SAP-C02 Mock Exam 94 — 25 Questions

Question 1

A company is building a new microservices-based application on AWS using Amazon ECS with Fargate. The application has a frontend service, an order service, and a payment service. Services communicate synchronously via REST APIs. The company expects variable traffic and wants to ensure that failures in one service do not cascade to others. Which solution should a Solutions Architect recommend?

Accepted Answer

Implement retry logic with exponential backoff, circuit breakers, and timeouts in each service's client code.. Option D is correct because implementing circuit breakers, retries, and timeouts is a standard pattern to prevent cascading failures. Option A is wrong because synchronous communication is already in place; adding an API Gateway doesn't prevent cascading failures. Option B is wrong because adding more instances does not protect against service failures. Option C is wrong because converting to asynchronous messaging is a larger architectural change and may not be suitable for all interactions.

Answer

Use Amazon API Gateway in front of each service to throttle requests and protect against traffic spikes.

Answer

Convert all inter-service communication to asynchronous messaging using Amazon SQS or SNS.

Answer

Deploy multiple instances of each service across multiple Availability Zones and use an Application Load Balancer.

Question 2

A company is designing a new application on AWS that processes real-time IoT sensor data from thousands of devices. The data must be ingested, processed, and stored for analysis. The company wants to use a serverless architecture to reduce operational overhead. The processing includes filtering, aggregation, and transformation. Which solution should a Solutions Architect recommend?

Accepted Answer

Use AWS IoT Core to ingest data, use IoT rules to route data to Kinesis Data Analytics for real-time processing, and store results in S3.. Option C is correct because IoT Core is purpose-built for IoT device ingestion, rules engine can process and route data, Kinesis Data Analytics provides real-time SQL processing, and S3 stores results. Option A is wrong because SQS is not a streaming ingestion service. Option B is wrong because Lambda functions triggered by SQS may have concurrency limits and are not ideal for high-throughput streaming. Option D is wrong because Kinesis Data Firehose delivers data in batches, not real-time processing.

Answer

Use Amazon Kinesis Data Streams to ingest data, use Kinesis Data Firehose to deliver data to S3, and use Athena for queries.

Answer

Use Amazon Kinesis Data Streams to ingest data, trigger a Lambda function for processing, and store results in DynamoDB.

Answer

Use Amazon SQS to ingest sensor data, trigger a Lambda function for processing, and store results in DynamoDB.

Question 3

A company has a centralized logging solution using Amazon OpenSearch Service (successor to Amazon Elasticsearch Service) in a central logging account. Application logs from hundreds of EC2 instances across multiple accounts are shipped to the OpenSearch cluster via Amazon Kinesis Data Firehose. The security team requires that all log data be encrypted at rest and in transit. The logging account has a KMS key used to encrypt the OpenSearch cluster and the Firehose delivery stream. Recently, the security team noticed that some log deliveries are failing with 'AccessDenied' errors. The CloudWatch Logs delivery to Firehose is configured correctly. What is the most likely cause of the failure?

Accepted Answer

The KMS key policy does not grant the Firehose delivery stream permission to use the key for encryption.. The most likely cause is that the KMS key policy does not grant the Firehose delivery stream permission to use the key for encryption. Even though the CloudWatch Logs subscription filter is correctly configured to send data to Firehose, Firehose must have kms:Decrypt and kms:GenerateDataKey permissions on the KMS key to encrypt the data at rest in the OpenSearch cluster and in transit. Without these permissions, Firehose cannot encrypt the data, resulting in 'AccessDenied' errors.

Answer

The CloudWatch Logs subscription filter does not have permissions to write to Firehose.

Answer

The OpenSearch cluster's access policy denies write access from the Firehose stream.

Answer

The Firehose delivery stream does not have a TLS certificate configured.

Question 4

A retail company is migrating its on-premises e-commerce platform to AWS. The platform consists of a load-balanced web tier, an application tier, and a MySQL database. The company wants to modernize the database by migrating to Amazon Aurora MySQL. The migration must have minimal downtime and support rollback. The database is 2 TB in size and has high write activity. The company has set up an AWS Direct Connect connection. Which approach should the company take to migrate the database with minimal downtime?

Accepted Answer

Use AWS SCT to convert the schema, then use AWS DMS with a full load and ongoing replication (CDC) task to keep the target in sync until cutover.. Option B is correct because AWS DMS with a full load and ongoing change data capture (CDC) task enables continuous replication of high-write activity from the on-premises MySQL database to Amazon Aurora MySQL, minimizing downtime by keeping the target synchronized until cutover. The CDC component captures incremental changes after the full load, allowing a near-zero downtime migration with the ability to roll back by stopping replication and reverting to the source.

Answer

Use AWS SCT to convert the schema, then use AWS DMS with a full load task to migrate the data.

Answer

Use mysqldump to export the database, transfer the dump via AWS Direct Connect, and import into Aurora MySQL.

Answer

Use the AWS Schema Conversion Tool (SCT) to convert the schema, then set up an Aurora Replica from the on-premises source using native MySQL replication.

Question 5

A retail company is migrating its e-commerce platform from a monolith running on a single on-premises server to AWS. The current application consists of a Java-based web server, a MySQL database, and a caching layer using Redis. The company wants to modernize the architecture by adopting microservices, using serverless where possible, and minimizing operational overhead. The migration must be completed within six months with minimal disruption to ongoing operations. The solutions architect proposes the following initial steps: containerize the Java application and run it on Amazon ECS with Fargate, migrate the MySQL database to Amazon Aurora Serverless v2, and replace Redis with Amazon ElastiCache for Redis Serverless. However, the team is concerned about the complexity of the migration and the potential for downtime. Which recommendation should the solutions architect make to address these concerns?

Accepted Answer

Use the Strangler Fig pattern to incrementally replace monolith functionality with microservices, routing traffic to new services as they are built.. Option C is correct because the Strangler Fig pattern allows the team to incrementally replace specific functionalities of the monolithic e-commerce platform with microservices, routing traffic to the new services as they are built. This minimizes disruption and downtime by avoiding a big-bang cutover, and it aligns with the goal of modernizing to microservices and serverless within the six-month timeline. The pattern leverages an existing ingress controller (e.g., an Application Load Balancer with path-based routing) to gradually shift requests from the monolith to new services running on Amazon ECS with Fargate, while the database and caching layers are migrated separately with minimal impact.

Answer

Rewrite the entire application as microservices from scratch and deploy them in a new AWS environment. Cut over all traffic at once after testing.

Answer

Use AWS Blue/Green deployment for the monolith to reduce downtime, then migrate to microservices after the deployment is stable.

Answer

Perform a lift-and-shift migration of the monolith to EC2 instances, then gradually refactor into microservices over the next year.

Question 6

A company is designing a new multi-region disaster recovery solution for a critical application running on AWS. The primary region is us-east-1. The application uses Amazon RDS for MySQL with Multi-AZ, and runs on EC2 instances behind an ALB. The RPO must be less than 5 minutes, and RTO less than 30 minutes. The company wants to minimize costs when the DR solution is not in use. Which solution should a Solutions Architect recommend?

Accepted Answer

Set up an RDS MySQL cross-Region read replica in us-west-2. Keep a standby EC2 environment with Auto Scaling configured to scale from 0 to minimum instances using a CloudWatch alarm on health checks. Use Route 53 failover routing to switch DNS to us-west-2.. Option A is correct because RDS cross-Region replication provides RPO of seconds, and using a standby EC2 environment with Auto Scaling configured for minimum zero instances (scaling based on DNS or health checks) minimizes cost. Option B is wrong because Multi-AZ does not provide cross-Region failover. Option C is wrong because read replicas are for read scaling, not DR failover, and cannot be promoted quickly. Option D is wrong because S3 is not a database; this doesn't meet RPO/RTO.

Answer

Use RDS MySQL with cross-Region read replicas in us-west-2. Use a hot standby EC2 environment with a single instance. Use Route 53 failover routing.

Answer

Back up RDS MySQL to S3 using automated snapshots and copy them to us-west-2. Use EC2 instances with S3-mounted volumes to serve traffic from the backup.

Answer

Use RDS MySQL with Multi-AZ in us-east-1 and a second Multi-AZ deployment in us-west-2. Keep EC2 instances running in us-west-2 behind an ALB with cross-Region load balancing.

Question 7

A large enterprise has a multi-account AWS environment managed through AWS Organizations. The central networking team uses a transit gateway in a shared services VPC to connect all VPCs. The security team requires that all traffic between VPCs be inspected by a third-party firewall appliance that is deployed in an auto-scaling group in the shared services VPC. The firewall appliance is configured as a Gateway Load Balancer (GWLB) endpoint. The transit gateway has a route table that sends all inter-VPC traffic to the GWLB endpoint. Recently, the operations team noticed that some applications are experiencing high latency and packet loss when communicating across VPCs. Upon investigation, they found that the firewall appliance is not scaling properly. Which solution should be implemented to ensure that the firewall can handle the traffic load and maintain low latency?

Accepted Answer

Enable cross-zone load balancing on the Gateway Load Balancer to distribute traffic evenly across all firewall instances in all Availability Zones.. Option A is correct because Gateway Load Balancers (GWLB) by default do not distribute traffic across Availability Zones (AZs); they only send traffic to targets in the same AZ as the GWLB endpoint. Enabling cross-zone load balancing allows the GWLB to distribute traffic evenly across all healthy firewall instances in all AZs, which prevents overloading a single AZ's instances and ensures the auto-scaling group can scale effectively based on overall load, reducing latency and packet loss.

Answer

Increase the size of the firewall instances to larger instance types to handle more traffic per instance.

Answer

Create additional Gateway Load Balancer endpoints in each Availability Zone and use a separate transit gateway route table for each AZ.

Answer

Configure the auto-scaling group to use a step scaling policy based on network throughput.

Question 8

A company is designing a new real-time analytics platform that ingests data from thousands of IoT devices. The devices send JSON messages every second to an AWS IoT Core topic. The messages must be processed and stored in Amazon S3 for long-term analysis. The processing includes enrichment by calling a third-party API to add location data. The company expects the workload to vary significantly, with peak traffic of 100,000 messages per second. The solution must be cost-effective and minimize operational overhead. The current architecture uses a Lambda function subscribed to the IoT topic, which processes each message and writes to S3. However, during initial testing, the Lambda function frequently times out due to the third-party API latency, causing message loss. What should the company do to resolve this issue while meeting all requirements?

Accepted Answer

Configure the IoT rule to write messages to an Amazon SQS queue. Then use a Lambda function with reserved concurrency to poll the queue and process messages at a controlled rate. Option D is correct because decoupling the ingestion from the processing using an SQS queue allows the Lambda function to poll messages at a controlled rate, preventing timeouts from third-party API latency. The SQS queue acts as a buffer, absorbing traffic spikes of up to 100,000 messages per second, and Lambda can process messages asynchronously without loss. This approach is cost-effective and minimizes operational overhead by leveraging managed services.

Answer

Increase the Lambda function timeout to 15 minutes and memory to 10240 MB

Answer

Use Amazon Kinesis Data Firehose to buffer data and write to S3, then trigger a Lambda function to enrich data asynchronously

Answer

Enable Provisioned Concurrency on the Lambda function to reduce cold starts

Question 9

A company runs a critical web application on Amazon EC2 instances in an Auto Scaling group behind an Application Load Balancer (ALB). The application stores session state in an Amazon ElastiCache for Redis cluster. Recently, the operations team noticed that during traffic spikes, the ALB returns 5xx errors and the application becomes slow. CloudWatch metrics show that the Redis cluster's CPU utilization reaches 100% and memory usage is high. The Auto Scaling group scales out, but the new instances take several minutes to warm up and become healthy. The company needs to improve the application's ability to handle traffic spikes with minimal impact on performance. Which solution should the company implement?

Accepted Answer

Enable cluster mode for the Redis cluster and add more shards.. Enabling cluster mode for the Redis cluster and adding more shards horizontally partitions the data across multiple nodes, distributing both CPU and memory load. This directly addresses the 100% CPU and high memory utilization during traffic spikes, allowing the cluster to handle more concurrent requests without performance degradation. Cluster mode also provides linear scalability, which is essential for a critical web application experiencing variable traffic.

Answer

Configure ElastiCache Auto Scaling to automatically add nodes when CPU utilization exceeds 75%.

Answer

Enable Multi-AZ replication for the Redis cluster.

Answer

Increase the instance size of the Redis cluster to a larger node type.

Question 10

A financial services company is migrating its trading platform to AWS. The platform consists of hundreds of microservices deployed in containers using Amazon ECS with Fargate launch type. Each service has its own IAM role for fine-grained permissions. The security team requires that all ECS tasks use a specific VPC (vpc-12345) and cannot run in any other VPC. During a recent audit, it was discovered that some tasks are running in a different VPC (vpc-67890). The solutions architect must implement a preventive control to ensure that ECS tasks only run in the approved VPC. The company uses AWS Organizations and has Service Control Policies (SCPs) in place. What should the solutions architect do?

Accepted Answer

Create an SCP that denies ecs:RunTask and ecs:CreateService unless the networkConfiguration.awsvpcConfiguration.subnets are in the approved VPC.. Option C is correct because Service Control Policies (SCPs) in AWS Organizations provide a preventive control that applies across all accounts in the organization. By denying ecs:RunTask and ecs:CreateService unless the subnets specified in networkConfiguration.awsvpcConfiguration belong to the approved VPC (vpc-12345), the SCP enforces the VPC constraint at the organization level, preventing any task from launching in a non-approved VPC regardless of individual IAM roles or account configurations.

Answer

Tag the approved VPC and use IAM policies to allow ECS actions only when the VPC tag matches.

Answer

Add an IAM policy to each ECS task role that denies the action if the VPC is not the approved one.

Answer

Use AWS Config rules to detect tasks running in non-approved VPCs and trigger a remediation action.

Question 11

A company runs a containerized microservices application on Amazon ECS with Fargate launch type. The application consists of a frontend service and a backend service. The backend service is CPU-intensive and experiences high load during business hours. The operations team observes that the frontend service sometimes returns 503 errors during peak load. The team has already configured an ECS service auto scaling policy for the backend service based on average CPU utilization with a target value of 70%. The backend service is currently running 4 tasks, and the frontend is running 2 tasks. The errors seem to correlate with the backend scaling up. Which solution should the team implement to improve the application's performance and reduce errors?

Accepted Answer

Update the backend service auto scaling policy to use a combination of CPU and memory utilization metrics with a step scaling policy, and increase the cooldown period to allow tasks to stabilize before additional scaling actions.. Option A is correct because the 503 errors during backend scale-up are likely caused by the backend tasks not being fully ready to handle traffic immediately after launch. By using a combination of CPU and memory utilization metrics with a step scaling policy, the team can make scaling decisions more responsive to actual load patterns. Increasing the cooldown period prevents additional scaling actions from being triggered prematurely, giving new tasks time to stabilize and reducing the window where the backend is overwhelmed, which in turn reduces frontend timeouts.

Answer

Reduce the target CPU utilization for the backend auto scaling policy from 70% to 50% to trigger scaling earlier and keep CPU lower.

Answer

Change the backend service from Fargate to EC2 launch type and use larger instance types to provide more CPU capacity.

Answer

Increase the desired count of the frontend service to 4 tasks to handle more requests and reduce the load on the backend service.

Question 12

A company has a complex AWS environment with multiple accounts and VPCs. The company wants to ensure that all outbound traffic from VPCs goes through a centralized inspection VPC for security monitoring. The company uses AWS Transit Gateway. Which solution should be implemented?

Accepted Answer

Create a Transit Gateway with route tables. Attach the inspection VPC as a central hub. Configure the route tables of the transit gateway to point the default route (0.0.0.0/0) to the inspection VPC attachment. Then attach all other VPCs and configure their route tables to send traffic to the Transit Gateway.. Option D is correct because it uses AWS Transit Gateway with centralized route tables to force all outbound traffic from attached VPCs through the inspection VPC. By configuring the Transit Gateway route table with a default route (0.0.0.0/0) pointing to the inspection VPC attachment, all outbound traffic from other VPCs is routed to the inspection VPC for security monitoring before leaving the network. This design meets the requirement of a single, centralized inspection point without requiring VPC peering or per-VPC firewall deployments.

Answer

Deploy AWS Network Firewall in each VPC and configure routing to send outbound traffic through the firewall.

Answer

Use VPC peering to connect all VPCs to the inspection VPC and configure routes.

Answer

Use Route 53 Resolver to forward all outbound DNS queries to the inspection VPC.

Question 13

A company has a global AWS environment with multiple VPCs in different regions. The company uses AWS Transit Gateway to connect VPCs in the same region, but they need to interconnect VPCs across regions. The network team wants a solution that provides transitive routing across regions with minimal latency and operational overhead. Which solution should be implemented?

Accepted Answer

Use Transit Gateway peering attachments between Transit Gateways in different regions.. Transit Gateway peering attachments enable transitive routing between Transit Gateways in different AWS regions, providing low-latency connectivity over the AWS global network without requiring VPN or Direct Connect. This solution minimizes operational overhead because AWS manages the peering connection and route propagation automatically, allowing VPCs attached to different Transit Gateways to communicate across regions.

Answer

Set up a VPN connection between Transit Gateways in different regions.

Answer

Use AWS Direct Connect to connect the Transit Gateways in different regions.

Answer

Create VPC peering connections between all VPCs in different regions.

Question 14

A media company is designing a new video transcoding pipeline on AWS. Raw video files (up to 10 GB each) are uploaded by users to an S3 bucket. Each upload must be transcoded into multiple formats (MP4, WebM, HLS) and stored in another S3 bucket. The transcoding job can take up to 30 minutes per file. The company needs a solution that is cost-effective and can handle hundreds of concurrent uploads. The operations team wants to minimize maintenance. Which solution should a Solutions Architect recommend?

Accepted Answer

Use S3 event notifications to invoke a Lambda function that submits a job to AWS Elemental MediaConvert for each file.. Option B is correct because AWS Elemental MediaConvert is a fully managed, serverless media transcoding service designed for high-volume, multi-format video processing. Using S3 event notifications to invoke a Lambda function that submits a job to MediaConvert offloads the transcoding complexity, scales automatically to handle hundreds of concurrent uploads, and requires no infrastructure maintenance, making it both cost-effective and operationally minimal.

Answer

Use S3 event notifications to invoke an AWS Lambda function that performs transcoding and stores results.

Answer

Use an Auto Scaling group of EC2 instances with transcoding software installed. Configure S3 events to send messages to an SQS queue, which the instances poll.

Answer

Use S3 event notifications to trigger an AWS Step Functions workflow that runs an ECS Fargate task for each file.

Question 15

A global e-commerce company is designing a new recommendation engine on AWS. The engine processes user behavior data (clicks, purchases) from multiple sources in real time and updates recommendations stored in Amazon DynamoDB. The data stream can reach 100,000 events per second. The solution must be highly available and process events with minimal latency (< 1 second). The company wants to use a managed streaming service and a real-time processing framework. Which solution should a Solutions Architect recommend?

Accepted Answer

Use Amazon Kinesis Data Streams to ingest events, process them in real time with Amazon Kinesis Data Analytics using SQL, and write results to DynamoDB.. Amazon Kinesis Data Streams can ingest up to 100,000 events per second with shard-level scaling, and Kinesis Data Analytics (SQL) provides sub-second processing latency for real-time transformations. Writing directly to DynamoDB from the analytics application meets the <1 second latency requirement while maintaining high availability through Kinesis's built-in replication across three Availability Zones.

Answer

Use Amazon Kinesis Data Firehose to ingest events, transform data with Lambda, and deliver to DynamoDB.

Answer

Use Amazon Kinesis Data Streams to ingest events, use AWS Lambda to process each event, and write results to DynamoDB.

Answer

Use Amazon MSK (Managed Streaming for Apache Kafka) to ingest events, process them with Apache Spark Streaming on Amazon EMR, and write to DynamoDB.

Question 16

A company is designing a data processing pipeline for real-time analytics. The pipeline ingests data from IoT devices that send JSON messages via MQTT to AWS IoT Core. The messages must be processed in real-time to detect anomalies and the results must be stored in Amazon S3 for later analysis. The company currently uses a Lambda function to process each message, but as the number of devices grows, the Lambda function is being throttled due to concurrency limits. The company needs a solution that scales to handle thousands of devices per second without losing messages. The processed data must be available in S3 within 1 minute of ingestion. Which architecture should the company use?

Accepted Answer

Use AWS IoT Core rules to route messages to Amazon Kinesis Data Firehose, which writes raw data to S3. Then use Amazon Kinesis Data Analytics to read from S3 and perform real-time anomaly detection, writing results back to S3 via Firehose.. Option C is correct because Kinesis Data Analytics provides real-time SQL processing, and Kinesis Data Firehose delivers the results to S3 with low latency. Option A is wrong because Lambda concurrency limits will still be hit; SQS does not solve concurrency limits. Option B is wrong because Kinesis Data Streams alone does not process data; Lambda would still be needed and could be throttled. Option D is wrong because S3 cannot process streaming data in real-time; S3 Select is for querying objects.

Answer

Send the IoT messages to an Amazon SQS queue and have Lambda poll the queue in batches to reduce the number of concurrent invocations.

Answer

Store the raw messages in an S3 bucket and use S3 Select to query the data for anomalies periodically.

Answer

Ingest the messages into Amazon Kinesis Data Streams with multiple shards, and use a Lambda function to process records from the stream. Increase the Lambda concurrency limit.

Question 17

A company runs a critical web application on EC2 instances in an Auto Scaling group across three Availability Zones. The application uses an Application Load Balancer (ALB) with a target group that has health checks configured. Recently, the operations team noticed that during a deployment, the ALB started routing traffic to a new instance before it was ready to serve requests, causing a brief period of errors. The team wants to ensure that new instances are fully initialized and ready before receiving traffic. The application takes about 30 seconds to start up. Current health check settings: health check protocol HTTP, path /, interval 30 seconds, timeout 5 seconds, healthy threshold 2, unhealthy threshold 2. The deployment uses the Auto Scaling group's instance refresh feature. Which of the following is the MOST effective way to prevent traffic from being sent to instances that are not ready?

Accepted Answer

Implement a lifecycle hook in the Auto Scaling group that waits for the instance to signal readiness. Also, configure the target group health check with a longer interval and a higher healthy threshold to ensure the instance is fully operational.. Option B is correct because the lifecycle hook pauses the instance until it is ready, and the health check with a longer grace period ensures the ALB does not consider the instance healthy until it passes. Option A is wrong because increasing the interval does not prevent early traffic; the instance might still pass the first check before being ready. Option C is wrong because the warm-up time in instance refresh is for the Auto Scaling group to launch instances, not for the application to become ready. Option D is wrong because pre-warming is not a service; it's a manual process.

Answer

Increase the health check interval to 60 seconds and the healthy threshold to 5.

Answer

Use the Auto Scaling group's instance refresh feature with a warm-up time of 60 seconds.

Answer

Use AWS Global Accelerator to pre-warm the endpoints before directing traffic.

Question 18

A company is designing a new microservices platform on AWS. The platform consists of 50 microservices, each running in its own Amazon ECS service on AWS Fargate. The services communicate via REST APIs. The company wants to implement a service mesh to handle traffic routing, observability, and security (mTLS). They also need to meet compliance requirements that all traffic between services must be encrypted and logged. The solution must be fully managed and reduce operational overhead. After implementing the service mesh, the operations team notices that latency between services has increased by 20%, and some services are experiencing connection timeouts. The team has enabled mTLS and distributed tracing. Which course of action should the team take to diagnose and resolve the latency issues?

Accepted Answer

Check the Envoy proxy resource limits in the App Mesh configuration and increase the CPU and memory allocated to the sidecar proxies.. Option A is correct because AWS App Mesh can inject Envoy sidecar proxies, and increasing the proxy resources can reduce latency. Option B (replacing with VPC peering) removes the service mesh benefits. Option C (using Cloud Map) does not address latency. Option D (converting to Lambda) is a major redesign.

Answer

Use AWS Cloud Map for service discovery instead of App Mesh.

Answer

Replace the service mesh with VPC peering and security groups, and use direct HTTP calls.

Answer

Convert the microservices to AWS Lambda functions and use API Gateway.

Question 19

A company runs a high-traffic e-commerce platform on AWS. The application consists of a web tier, an application tier, and a database tier using Amazon RDS for PostgreSQL with Multi-AZ. During a recent sales event, the database experienced high CPU utilization and read replicas were added to offload read traffic. However, the application team noticed that some product detail pages were showing stale data (prices and inventory levels) even though the primary database had the correct data. The application uses read replicas for read queries. The solutions architect investigated and found that the read replica lag was minimal (under 1 second). The application uses Django ORM with default transaction isolation. What is the most likely cause of the stale data?

Accepted Answer

The application is reading from read replicas, which are eventually consistent, and the data may be stale if the replica has not yet applied changes from the primary.. Option C is correct. The issue is that the application is reading from read replicas, which are eventually consistent. Even with minimal lag, there is a chance of reading stale data after a write to the primary. The application should read from the primary for critical data like prices and inventory. Option A is incorrect because Multi-AZ failover is for high availability, not read consistency. Option B is incorrect because Aurora I/O-Optimized is not applicable here (they are using RDS PostgreSQL). Option D is incorrect because increasing instance size would reduce CPU but not solve stale reads.

Answer

The Multi-AZ standby was promoted due to a failover, causing a brief inconsistency.

Answer

The application is not using a connection pool, causing connections to be established to different replicas.

Answer

The read replica is using a different storage type (Aurora I/O-Optimized) than the primary.

Question 20

A media company runs a video processing pipeline on AWS. Videos are uploaded to an S3 bucket, which triggers an AWS Lambda function that transcodes the video into multiple formats using FFmpeg. The transcoding job runs on the Lambda function with a 15-minute timeout. Recently, the company started receiving 4K videos that take more than 15 minutes to transcode. The Lambda function times out, and the video is not processed. The company wants to process these large videos without increasing the Lambda timeout and without rewriting the entire pipeline. What should the solutions architect do?

Accepted Answer

Replace the Lambda function with AWS Elemental MediaConvert job triggered by S3 events.. Option A is correct. AWS Elemental MediaConvert is a managed service designed for video transcoding. It can handle large files and long-running jobs. The pipeline can be modified to trigger a MediaConvert job instead of a Lambda function. Option B is incorrect because Lambda functions have a maximum execution time of 15 minutes; increasing memory does not extend timeout. Option C is incorrect because using a larger Lambda function still has the 15-minute limit. Option D is incorrect because Step Functions orchestrate Lambda functions but do not extend the individual Lambda timeout.

Answer

Increase the Lambda function memory to the maximum to improve performance and reduce processing time.

Answer

Use AWS Step Functions to call multiple Lambda functions in parallel to process chunks of the video.

Answer

Use a Lambda function with a larger ephemeral storage to handle the video file.