DVA-C02 Development with AWS Services — 50 Questions

Question 1

A developer has an AWS Lambda function that processes messages from an Amazon SQS queue. The function is configured with a batch size of 10, reserved concurrency of 5, and a timeout of 5 minutes. The SQS queue has a large backlog, and CloudWatch metrics show high throttling (Throttles) for the Lambda function. The function is idempotent and can process up to 100 messages in a single invocation. What is the MOST effective way to increase throughput without increasing the reserved concurrency?

Accepted Answer

Increase the batch size to 100.. Increasing the batch size to 100 allows each Lambda invocation to process up to 100 messages from the SQS queue instead of the current 10. Since the function is idempotent and can handle 100 messages per invocation, this change maximizes the number of messages processed per invocation without altering the reserved concurrency of 5. With a batch size of 100, each of the 5 concurrent invocations can process up to 100 messages, yielding a potential throughput of 500 messages per invocation cycle, which directly reduces the backlog and throttling by consuming messages faster.

Answer

Increase the reserved concurrency to 10.

Answer

Reduce the batch size to 1.

Answer

Enable the SQS queue to use long polling.

Question 2

A developer has an AWS Lambda function that processes messages from an Amazon SQS standard queue. The function is idempotent and currently has a batch size of 10. The developer wants to increase throughput and increases the batch size to 100. After the change, CloudWatch metrics show a significant increase in throttles and the queue backlog is growing. The function's reserved concurrency is set to 10. What is the most effective action to resolve the throttling and improve throughput?

Accepted Answer

Increase the reserved concurrency of the Lambda function. Increasing the reserved concurrency from 10 to a higher value directly addresses the root cause of throttling. With a batch size of 100, each invocation processes more messages, but the function's reserved concurrency of 10 limits the maximum number of concurrent executions to 10. This means the Lambda service can only invoke the function 10 times at once, regardless of how many messages are in the queue. By raising reserved concurrency, you allow more concurrent invocations to handle the larger batches, reducing throttling and improving throughput.

Answer

Increase the memory allocation of the Lambda function

Answer

Switch the SQS queue to a FIFO queue

Answer

Decrease the batch size back to 10

Question 3

A developer is using AWS X-Ray to trace a serverless application. The application uses an AWS Lambda function to query a DynamoDB table. The trace shows that the DynamoDB subsegment takes a significant portion of the total response time. The developer wants to reduce the DynamoDB query latency. Which service should the developer integrate with the Lambda function to achieve the lowest latency for repeated read queries?

Accepted Answer

DynamoDB Accelerator (DAX). DynamoDB Accelerator (DAX) is a fully managed, highly available, in-memory cache for DynamoDB that delivers up to 10x read performance improvement by reducing response times from milliseconds to microseconds for repeated read queries. By integrating DAX with the Lambda function, the developer can cache the results of frequent DynamoDB queries directly in memory, bypassing the read capacity units and the underlying storage engine, which directly addresses the latency bottleneck shown in the X-Ray trace.

Answer

Amazon ElastiCache for Redis

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DynamoDB Global Tables

Answer

DynamoDB Streams

Question 4

A developer is building a serverless application using AWS Step Functions to orchestrate multiple AWS Lambda functions. One of the Lambda functions occasionally fails due to a transient error. The developer wants the Step Functions execution to automatically retry the failed task up to three times with exponential backoff. Which configuration should the developer set in the Step Functions state machine definition?

Accepted Answer

Use the Amazon States Language (ASL) Retry field in the Task state definition.. Option B is correct because the Amazon States Language (ASL) provides a native Retry field within a Task state definition that allows you to specify retry policies, including a maximum retry count and exponential backoff. This is the intended mechanism for handling transient failures in Step Functions without requiring custom code or external retry logic.

Answer

Add a Retry clause in the Lambda function's configuration with a maximum retry count of 3.

Answer

Wrap the Lambda function invocation in a custom while loop within the function code.

Answer

Use the Amazon States Language Catch field in the Task state to redirect to a retry logic.

Question 5

A developer is building a serverless application that processes orders. An order is placed and an event is published to an Amazon SNS topic. The SNS topic has multiple subscribers, including an SQS queue for order processing and a Lambda function for sending notifications. The developer wants to ensure that the SQS queue receives all messages reliably, even if the processing Lambda function fails temporarily. Which configuration should the developer set?

Accepted Answer

Enable a dead-letter queue on the SQS queue. A dead-letter queue (DLQ) on the SQS queue ensures that messages that cannot be processed successfully after the configured number of retries (maxReceiveCount) are moved to a separate queue for later analysis or reprocessing. This prevents message loss when the Lambda function fails temporarily, as the SQS queue will continue to receive messages from SNS reliably, and only messages that exceed the retry limit are redirected to the DLQ.

Answer

Enable SNS delivery retries for HTTP endpoints

Answer

Set the SQS queue's visibility timeout to a value greater than the Lambda function's processing time

Answer

Configure the SNS topic to use server-side encryption

Question 6

A developer is building a REST API using Amazon API Gateway and AWS Lambda. The API receives a large number of requests with duplicate payloads from the same client within a short time window. To reduce Lambda invocations and improve performance, the developer wants to return the previously computed response for identical requests based on a unique client ID in the header. How can the developer achieve this using API Gateway features?

Accepted Answer

Enable API Gateway caching on the stage and configure the client ID header as a cache key parameter. Set a cache TTL of 5 minutes.. Option A is correct because API Gateway caching allows you to store responses for a configurable TTL and use the client ID header as a cache key parameter. This means that when a request with the same client ID arrives within the TTL window, API Gateway returns the cached response directly without invoking the Lambda function, reducing invocations and improving performance.

Answer

Configure a usage plan with a quota and throttle settings to limit requests per client ID.

Answer

Use request validation to reject requests that have the same client ID within 5 minutes.

Answer

Reduce the Lambda function's batch size to 1 and implement caching logic inside the function using an external cache like ElastiCache.

Question 7

A developer is building a RESTful API using Amazon API Gateway (HTTP API) and AWS Lambda. The API receives a large number of requests with duplicate payloads within a short time window. To improve performance and reduce costs, the developer wants to ensure that if the same request (based on a unique client ID) is sent within 5 minutes, the Lambda function is not invoked again, and the previously calculated response is returned. Which API Gateway feature should the developer use?

Accepted Answer

Enable API caching on the stage with a TTL of 300 seconds and configure the client ID as a cache key parameter.. Option A is correct because API Gateway's caching feature stores responses from your endpoint for a specified time-to-live (TTL). By setting the TTL to 300 seconds (5 minutes) and configuring the client ID as a cache key parameter, API Gateway will use the client ID to uniquely identify requests. If a request with the same client ID arrives within the TTL window, API Gateway returns the cached response without invoking the Lambda function, reducing costs and improving performance.

Answer

Enable request validation to reject duplicate requests.

Answer

Configure a usage plan with a throttle rate to limit requests from each client.

Answer

Enable stage variables to store the previous response.

Question 8

A developer is building a RESTful API using Amazon API Gateway and AWS Lambda. The API needs to support custom domain names with SSL/TLS certificates. The developer has created the custom domain name in API Gateway and uploaded the certificate to AWS Certificate Manager (ACM) in the same region. However, when accessing the custom domain, users get an SSL error. What is the most likely cause?

Accepted Answer

The custom domain name's DNS record does not point to API Gateway's regional domain name.. The most likely cause is that the custom domain name's DNS record does not point to API Gateway's regional domain name. When using a custom domain name with API Gateway, you must create a DNS record (typically a CNAME or A record using Route 53 alias) that maps your custom domain to the API Gateway-generated regional domain name (e.g., d-xxxxx.execute-api.region.amazonaws.com). Without this correct DNS mapping, the SSL/TLS handshake fails because the certificate presented by API Gateway does not match the domain name the client is connecting to, resulting in an SSL error.

Answer

The certificate was not issued by a trusted certificate authority.

Answer

The API Gateway API is not deployed to a stage that is mapped to the custom domain name.

Answer

The certificate is in the wrong region relative to the API Gateway regional endpoint.

Question 9

A developer is building a system that reads messages from an Amazon SQS queue, processes them, and stores results in an Amazon DynamoDB table. The developer wants to use a managed service to coordinate the processing steps, including error handling and retry logic, without provisioning any servers. Which AWS service should the developer use?

Accepted Answer

AWS Step Functions. AWS Step Functions is a serverless orchestration service that lets you coordinate multiple AWS services into a workflow. It directly supports error handling, retry logic, and conditional branching, making it ideal for managing the processing steps of messages from SQS through to DynamoDB without provisioning any servers.

Answer

Amazon Simple Workflow Service (SWF)

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AWS Glue

Answer

Amazon MQ

Question 10

A developer is building a serverless application using AWS Lambda and Amazon API Gateway. The API must support different HTTP methods (GET, POST, PUT, DELETE) for the same resource path. The developer wants to define the API in a single Lambda function that can handle all methods without additional mapping configuration. Which Lambda integration type should the developer use?

Accepted Answer

Lambda proxy integration. Lambda proxy integration (option A) is correct because it allows a single Lambda function to handle all HTTP methods (GET, POST, PUT, DELETE) for the same resource path without additional mapping configuration. In this integration type, API Gateway passes the entire client request (method, headers, query parameters, body) as a JSON event to the Lambda function, and the function must return a response in a specific format that includes status code, headers, and body. This eliminates the need for manual mapping templates or method-specific configurations.

Answer

Lambda custom integration

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AWS service integration

Answer

HTTP integration

Question 11

A developer is building a serverless application that processes user-submitted images. The images are uploaded to an S3 bucket, which triggers an AWS Lambda function that creates a thumbnail and stores it in another S3 bucket. The developer notices that sometimes the Lambda function is invoked multiple times for a single image upload. What should the developer configure to ensure idempotent processing?

Accepted Answer

Implement a DynamoDB table to track processed objects.. Option C is correct because S3 event notifications can occasionally deliver duplicate events (at-least-once semantics). By storing the unique object key (or ETag) in a DynamoDB table with a TTL, the Lambda function can check if the object has already been processed and skip duplicate invocations, ensuring idempotent processing.

Answer

Enable S3 event notifications with a suffix filter.

Answer

Use an SQS queue to decouple S3 events.

Answer

Increase the Lambda function's timeout.

Question 12

A developer is building a serverless application that uses an Amazon SQS FIFO queue to process orders. The orders must be processed exactly once and in the order they are received. The developer uses an AWS Lambda function as the consumer. Despite using a FIFO queue, the developer notices that some orders are being processed more than once. What is the most likely cause of this behavior?

Accepted Answer

The Lambda function is not deleting messages from the queue after successful processing, so they become visible again after the visibility timeout.. The most likely cause is that the Lambda function is not deleting messages from the SQS FIFO queue after successful processing. By default, Lambda does not automatically delete messages; it relies on the function code to call the `DeleteMessage` API. If the function fails to delete a message, it remains in the queue and becomes visible again after the visibility timeout expires, leading to duplicate processing even though the queue is FIFO.

Answer

The Lambda function is configured with a batch size greater than 1, causing multiple messages to be processed at once and some to be duplicated.

Answer

The SQS queue has a message retention period set too low, causing messages to be deleted automatically and re-queued.

Answer

The Lambda function's execution role does not have permission to delete messages from the queue.

Question 13

A developer is building a multi-region application using Amazon DynamoDB global tables. The application needs to read data from a replica table in a different region shortly after a write in the primary region. The developer notices that reads sometimes return stale data. Which of the following explains this behavior?

Accepted Answer

Global tables use asynchronous replication, introducing unavoidable replication lag.. Amazon DynamoDB global tables use asynchronous replication to propagate writes from one region to all other replica tables. This means that after a write in the primary region, there is an inherent replication lag (typically sub-second but can be higher under load or network issues) before the change is visible in other regions. The developer observes stale reads because the read is hitting a replica that has not yet received the update, which is expected behavior for eventually consistent reads on global tables.

Answer

The developer must use DynamoDB Streams to capture changes and replicate them separately.

Answer

The developer must enable strong consistency reads on the replica table.

Answer

The global table must be configured with write forwarding.

Question 14

A developer is migrating a monolithic application to a microservices architecture on AWS. The application uses a relational database. The developer wants to use Amazon RDS for the database and needs to ensure that each microservice can only access its own set of tables. Which approach should the developer take?

Accepted Answer

Use RDS with IAM database authentication and create database users with limited privileges for each microservice.. Option B is correct because IAM database authentication allows the developer to create database users with granular, table-level privileges using standard SQL GRANT statements, ensuring each microservice can only access its own set of tables. By combining IAM roles with database user credentials, the developer can enforce least-privilege access without sharing a single database user across services. This approach directly addresses the requirement for per-microservice table isolation while leveraging RDS's native authentication and authorization capabilities.

Answer

Create a single RDS instance with a separate database per microservice.

Answer

Use RDS in a VPC and restrict network access per microservice using security groups.

Answer

Use Amazon RDS Proxy to control access.

Question 15

A developer is running a web application on multiple Amazon EC2 instances behind an Application Load Balancer (ALB). The application needs to store user session state that must be available across all instances. The session data is small and temporary but must survive individual instance failures. Which AWS service should the developer use to store this session state?

Accepted Answer

Store session state in an Amazon ElastiCache cluster. Amazon ElastiCache (e.g., using Redis or Memcached) provides a centralized, in-memory data store that is external to the EC2 instances. This allows all instances behind the ALB to read and write the same session state, ensuring consistency across the fleet. Because the data is stored in a managed cluster, it survives individual instance failures and is ideal for small, temporary session data that requires low-latency access.

Answer

Store session state in the /tmp directory of each EC2 instance

Answer

Use an Amazon SQS queue to persist session data

Answer

Store session state in an Amazon S3 bucket

Question 16

A developer is building a web application that uses Amazon DynamoDB as the database. The application needs to store user session data and must support eventual consistency reads for most use cases, but strongly consistent reads for critical operations. The developer wants to minimize costs. Which read capacity unit (RCU) configuration should the developer use?

Accepted Answer

Use on-demand capacity mode to pay per request, avoiding provisioned capacity costs.. Option A is correct because on-demand capacity mode charges per request (read/write), eliminating the need to provision fixed RCUs. For a session store with mixed consistency requirements, on-demand is cost-effective when traffic is unpredictable or low, as you only pay for actual reads and writes. Eventually consistent reads consume half the RCUs of strongly consistent reads, but on-demand pricing automatically accounts for this difference without manual configuration.

Answer

Use provisioned capacity with 1 RCU per item, since eventually consistent reads consume half the RCUs.

Answer

Use provisioned capacity with sufficient RCUs to handle strongly consistent reads, as they consume the same as eventually consistent.

Answer

Use provisioned capacity with enough RCUs for peak traffic, and use DynamoDB Accelerator (DAX) for caching.

Question 17

A developer is building a serverless application using AWS SAM. The application includes an Amazon API Gateway endpoint with a Lambda function that processes user uploads. The developer wants to enable API caching in the development stage to speed up repeated requests, but disable caching in the production stage. What is the most efficient way to achieve this?

Accepted Answer

Configure caching in the SAM template using the CacheClusterEnabled property and use CloudFormation conditions to enable it only in the dev stage.. Option A is correct because AWS SAM extends AWS CloudFormation, allowing you to use CloudFormation conditions to conditionally enable the `CacheClusterEnabled` property on the `AWS::ApiGateway::Stage` resource. By defining a condition that evaluates to true only for the dev stage (e.g., based on a parameter like `StageName`), you can enable caching in dev and disable it in prod within a single SAM template, avoiding duplication and manual steps.

Answer

Create two separate SAM templates, one for dev with caching and one for prod without.

Answer

Enable caching in the API Gateway console after each deployment for the dev stage.

Answer

Use a custom CloudFormation resource to toggle caching based on a parameter.

Question 18

A developer is building a serverless application using AWS Lambda and Amazon DynamoDB. The application needs to store large JSON documents (up to 1 MB) and retrieve them by a primary key. The documents are updated frequently. Which DynamoDB feature should the developer consider to optimize performance and cost for storing and retrieving these large items?

Accepted Answer

Use Amazon S3 to store the documents and store only the S3 key in DynamoDB.. Option A is correct because DynamoDB has a 400 KB item size limit, so storing large JSON documents (up to 1 MB) directly in DynamoDB is not possible. By storing the documents in Amazon S3 (which supports objects up to 5 TB) and keeping only the S3 object key in DynamoDB, the developer can efficiently retrieve the document via the primary key while avoiding DynamoDB's size constraint. This pattern also reduces DynamoDB read/write capacity unit consumption, lowering cost for frequently updated large items.

Answer

Enable DynamoDB Accelerator (DAX) to cache the large items.

Answer

Use DynamoDB Transactions to atomically update the items.

Answer

Enable DynamoDB Streams to capture changes to the items.

Question 19

A developer is building a serverless application using AWS Step Functions. The workflow must execute hundreds of thousands of short-lived tasks per day, each taking less than 30 seconds. The tasks need to run in parallel, and a small number of duplicate executions are acceptable. Which type of Step Functions workflow should the developer choose?

Accepted Answer

Express Workflow. Express Workflows are designed for high-volume, short-duration (under 5 minutes) event-processing workloads, executing hundreds of thousands of state transitions per second with at-least-once semantics. Since the tasks are short-lived (under 30 seconds), run in parallel, and tolerate a small number of duplicate executions, Express Workflow is the correct choice because it offers lower cost and higher throughput than Standard Workflow, which guarantees exactly-once execution and is better suited for long-running, auditable workflows.

Answer

Standard Workflow

Answer

AWS Lambda function with synchronous invocation

Answer

Amazon Simple Workflow Service (SWF)

Question 20

A developer is using the AWS Serverless Application Model (SAM) to define a serverless application with an API Gateway endpoint. The developer wants to enable API caching only in the development stage to speed up testing, but disable it in the production stage to ensure data freshness. What is the most efficient way to achieve this with SAM?

Accepted Answer

Use AWS SAM parameters with a condition to set CacheClusterEnabled based on the stage parameter.. AWS SAM parameters allow you to define a stage parameter (e.g., 'dev' or 'prod') and use a condition to conditionally set the `CacheClusterEnabled` property on the `AWS::Serverless::Api` resource. This is the most efficient approach because it uses a single template and SAM's built-in intrinsic functions (like `Fn::Equals`) to toggle caching based on the deployment stage, avoiding separate templates or post-deployment custom resources.

Answer

Deploy two separate SAM templates, one for each stage.

Answer

Use a custom resource to toggle caching after deployment.

Answer

Enable caching globally and configure a usage plan with a quota for production.