status reporting daemon runs on port

8081

The load balancer needs to route user traffic and perform health probes on their respective correct ports.

Configure the target group health check settings.

Set the target group health check port to port

8081

instead of using the default traffic port (

9000

Probing port

9000

would check the traffic listener instead of the health-reporting daemon, which results in inaccurate health status reporting.

Key Concept

Tightly-coupled high-performance compute placement and custom health check port routing in AWS SAA architectures.

Question 844Question →

A media company hosts a popular news portal on AWS. The portal's database tier consists of an Amazon RDS for MySQL DB instance. During breaking news events, the portal experiences a massive surge in read traffic, causing high CPU utilization on the database and slow page loading times for readers. Writes to the database remain low. Which architectural modification should a solutions architect recommend to resolve the read performance bottleneck?

Create one or more Amazon RDS Read Replicas and configure the application to route read queries to the replica endpoints.

Enable a Multi-AZ deployment for the Amazon RDS DB instance and configure the application to load balance read queries between the primary and standby instances.

Migrate the database to Amazon DynamoDB and use the article publication date as the partition key for the table.

Migrate the database to Amazon DynamoDB and configure it in Provisioned Capacity mode with auto-scaling to handle the sudden spikes.

Show answer & explanation

Answer: Create one or more Amazon RDS Read Replicas and configure the application to route read queries to the replica endpoints.

Answer

Create one or more Amazon RDS Read Replicas and configure the application to route read queries to the replica endpoints.

Creating one or more Amazon RDS Read Replicas and routing read queries to them allows the application to offload the read-heavy workload from the primary DB instance. This effectively reduces CPU utilization on the primary instance and resolves the performance bottleneck with minimal architectural changes.

Step-by-Step Solution

Identify the performance bottleneck and traffic characteristics.

The bottleneck is high CPU utilization caused exclusively by a high volume of read queries, while write operations remain low.

This determines that the solution must scale read capacity independently of write capacity.

Select the appropriate scaling mechanism for relational database reads in AWS.

Amazon RDS Read Replicas are identified as the standard feature designed to offload read traffic from the primary instance.

Replicas are updated asynchronously and can be queried directly to scale read throughput.

Evaluate alternative options and eliminate non-viable architectural designs.

Multi-AZ standby instances cannot receive traffic, and DynamoDB migration with poor key design introduces write/read bottlenecks.

Ensures the proposed architecture aligns with official AWS constraints and best practices.

Key Concept

Scaling read performance in relational databases using Amazon RDS Read Replicas.

Estimated Time:50s

Question 845Question →

A solutions architect is designing a high-performance database tier for a web application. The application requires a caching layer to reduce read latency of frequently accessed database queries to sub-milliseconds. Additionally, the application requires a key-value database to store user session data that can scale dynamically to support high write volume without performance degradation. Which two actions should the solutions architect take to meet these requirements? (Select TWO.)

Select all that apply

Deploy an Amazon ElastiCache cluster to cache frequently accessed read queries.

Design Amazon DynamoDB tables using partition keys with high cardinality, such as a unique user ID.

Create Amazon RDS Read Replicas and configure them as the primary targets for automatic disaster recovery write failover.

Design Amazon DynamoDB tables using a monotonically increasing sequence or timestamp as the partition key.

Configure AWS Lambda functions to run continuously to buffer and write incoming session data to Amazon S3.

Show answer & explanation

Answer: Deploy an Amazon ElastiCache cluster to cache frequently accessed read queries.; Design Amazon DynamoDB tables using partition keys with high cardinality, such as a unique user ID.

Answer

Deploying an Amazon ElastiCache cluster to cache read queries and designing Amazon DynamoDB tables using a partition key with high cardinality.

The correct options are deploying an Amazon ElastiCache cluster and using partition keys with high cardinality for DynamoDB tables. ElastiCache is an in-memory caching service that reduces read latency to sub-milliseconds. High cardinality partition keys in DynamoDB ensure even write distribution across partitions, avoiding write throttling.

Step-by-Step Solution

Analyze the read caching requirement.

Identify that ElastiCache provides sub-millisecond caching to offload reads from databases.

The requirement specifies sub-millisecond read latency for frequently accessed database queries, which is a classic use case for an in-memory cache like ElastiCache.

Analyze the key-value database and write scaling requirements.

Identify that Amazon DynamoDB tables should be designed with high cardinality partition keys to prevent hot partitions.

DynamoDB is a high-performance key-value database. A partition key with high cardinality distributes the write throughput across multiple partition keys, preventing write throttling.

Key Concept

High-performing database architectures using in-memory caching (ElastiCache) and proper partitioning strategies in NoSQL databases (DynamoDB) to optimize read and write latency.

Question 846Question →

A digital animation studio stores two types of files in an Amazon S3 bucket:

* Render Input Assets: Average size of $12\text{ MB}$ . These files are generated daily and are needed for $15\text{ days}$ for potential re-rendering, after which they can be permanently deleted.
* Finished Master Videos: Average size of $8\text{ GB}$ . These files are accessed frequently during the first $30\text{ days}$ , accessed rarely for the next $60\text{ days}$ (but must be available immediately in milliseconds if requested), and then must be archived for $3\text{ years}$ for compliance. Retrieval within $12\text{ hours}$ is acceptable for archived files.

Which two actions should a solutions architect take to meet these requirements most cost-effectively?

Select all that apply

Create a lifecycle rule for the Render Input Assets prefix to expire the objects after

15\text{ days}

Create a lifecycle rule for the Finished Master Videos prefix to transition the objects to S3 Standard-IA after

30\text{ days}

, transition them to S3 Glacier Deep Archive after

90\text{ days}

, and expire them after

3\text{ years}

Create a lifecycle rule for the Render Input Assets prefix to transition the objects to S3 Standard-IA after

7\text{ days}

and expire them after

15\text{ days}

Create a lifecycle rule for the Finished Master Videos prefix to transition the objects to S3 Glacier Flexible Retrieval after

30\text{ days}

and keep them there for the remainder of the

3\text{ year}

period.

Create a lifecycle rule for the Render Input Assets prefix to transition the objects to S3 Glacier Instant Retrieval after

5\text{ days}

and expire them after

15\text{ days}

Show answer & explanation

Answer: Create a lifecycle rule for the Render Input Assets prefix to expire the objects after $15\text{ days}$ .; Create a lifecycle rule for the Finished Master Videos prefix to transition the objects to S3 Standard-IA after $30\text{ days}$ , transition them to S3 Glacier Deep Archive after $90\text{ days}$ , and expire them after $3\text{ years}$ .

Answer

The correct actions are to expire the Render Input Assets after 15 days without transitioning them, and to transition the Finished Master Videos to S3 Standard-IA after 30 days, to S3 Glacier Deep Archive after 90 days, and expire them after 3 years.

Expiring the Render Input Assets after 15 days is correct because keeping them in S3 Standard avoids the 30-day minimum storage charge penalty of S3 Standard-IA and the 90-day minimum storage charge penalty of S3 Glacier classes. Transitioning the Finished Master Videos to S3 Standard-IA after 30 days satisfies the millisecond latency and rare access requirements for the subsequent 60 days without incurring minimum duration penalties. Transitioning them to S3 Glacier Deep Archive after 90 days total meets the 12-hour recovery SLA for the remaining 3-year archive period at the lowest cost tier.

Step-by-Step Solution

Analyze the lifecycle requirements and file sizes of the Render Input Assets.

The files are

12\text{ MB}

and are deleted after

15\text{ days}

This determines if transitioning to other storage tiers is cost-effective under S3 minimum storage duration policies.

Evaluate S3 storage tier minimum duration constraints for the Render Input Assets.

S3 Standard-IA has a

30\text{ day}

minimum, and S3 Glacier tiers have a

90\text{ day}

180\text{ day}

minimum.

Since the assets are deleted at day 15, transitioning them to S3 Standard-IA or S3 Glacier would trigger minimum storage duration charges for the unused days, as well as transition charges. Thus, keeping them in S3 Standard and expiring them after 15 days is the most cost-effective approach.

Analyze the access pattern and compliance timeline of the Finished Master Videos.

They require frequent access for

30\text{ days}

, immediate access (millisecond latency) but rare usage for the next

60\text{ days}

(days 31 to 90), and long-term archiving for

3\text{ years}

with a

12\text{ hour}

retrieval SLA.

This maps the data to the appropriate storage classes based on latency, access frequency, minimum storage duration, and retrieval time.

Map the Finished Master Videos timeline to cost-optimized S3 storage tiers.

Transition to S3 Standard-IA after

30\text{ days}

(satisfies millisecond latency and rare access for 60 days, exceeding the 30-day minimum charge period). Transition to S3 Glacier Deep Archive after

90\text{ days}

total (satisfies the 12-hour archive retrieval requirement at the lowest storage cost for 3 years).

This matches the latency, cost, and retrieval SLA requirements of the master videos.

Key Concept

S3 Lifecycle management requires balancing transition costs and minimum storage durations against storage tier savings. S3 Standard-IA has a

30\text{ day}

minimum storage duration, and S3 Glacier Instant/Flexible Retrieval tiers have a

90\text{ day}

minimum storage duration, while S3 Glacier Deep Archive has a

180\text{ day}

minimum storage duration. Transitioning files that will be deleted before these minimum durations expire leads to cost penalties.

Question 847Question →

An enterprise application runs on Amazon EC2 instances and uses an Amazon RDS for PostgreSQL database. The database must be designed for high availability within a single AWS Region with a Recovery Time Objective (RTO) of under 60 seconds and a Recovery Point Objective (RPO) of zero. Additionally, the database must support scaling read traffic during peak monthly reporting periods without affecting write performance on the primary database instance. Which combination of database configurations should a solutions architect implement to meet these requirements? (Select TWO.)

Select all that apply

Deploy the RDS for PostgreSQL DB instance in a Multi-AZ configuration to enable synchronous replication and automatic failover.

Create RDS Read Replicas and configure the reporting application to use the read replica endpoints.

Configure an RDS Read Replica in another Availability Zone and manually promote it to primary during a database failover.

Deploy a single-AZ database instance and restore from Amazon S3 backups in a different Availability Zone during a failure.

Use Amazon Route 53 latency-based routing to distribute database write traffic between the primary DB instance and its read replicas.

Show answer & explanation

Answer: Deploy the RDS for PostgreSQL DB instance in a Multi-AZ configuration to enable synchronous replication and automatic failover.; Create RDS Read Replicas and configure the reporting application to use the read replica endpoints.

Answer

To meet both the high availability and read-scaling requirements, the solutions architect should deploy the Amazon RDS database in a Multi-AZ configuration to enable automatic failover and synchronous replication (ensuring an RTO of under 60 seconds and an RPO of zero), and create RDS Read Replicas to offload read-heavy reporting queries from the primary instance.

Deploying Amazon RDS for PostgreSQL in a Multi-AZ configuration ensures that data is synchronously replicated to a standby instance in another Availability Zone, allowing for automatic failover without data loss (RPO = 0) in under 60 seconds (RTO < 60s). Creating RDS Read Replicas allows the application to route read-intensive reporting traffic to the replicas, successfully offloading the primary write-serving instance.

Step-by-Step Solution

Analyze the high availability requirements (RTO under 60 seconds, RPO of zero).

Identify that synchronous replication and automatic failover are required, which matches the capabilities of RDS Multi-AZ deployments.

Single-AZ deployments with manual restores or asynchronous replication cannot meet the zero data loss (RPO = 0) and sub-minute recovery time (RTO < 60s) requirements.

Analyze the read scaling requirement (offloading peak monthly reporting traffic without affecting writes on the primary DB instance).

Identify that RDS Read Replicas must be deployed and configured as endpoints for the reporting application queries.

Read replicas utilize asynchronous replication to provide scalable read-only targets, preserving primary instance capacity for write operations.

Key Concept

Combining Amazon RDS Multi-AZ deployments for synchronous, zero-RPO high availability with Read Replicas for scalable, asynchronous read workloads.

Estimated Time:2m 0s

Question 848Question →

A logistics company hosts an inventory management system on Amazon EC2 instances located in a private subnet. The application frequently uploads large archive files to an Amazon S3 bucket in the same AWS Region. Currently, the traffic routes through a NAT Gateway, which is causing high NAT Gateway data processing charges. Which configuration change should a solutions architect implement to reduce data transfer costs most effectively?

Create a gateway VPC endpoint for Amazon S3 and associate it with the route table of the private subnet.

Create an interface VPC endpoint for Amazon S3 and route the traffic through the endpoint.

Deploy an EC2 NAT instance in a public subnet and route the S3 traffic through it instead of the NAT Gateway.

Assign public IP addresses to the EC2 instances and route the traffic directly through an Internet Gateway.

Show answer & explanation

Answer: Create a gateway VPC endpoint for Amazon S3 and associate it with the route table of the private subnet.

Answer

Create a gateway VPC endpoint for Amazon S3 and associate it with the route table of the private subnet.

The correct option is to create a gateway VPC endpoint for Amazon S3 and associate it with the route table of the private subnet. Gateway endpoints for Amazon S3 are free of charge and provide private, direct routing over the AWS internal network, completely bypassing the NAT Gateway and eliminating data processing charges.

Step-by-Step Solution

Identify the source of the high data transfer costs in the current architecture.

Traffic from private EC2 instances accessing Amazon S3 in the same region is passing through a NAT Gateway, which charges for data processing.

Understanding where the cost originates allows the solutions architect to target the specific network path for optimization.

Evaluate AWS network routing options that bypass the NAT Gateway for Amazon S3 traffic.

A gateway VPC endpoint can route traffic from the private subnet directly to Amazon S3 over the AWS internal network.

Gateway VPC endpoints for Amazon S3 are free of charge, eliminating both NAT Gateway processing fees and regional data transfer costs.

Update the routing configuration.

Associate the gateway VPC endpoint with the route table of the private subnet.

This dynamically updates the routing table with a route pointing S3 traffic directly to the gateway VPC endpoint.

Key Concept

Gateway VPC Endpoints for S3 provide cost-free, direct connectivity to Amazon S3 from private subnets, bypassing NAT Gateways and avoiding data processing fees.

Question 849Question →

A financial services company hosts an application on Amazon EC2 instances in a private subnet. The application downloads $1.5\text{ TB}$ of daily reports from an Amazon S3 bucket in the same AWS Region. The private subnet is configured with a route that sends all internet-bound traffic through a NAT Gateway. Which routing solution should a solutions architect implement to minimize data transfer costs?

Purchase a Compute Savings Plan to offset the NAT Gateway data processing charges.

Create a Gateway VPC endpoint for Amazon S3 and associate it with the route table of the private subnet.

Create an Interface VPC endpoint for Amazon S3 in the private subnet and update the route table.

Keep using the existing NAT Gateway to route the Amazon S3 traffic.

Show answer & explanation

Answer: Create a Gateway VPC endpoint for Amazon S3 and associate it with the route table of the private subnet.

Answer

Creating a Gateway VPC endpoint for Amazon S3 and associating it with the private subnet's route table is the most cost-effective option, as Gateway VPC endpoints are free of charge and keep traffic entirely within the AWS network.

Creating a Gateway VPC endpoint for Amazon S3 is the most cost-effective solution. Gateway VPC endpoints are provided at no additional cost, and all data transfers through them are free of charge. This allows private EC2 instances to communicate securely with Amazon S3 without routing traffic through a NAT Gateway, avoiding both NAT Gateway data processing and hourly charges.

Step-by-Step Solution

Identify the source, destination, and quantity of traffic: Amazon EC2 instances in a private subnet downloading

1.5\text{ TB}

of data daily from Amazon S3 in the same AWS Region.

The traffic is internal to the AWS Region and can be routed privately.

Traffic does not need to traverse the public internet to reach S3.

Evaluate the cost profiles of routing S3 traffic through a NAT Gateway, Interface VPC endpoint, and Gateway VPC endpoint.

NAT Gateways and Interface VPC endpoints incur hourly charges and data processing fees per gigabyte, while Gateway VPC endpoints for S3 are free of charge.

Using a Gateway VPC endpoint allows S3 traffic to bypass costly NAT Gateway data processing fees.

Update the subnet's route table to associate it with the new Gateway VPC endpoint.

Traffic destined for S3 will be automatically redirected to the gateway endpoint.

Route table associations direct traffic matching the S3 prefix list through the endpoint.

Key Concept

Gateway VPC Endpoints for S3 allow private instances to access S3 directly without going through a NAT Gateway or incurring data transfer/processing charges.

Estimated Time:1m 0s

Question 850Question →

A media company hosts a video transcoding application on Amazon EC2 instances located in a private subnet. The application downloads high-definition video files from an Amazon S3 bucket, transcodes them, and uploads the processed files back to the same S3 bucket. The application processes approximately $15\text{ TB}$ of raw video data daily. Currently, the EC2 instances access Amazon S3 through a NAT Gateway. A solutions architect needs to redesign the network routing to reduce data transfer costs. Which solution is the most cost-effective way to meet these requirements?

Create a Gateway VPC endpoint for Amazon S3 in the VPC and associate it with the route tables of the private subnet.

Keep the existing NAT Gateway and configure a NAT Instance in the public subnet to handle the S3 traffic.

Establish an AWS Site-to-Site VPN connection and route all S3 traffic through the on-premises network gateway.

Move the S3 bucket's data to the Amazon S3 Standard-Infrequent Access (S3 Standard-IA) storage class to lower overall costs.

Show answer & explanation

Answer: Create a Gateway VPC endpoint for Amazon S3 in the VPC and associate it with the route tables of the private subnet.

Answer

Create a Gateway VPC endpoint for Amazon S3 in the VPC and associate it with the route tables of the private subnet.

Creating a Gateway VPC endpoint for Amazon S3 allows instances in the private subnet to access S3 directly over the AWS network without traversing the NAT Gateway. Gateway endpoints do not incur any hourly or data processing charges, making this the most cost-effective and secure routing option.

Step-by-Step Solution

Analyze the current traffic pattern and identify that the EC2 instances in a private subnet are downloading

15\text{ TB}

of data daily from Amazon S3 through a NAT Gateway.

Identify that NAT Gateway data processing charges (

0.045\text{ USD}

per GB) for

15\text{ TB}

daily represent a significant and avoidable cost.

Traffic destined for AWS services like S3 or DynamoDB should not be routed through a NAT Gateway if a free alternative exists.

Evaluate alternative routing mechanisms that provide private connectivity to Amazon S3.

Compare Gateway VPC endpoints and Interface VPC endpoints.

Gateway VPC endpoints are free and do not charge for data processing, unlike Interface VPC endpoints or NAT Gateways.

Select and configure the Gateway VPC endpoint by adding it to the route tables of the private subnet.

Route table rules are updated so that traffic destined for S3 (via prefix lists) bypasses the NAT Gateway and goes directly through the VPC endpoint.

This removes the NAT Gateway data processing charges for S3 traffic entirely while keeping the traffic within the AWS private network.

Key Concept

Gateway VPC Endpoints for S3 eliminate NAT Gateway data processing charges for traffic between private EC2 instances and S3.

Estimated Time:1m 30s

Question 851Question →

A research organization is deploying a high-performance computing (HPC) cluster on AWS to process large-scale seismic simulation workloads. The cluster consists of multiple Amazon EC2 instances that require simultaneous, shared access to a storage volume. The storage solution must support parallel read/write operations, scale throughput up to $12\text{ GB/s}$ , and deliver sub-millisecond latencies.

Which combination of storage solutions and client configurations should a solutions architect select to meet these requirements? (Choose two.)

Select all that apply

Provision an Amazon FSx for Lustre file system with SSD storage using a persistent deployment model.

Mount the shared file system on the EC2 cluster using the native Lustre client to leverage parallel I/O.

Provision an Amazon EFS file system configured with Elastic throughput and mount it using the Network File System (NFSv4) client.

Provision an Amazon EBS gp3 volume with maximum provisioned IOPS and throughput, and enable Multi-Attach to share the volume across the EC2 instances.

Create an Amazon S3 bucket and configure an S3 Gateway VPC Endpoint to mount it as a shared block device.

Show answer & explanation

Answer: Provision an Amazon FSx for Lustre file system with SSD storage using a persistent deployment model.; Mount the shared file system on the EC2 cluster using the native Lustre client to leverage parallel I/O.

Answer

The correct answers are provisioning an Amazon FSx for Lustre file system with SSD storage and mounting the file system on the EC2 instances using the native Lustre client.

Amazon FSx for Lustre with SSD storage provides a high-performance parallel file system that is optimized for compute-heavy workloads like HPC, delivering sub-millisecond latencies and scaling to hundreds of gigabytes per second of throughput. Using the native Lustre client allows the EC2 instances to communicate directly and in parallel with the file system storage servers, maximizing throughput.

Step-by-Step Solution

Analyze the workload requirements: high-performance computing (HPC) seismic simulation cluster requiring shared storage access, parallel read/write,

12\text{ GB/s}

throughput, and sub-millisecond latencies.

Identify that the workload demands an HPC-optimized parallel file system rather than a general-purpose file or object storage.

General-purpose solutions cannot meet the sub-millisecond latency and high parallel throughput requirements of this simulation cluster.

Select the appropriate storage service.

Choose Amazon FSx for Lustre with SSD storage using a persistent deployment model.

FSx for Lustre is purpose-built for HPC, offering sub-millisecond latency, massive parallel throughput, and high IOPS.

Determine the client mounting mechanism.

Choose to mount the file system using the native Lustre client.

The native Lustre client is required to exploit the parallel architecture of the Lustre file system to achieve the high throughput target.

Key Concept

High-Performance storage solutions for HPC workloads using Amazon FSx for Lustre and parallel clients

Question 852Question →

A logistics tracking company operates a fleet management system on AWS with a write-intensive workload. The backend database is an Amazon RDS for PostgreSQL DB instance. The architecture team wants to design a resilient database setup that survives an Availability Zone outage with a Recovery Time Objective (RTO) of under 2 minutes and a Recovery Point Objective (RPO) of 0 (no data loss). In addition, they must offload heavy read-only reporting queries from the primary database to ensure write operations are unaffected. Which database configuration should a solutions architect recommend?

Deploy a Single-AZ Amazon RDS for PostgreSQL DB instance, and create a Read Replica in a different Availability Zone. Configure the application to promote the Read Replica to primary in the event of an outage.

Deploy an Amazon RDS for PostgreSQL Multi-AZ DB instance deployment. Configure Amazon Route 53 latency routing to distribute the reporting read queries between the primary instance and the standby instance in the secondary Availability Zone.

Deploy an Amazon RDS for PostgreSQL Multi-AZ DB cluster with one primary writer instance and two readable standby DB instances.

Deploy a Single-AZ Amazon RDS for PostgreSQL DB instance. Configure AWS Database Migration Service (AWS DMS) to continuously replicate data to a warm standby instance in another Availability Zone, and use this instance for reporting queries.

Show answer & explanation

Answer: Deploy an Amazon RDS for PostgreSQL Multi-AZ DB cluster with one primary writer instance and two readable standby DB instances.

Answer

Deploy an Amazon RDS for PostgreSQL Multi-AZ DB cluster with one primary writer instance and two readable standby DB instances.

Deploying an Amazon RDS Multi-AZ DB cluster meets all requirements. It uses semi-synchronous replication to write data to two standby DB instances in different Availability Zones, guaranteeing a Recovery Point Objective (RPO) of 0. It also provides automatic failover in the event of an outage in less than 2 minutes (typically 35 to 75 seconds), meeting the Recovery Time Objective (RTO). Finally, because both standby instances are readable, they can serve read traffic to handle read scaling, eliminating the need to provision separate read replicas.

Step-by-Step Solution

Analyze the recovery objectives (RTO < 2 minutes, RPO = 0) and scaling requirements (must scale read traffic).

Identify that the database configuration must support synchronous or semi-synchronous replication for RPO = 0, fast automated failover for RTO < 2 minutes, and active readable secondary nodes to scale reads.

This establishes the constraints that the chosen database solution must satisfy.

Evaluate Amazon RDS deployment options against these constraints.

A standard Multi-AZ DB instance deployment supports RPO = 0 and automatic failover, but its standby is passive and cannot serve reads. An RDS Multi-AZ DB cluster uses semi-synchronous replication (RPO = 0), performs automated failover in 35-75 seconds (RTO < 2 minutes), and contains two readable standby instances.

Comparing available RDS architectures helps select the one that meets both high availability and read scaling out-of-the-box.

Select the configuration that minimizes administrative overhead.

The Amazon RDS Multi-AZ DB cluster provides a single reader endpoint to load balance queries across the readable standbys without requiring manual setup of separate read replicas or promotion scripts.

Choosing the cluster option meets all performance and resiliency criteria with the least configuration effort.

Key Concept

Amazon RDS Multi-AZ DB clusters provide high availability, automatic failover, and read scaling by utilizing two readable standby DB instances across different Availability Zones.

Estimated Time:2m 0s

Question 853Question →

A media company is launching a live video streaming service where millions of viewers can post comments simultaneously during a broadcast. The application uses an Amazon DynamoDB table to store the comments. The table is designed with `broadcast_id` as the partition key and `comment_timestamp` as the sort key. During a stress test simulating 30,000 writes per second for a single live broadcast, the application experiences widespread write throttling, even though the table's provisioned write capacity is set to 35,000 Write Capacity Units (WCUs). Which database architecture modification should a solutions architect implement to resolve the performance bottleneck?

Modify the table schema to append a random integer suffix to the partition key value, distributing the write operations across multiple physical partitions, and query across all partition suffixes to retrieve the comments.

Change the table's partition key to `comment_timestamp` to ensure that write operations are distributed sequentially and evenly over time as comments are posted.

Migrate the database layer to an Amazon RDS for PostgreSQL database, configuring multiple read replicas in different Availability Zones to act as the primary automatic failover targets and absorb the high write throughput.

Switch the DynamoDB table from provisioned capacity mode to on-demand capacity mode to allow the database to automatically partition and scale to support the peak write throughput without throttling.

Show answer & explanation

Answer: Modify the table schema to append a random integer suffix to the partition key value, distributing the write operations across multiple physical partitions, and query across all partition suffixes to retrieve the comments.

Answer

Modify the table schema to append a random integer suffix to the partition key value (write sharding), distributing the write operations across multiple physical partitions.

The correct solution uses write sharding (adding a synthetic suffix to the partition key) to distribute write operations across multiple physical partitions. This design bypasses the physical limit of 1,000 WCUs per partition key in DynamoDB.

Step-by-Step Solution

Analyze the DynamoDB throttling behavior.

Determine that a single physical partition key is limited to a maximum of 1,000 Write Capacity Units (WCUs) per second.

Although the total table capacity is set to 35,000 WCUs, all writes for a single broadcast share the same `broadcast_id` partition key, targeting a single partition and causing throttling.

Implement write sharding by designing a synthetic partition key.

Append a random integer suffix (e.g., 1 to 30) to the `broadcast_id` partition key value.

This distributes the 30,000 writes per second across 30 distinct partition key values, ensuring each partition handles only about 1,000 writes per second, which stays within the single partition limit.

Adjust the application query logic.

Retrieve comments by querying across all suffix partitions and sorting/merging the results.

Because the data is split across multiple partition keys, the application must query all partitions to compile a complete list of comments.

Key Concept

DynamoDB partition design and write sharding to scale throughput.

Estimated Time:2m 0s

Question 854Question →

A gaming company is launching a multiplayer game and needs to design a telemetry ingestion pipeline. The game clients will send player state updates to the pipeline. The pipeline must ingest the updates, guarantee that updates are processed in the strict order they are received for each individual game session, and write them to Amazon DynamoDB. During peak usage, the pipeline is expected to receive $12,000$ messages per second, with an average message size of $2\text{ KB}$ . Which solution meets these requirements with the highest performance and the lowest operational overhead?

Configure an Amazon Kinesis Data Stream in On-Demand capacity mode. Write the telemetry messages to the stream using the game session ID as the partition key. Configure an AWS Lambda function to consume the messages from the stream and write them to Amazon DynamoDB.

Configure an Amazon SQS Standard queue to ingest the telemetry messages. Configure an AWS Lambda function to consume the messages from the queue and write them to Amazon DynamoDB.

Configure an Amazon Kinesis Data Stream in Provisioned capacity mode with

10

shards. Write the telemetry messages to the stream using the game session ID as the partition key. Configure an AWS Lambda function to consume the messages from the stream and write them to Amazon DynamoDB.

Configure an Amazon Kinesis Data Stream in On-Demand capacity mode. Write the telemetry messages to the stream using a monotonically increasing sequence number as the partition key. Configure an AWS Lambda function to consume the messages and write them to Amazon DynamoDB using the sequence number as the partition key.

Show answer & explanation

Answer: Configure an Amazon Kinesis Data Stream in On-Demand capacity mode. Write the telemetry messages to the stream using the game session ID as the partition key. Configure an AWS Lambda function to consume the messages from the stream and write them to Amazon DynamoDB.

Answer

Configure an Amazon Kinesis Data Stream in On-Demand capacity mode, using the game session ID as the partition key, and consume the stream with AWS Lambda to write the data to Amazon DynamoDB.

The correct solution uses Amazon Kinesis Data Streams in On-Demand capacity mode, partition key based on the game session ID, and AWS Lambda to write to DynamoDB. On-Demand mode automatically scales shard capacity to handle the peak write throughput of

24 \text{ MB/s}

and

12,000 \text{ records/s}

without operational management. Partitioning by game session ID ensures that updates for any given game session are routed to the same shard, guaranteeing sequential processing of updates.

Step-by-Step Solution

Calculate required throughput and record count.

Peak throughput is

12,000 \text{ messages/s} \times 2 \text{ KB} = 24 \text{ MB/s}

, and record count is

12,000 \text{ records/s}

To determine the required scale and shard count for the ingestion service.

Select ingestion service and capacity mode.

Amazon Kinesis Data Streams in On-Demand capacity mode is chosen.

On-Demand mode automatically scales up to 200 MB/s and 200,000 write records/s, which comfortably covers the

24 \text{ MB/s}

and

12,000 \text{ records/s}

workload without manual provisioning or operational overhead.

Determine partitioning strategy.

Use the game session ID as the partition key.

Using the game session ID ensures all messages for a specific session are mapped to the same shard and processed in order, meeting the strict ordering requirement while distributing workloads across shards.

Key Concept

Choosing high-performing ingestion services and scaling mechanisms while maintaining message ordering through partitioning.

Question 855Question →

A gaming company hosts a real-time multiplayer application on Amazon EC2 instances in a private subnet. The application uses a custom TCP-based protocol. The client applications are deployed globally, and several corporate clients require a pair of static IP addresses to configure their outbound firewall rules. The network architecture must support high throughput, minimize latency and jitter, and route traffic efficiently from global clients to the private backend. Which combination of services and configurations should a solutions architect use to meet these requirements? (Select TWO.)

Select all that apply

Create an AWS Global Accelerator accelerator and register a public Network Load Balancer as an endpoint.

Deploy a public Network Load Balancer in the AWS Region and register the private EC2 instances as targets.

Deploy an Application Load Balancer and configure Amazon Route 53 with latency-based routing policies pointing to the load balancer.

Deploy a public Network Load Balancer and configure stateful Network ACLs on the public subnets to whitelist the corporate clients' IP addresses.

Establish a single AWS Site-to-Site VPN connection between the clients' networks and the VPC to handle high-throughput traffic up to

10\text{ Gbps}

Show answer & explanation

Answer: Create an AWS Global Accelerator accelerator and register a public Network Load Balancer as an endpoint.; Deploy a public Network Load Balancer in the AWS Region and register the private EC2 instances as targets.

Answer

Deploy a public Network Load Balancer in the AWS Region, register the private EC2 instances as targets, and create an AWS Global Accelerator accelerator registering the Network Load Balancer as an endpoint.

To meet the requirements, the solutions architect should deploy a public Network Load Balancer (NLB) and an AWS Global Accelerator. An NLB handles high-throughput, low-latency TCP traffic and can route requests directly to EC2 instances in private subnets. AWS Global Accelerator provides two static Anycast IP addresses for the clients to whitelist in their firewalls, and it routes traffic over the high-speed AWS global network to the NLB, minimizing latency and jitter.

Step-by-Step Solution

Identify the protocol and throughput requirements.

The application uses a custom TCP-based protocol requiring high throughput.

This rules out Application Load Balancers (ALB) and CloudFront as they do not support custom TCP traffic (only HTTP/HTTPS/WebSockets).

Identify the client IP and routing requirements.

Global clients need static IP addresses to whitelist, and latency/jitter must be minimized.

AWS Global Accelerator provides two static Anycast IP addresses and routes TCP traffic over the AWS global backbone network to the nearest endpoint, minimizing latency and jitter.

Combine the load balancer and routing services.

Deploy a public Network Load Balancer (NLB) in the AWS Region to target the private EC2 instances, and register the NLB as an endpoint for AWS Global Accelerator.

This ensures high-throughput TCP routing to private backend instances while providing static entry IPs and low latency.

Key Concept

AWS Global Accelerator routes TCP/UDP traffic over the AWS global network to endpoints like Network Load Balancers, providing static IP addresses and low-latency performance.

Question 856Question →

An enterprise operates a data processing application deployed on Amazon EC2 instances in private subnets within an application VPC. The application needs to transfer $100\text{ TB}$ of data monthly to a central database VPC located in the same AWS Region. Additionally, the EC2 instances must upload $80\text{ TB}$ of processed log files monthly to an Amazon S3 bucket. Currently, both the database VPC traffic and the S3 traffic are routed through an AWS Transit Gateway and a NAT Gateway. A solutions architect needs to optimize the network architecture to minimize data transfer charges. Which two actions should the solutions architect recommend to meet these requirements most cost-effectively? (Select TWO.)

Select all that apply

Establish a VPC Peering connection between the application VPC and the database VPC, and update the route tables to route database traffic through the peering connection.

Create a Gateway VPC Endpoint for Amazon S3 in the application VPC, and associate it with the private subnet route tables to direct S3 traffic.

Replace the NAT Gateway with an Interface VPC Endpoint (AWS PrivateLink) for Amazon S3 to handle the log uploads.

Deploy an AWS Site-to-Site VPN connection between the application VPC and the database VPC to secure and route the database traffic.

Assign public IP addresses to the EC2 instances and configure them to transfer the data directly to the database VPC and Amazon S3 over the public internet.

Show answer & explanation

Answer: Establish a VPC Peering connection between the application VPC and the database VPC, and update the route tables to route database traffic through the peering connection.; Create a Gateway VPC Endpoint for Amazon S3 in the application VPC, and associate it with the private subnet route tables to direct S3 traffic.

Answer

Establish a VPC Peering connection between the application VPC and the database VPC to route database traffic, and create a Gateway VPC Endpoint for Amazon S3 in the application VPC to route S3 traffic.

Establishing a VPC Peering connection enables direct routing between the application and database VPCs without incurring the data processing fees of AWS Transit Gateway. Creating a Gateway VPC Endpoint for Amazon S3 directs the log upload traffic directly to S3 without traversing the NAT Gateway, eliminating the NAT Gateway data processing and hourly charges.

Step-by-Step Solution

Analyze database VPC data transfer costs

Database traffic (

100\text{ TB}

) currently routes over AWS Transit Gateway, which charges a processing fee of

0.02\text{ USD}

per

\text{GB}

. Routing via VPC Peering charges

0\text{ USD}

for data processing and uses the standard underlying network topology.

Identify the most cost-effective connection type between the application VPC and the database VPC.

Analyze S3 upload data transfer costs

S3 uploads (

80\text{ TB}

) currently route through a NAT Gateway, which charges a processing fee of

0.045\text{ USD}

per

\text{GB}

in addition to hourly charges. Setting up a Gateway VPC Endpoint is free and routes the traffic directly to S3.

Identify the most cost-effective endpoint type for routing S3 traffic from private subnets.

Key Concept

AWS Data Transfer Cost Optimization using VPC Peering and Gateway Endpoints

Question 857Question →

A media production studio uploads raw 4K video clips to Amazon S3. Each clip is approximately $2\text{ GB}$ in size. The clips are accessed frequently for editing and rendering during the first $25$ days after upload. After $25$ days, the clips are rarely accessed, but the studio must retain them for a total of $35$ days from the upload date to finalize client approvals, after which they can be permanently deleted. Which storage strategy is the most cost-effective?

Configure an S3 Lifecycle rule to transition the files to Amazon S3 Standard-Infrequent Access (S3 Standard-IA) after

25

days, and delete the files after

35

days.

Configure an S3 Lifecycle rule to transition the files to Amazon S3 Glacier Flexible Retrieval after

25

days, and delete the files after

35

days.

Retain the files in Amazon S3 Standard for the entire

35

days, and configure an S3 Lifecycle rule to delete the files after

35

days.

Configure an S3 Lifecycle rule to transition the files to Amazon S3 Intelligent-Tiering immediately, and delete the files after

35

days.

Show answer & explanation

Answer: Retain the files in Amazon S3 Standard for the entire $35$ days, and configure an S3 Lifecycle rule to delete the files after $35$ days.

Answer

Retain the files in Amazon S3 Standard for the entire

35

days, and configure an S3 Lifecycle rule to delete the files after

35

days.

Retaining the files in S3 Standard for the entire

35

days is the most cost-effective strategy. Because the files are only kept for

10

days after the frequent access period, transitioning them to S3 Standard-IA or S3 Glacier Flexible Retrieval triggers minimum billing duration penalties (

30

days for S3 Standard-IA and

90

days for S3 Glacier). These penalties, along with transition request fees, make the transition options more expensive than simply keeping the files in S3 Standard for the entire lifecycle.

Step-by-Step Solution

Calculate the cost of keeping files in S3 Standard for the entire duration.

For

1\text{ GB}

of data stored for

35\text{ days}

, the cost is approximately

\frac{35}{30} \times \$0.023 = \$0.0268

Establishes the baseline cost for the non-tiered storage strategy.

Calculate the cost of transitioning to S3 Standard-IA at day

25

and deleting at day

35

25\text{ days}

in S3 Standard cost

\frac{25}{30} \times \$0.023 = \$0.0192

. Transitioning to S3 Standard-IA for the remaining

10\text{ days}

triggers a

30

-day minimum billing duration. The S3 Standard-IA cost is

\frac{30}{30} \times \$0.0125 = \$0.0125

. The total is

\$0.0192 + \$0.0125 = \$0.0317

per GB.

Determines the impact of the

30

-day minimum storage duration requirement for S3 Standard-IA.

Calculate the cost of transitioning to S3 Glacier Flexible Retrieval at day

25

and deleting at day

35

25\text{ days}

in S3 Standard cost

\$0.0192

. Transitioning to S3 Glacier Flexible Retrieval for the remaining

10\text{ days}

triggers a

90

-day minimum billing duration. The Glacier cost is

\frac{90}{30} \times \$0.0036 = \$0.0108

. The total is

\$0.0192 + \$0.0108 = \$0.0300

per GB (excluding transition fees).

Determines the impact of the

90

-day minimum storage duration requirement for S3 Glacier Flexible Retrieval.

Compare the total storage costs of all options.

The S3 Standard-only strategy (

\$0.0268

per GB) is cheaper than transitioning to S3 Standard-IA (

\$0.0317

per GB) or transitioning to S3 Glacier Flexible Retrieval (

\$0.0300

per GB).

Identifies the storage strategy that minimizes overall AWS charges.

Key Concept

S3 Lifecycle policies must account for minimum storage duration charges in colder storage classes (30 days for S3 Standard-IA, 90 days for S3 Glacier Flexible Retrieval) to avoid cost penalties on short-lived data.

Estimated Time:2m 0s

Question 858Question →

A company is planning to migrate a workload to AWS. The workload consists of two main components:
1. A front-end web application that must run continuously on Amazon EC2 instances to handle a predictable, steady baseline traffic 24/7.
2. A background analytics batch job that is highly fault-tolerant, can run at any time of the night, and can be safely interrupted without losing progress.

Which combination of Amazon EC2 purchasing options will provide the most cost-effective solution to meet these requirements? (Select TWO.)

Select all that apply

Purchase EC2 Instance Savings Plans to cover the baseline capacity of the web application EC2 instances.

Use Spot Instances to run the fault-tolerant background analytics batch jobs.

Use AWS Lambda to host the continuous 24/7 web application tier to eliminate idle instance costs.

Purchase Compute Savings Plans to apply discounts to the Amazon RDS database instances used by the application.

Deploy a DynamoDB table with Provisioned Capacity Mode to handle the highly unpredictable, spiky data storage needs of the batch jobs.

Show answer & explanation

Answer: Purchase EC2 Instance Savings Plans to cover the baseline capacity of the web application EC2 instances.; Use Spot Instances to run the fault-tolerant background analytics batch jobs.

Answer

Using EC2 Instance Savings Plans for the steady-state web application EC2 instances, and Spot Instances for the fault-tolerant background analytics batch jobs.

The correct answer combines EC2 Instance Savings Plans for the predictable, continuous 24/7 web tier workload and Spot Instances for the interruptible, fault-tolerant background batch jobs. This combination leverages the deep discounts of Savings Plans for baseline needs and Spot Instances for flexible, batch workloads to minimize overall compute costs.

Step-by-Step Solution

Analyze the web application requirement.

The web application runs continuously (24/7) with predictable, steady traffic, which requires a compute purchasing option that provides discounts for consistent usage.

Identify the steady-state compute requirement to apply the most cost-effective commitment-based purchasing strategy.

Analyze the background batch job requirement.

The batch job is fault-tolerant, runs nightly, and can tolerate interruptions, making it a perfect candidate for utilizing unused capacity at a deep discount.

Identify the flexibility and interruptibility of the workload to safely apply Spot Instance discounts.

Select the appropriate AWS purchasing options.

EC2 Instance Savings Plans cover the baseline EC2 instances, and Spot Instances cover the batch jobs.

Map the workload characteristics to EC2 Instance Savings Plans (for baseline) and Spot Instances (for interruptible batch jobs).

Key Concept

Selecting cost-optimized Amazon EC2 purchasing options based on workload patterns (steady-state vs. fault-tolerant/flexible).

Question 859Question →

A solutions architect is deploying a high-performance computing (HPC) application on Amazon EC2 instances. The application nodes require closely-coupled, low-latency node-to-node communication. Additionally, the instances must be registered with an Application Load Balancer (ALB) for health monitoring on a custom port 8080, while the application itself serves web traffic on port 80. Which combination of steps should the solutions architect take to meet these performance and health check requirements? (Select TWO.)

Select all that apply

Launch the EC2 instances in a cluster placement group.

Configure the Application Load Balancer target group health check port to 8080.

Launch the EC2 instances in a spread placement group.

Configure the Application Load Balancer target group health check port to use the default traffic-port.

Launch the EC2 instances in a partition placement group.

Show answer & explanation

Answer: Launch the EC2 instances in a cluster placement group.; Configure the Application Load Balancer target group health check port to 8080.

Answer

Launch the EC2 instances in a cluster placement group and configure the Application Load Balancer target group health check port to 8080.

The correct options are to launch the EC2 instances in a cluster placement group and to configure the Application Load Balancer target group health check port to 8080. A cluster placement group is ideal for applications that need low network latency and high network throughput. Setting the target group health check port explicitly to 8080 ensures the load balancer queries the correct custom port where the health monitoring endpoint is running.

Step-by-Step Solution

Analyze the network latency requirement.

The workload requires closely-coupled, low-latency node-to-node communication.

This requirement points directly to a cluster placement group, which places instances physically close together on the same underlying hardware within a single Availability Zone.

Analyze the application health check port requirement.

The application listens on port 80 for traffic, but health checks must be performed on custom port 8080.

The target group must be configured with a health check port override of 8080 to ensure the ALB queries the monitoring endpoint rather than port 80.

Key Concept

High-performance EC2 networking using placement groups and configuring Application Load Balancer health checks for non-standard ports.

Question 860Question →

An organization is deploying a real-time cluster analysis application on several Amazon EC2 instances. The instances must communicate with each other with minimal network latency and maximum network throughput. Which configuration should be selected for the EC2 instances to achieve this performance?

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

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

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

Deploy the instances behind an Application Load Balancer with target group health checks configured on port 80 while the application listens on port 8080.

Show answer & explanation

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

Answer

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

The correct configuration is to launch the instances in a cluster placement group. A cluster placement group is a logical grouping of instances within a single Availability Zone. This configuration enables workloads to achieve the low-latency network performance and high throughput necessary for tightly-coupled node-to-node communication.

Step-by-Step Solution

Identify the primary requirement of the workload, which is low-latency, high-throughput node-to-node communication for cluster analysis.

The application requires tightly-coupled compute nodes.

This helps determine the optimal EC2 placement strategy.

Evaluate EC2 placement group options to find the one optimized for low latency.

Cluster placement groups place instances physically close together on the same underlying hardware within a single Availability Zone, providing 10 Gbps or higher network performance.

Choosing a cluster placement group satisfies the performance requirements.

Key Concept

EC2 Placement Groups

Estimated Time:1m 0s

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