DVA-C02 Troubleshooting and Optimization Practice Test 15 — 15 Questions

Question 1

A developer has deployed an AWS Lambda function that is triggered by an Amazon S3 event. The function processes image files and stores metadata in an Amazon DynamoDB table. CloudWatch metrics show that the function's error count has increased. The developer checks CloudWatch Logs and sees errors related to insufficient memory. The function is configured with 128 MB of memory. What should the developer do to resolve the errors?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Increase the function's memory to 256 MB or higher.. The error is caused by insufficient memory, which directly impacts the CPU and execution resources allocated to the Lambda function. Increasing the memory allocation to 256 MB or higher provides more CPU throughput and memory, resolving the out-of-memory errors without requiring code changes.

Answer

Increase the function's timeout to 30 seconds.

Answer

Reduce the size of the images being uploaded to S3.

Answer

Move the DynamoDB write operation to an asynchronous invocation.

Question 2

A developer is monitoring an AWS Lambda function that is triggered by an Amazon SQS queue. The function's CloudWatch metrics show a high number of throttles. The function has a reserved concurrency of 10 and the SQS queue has a large backlog of messages. The function processes each message in about 2 seconds and has a timeout of 60 seconds. Which action will most effectively reduce the throttles and increase throughput?

Accepted Answer

Increase the reserved concurrency of the Lambda function to 50. The high throttles indicate that the Lambda function's reserved concurrency of 10 is insufficient to handle the incoming messages from the SQS queue. By increasing reserved concurrency to 50, you allow more concurrent executions, which reduces throttling and increases throughput. The function's 2-second processing time and 60-second timeout are not the bottleneck; the concurrency limit is.

Answer

Increase the batch size in the SQS event source mapping to 100

Answer

Increase the function timeout to 120 seconds

Answer

Decrease the reserved concurrency to 5

Question 3

A developer is troubleshooting an AWS Lambda function that experiences high latency for the first few invocations after being idle. The function is written in Python and uses a large library (e.g., Pandas). The function connects to an RDS database in a VPC. What is the most effective way to reduce the latency for the first invocation after idle?

Accepted Answer

Enable provisioned concurrency on the function.. Provisioned concurrency keeps a specified number of execution environments initialized and ready to respond immediately, eliminating the cold start latency that occurs after a period of idle time. This is the most direct solution for reducing latency on the first invocation after idle, especially for functions with large libraries like Pandas that take significant time to load.

Answer

Increase the function's memory allocation to 3008 MB.

Answer

Move the large library to a Lambda layer.

Answer

Replace the RDS database with Amazon DynamoDB.

Question 4

A developer notices that an AWS Lambda function, configured to access an Amazon RDS database in the same VPC, is timing out. The function has a 30-second timeout. CloudWatch Logs show that the function starts execution but never reaches the database. The VPC configuration includes private subnets without a NAT gateway. The RDS database is in the same VPC. What is the most likely cause of the timeout?

Accepted Answer

The security group of the RDS database does not allow inbound traffic from the Lambda function's security group.. The Lambda function is timing out when trying to connect to the RDS database, which is in the same VPC. The most likely cause is that the RDS database's security group does not have an inbound rule allowing traffic from the Lambda function's security group on the database port (e.g., 3306 for MySQL, 5432 for PostgreSQL). Without this rule, the TCP connection attempt is silently dropped or rejected, causing the Lambda function to wait until its 30-second timeout expires.

Answer

The Lambda function does not have internet access because it is in a VPC without a public IP.

Answer

The Amazon RDS database is not publicly accessible and the Lambda function cannot resolve the database endpoint.

Answer

The VPC does not have a VPC endpoint for Amazon RDS, and the Lambda function cannot access the database through the NAT gateway.

Question 5

A developer notices that an AWS Lambda function processing S3 events is being retried frequently due to throttling errors from Amazon DynamoDB. The function writes records to a DynamoDB table and has reserved concurrency set to 100. The DynamoDB table uses on-demand capacity mode. What should the developer do to reduce retries and improve overall throughput?

Accepted Answer

Implement exponential backoff and retry in the Lambda function code for DynamoDB API calls.. Implementing exponential backoff and retry in the Lambda function code for DynamoDB API calls directly addresses the throttling errors. Even with on-demand capacity, DynamoDB can throttle requests if they exceed the table's burst capacity or if there are hot partitions. Exponential backoff reduces the retry rate, allowing DynamoDB to recover and improving overall throughput without changing the Lambda concurrency or capacity mode.

Answer

Increase the Lambda function's reserved concurrency to 500.

Answer

Disable the Lambda function's S3 event source mapping and use Amazon SQS to buffer events.

Answer

Switch the DynamoDB table to provisioned capacity with a high write capacity unit setting.

Question 6

A developer is managing an application running on Amazon EC2 instances behind an Application Load Balancer. Users report that the application becomes unresponsive after several hours, and restarting the instance temporarily fixes the issue. The developer suspects a memory leak but cannot add custom instrumentation. Which AWS service can collect memory utilization metrics and help identify the memory leak with minimal configuration?

Accepted Answer

Install the CloudWatch agent on the EC2 instances to collect memory metrics and emit them to CloudWatch.. The CloudWatch agent can collect custom metrics, including memory utilization, from EC2 instances and publish them to Amazon CloudWatch. This allows the developer to monitor memory usage over time and identify a memory leak without modifying the application code. The default EC2 metrics do not include memory utilization, so the CloudWatch agent is the minimal-configuration solution for this requirement.

Answer

Use Amazon CloudWatch Logs agent to capture application logs.

Answer

Use the EC2 instance metadata service to query memory usage.

Answer

Use AWS X-Ray to trace memory allocation.

Question 7

A developer is troubleshooting an AWS Lambda function that processes records from an Amazon Kinesis Data Stream. The function is configured with a batch size of 100 and a parallelization factor of 1. The iterator age metric is increasing, and CloudWatch Logs show the function execution time is around 4 minutes (timeout is 5 minutes). The stream has 10 shards. What is the most cost-effective way to increase processing throughput?

Accepted Answer

Increase the parallelization factor per shard. Increasing the parallelization factor per shard (option D) allows each shard to be processed by multiple Lambda instances concurrently, which directly increases throughput without requiring additional shards or changes to the stream. Since the function is not hitting the 5-minute timeout but is taking ~4 minutes per batch, the bottleneck is processing concurrency per shard, not batch size or execution duration. This is the most cost-effective solution because it uses existing shards and avoids the cost of additional shards or unnecessary timeout increases.

Answer

Increase the batch size to 500

Answer

Increase the number of shards

Answer

Increase the timeout to 10 minutes

Question 8

A developer monitors an AWS Lambda function that processes messages from an Amazon SQS queue. CloudWatch logs show that the function's execution time has increased significantly over the past week, and it now frequently times out at the 5-minute timeout. The function's code has not been changed recently. The function makes calls to an Amazon DynamoDB table. What is the most likely cause of the increased execution time?

Accepted Answer

The DynamoDB table's read capacity units are underprovisioned, causing throttling.. The most likely cause is that the DynamoDB table's read capacity units are underprovisioned, leading to throttling (ProvisionedThroughputExceededException). When DynamoDB throttles requests, the Lambda function must retry them, which adds latency and can cause the function to exceed its 5-minute timeout. Since the code hasn't changed, this points to a scaling or capacity issue on the DynamoDB side.

Answer

The SQS queue's visibility timeout is too short, causing duplicate processing.

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The Lambda function's memory is too low, causing CPU throttling.

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The DynamoDB table's indexes are missing, causing full table scans.

Question 9

A developer is troubleshooting an AWS Lambda function that returns timeout errors when calling an external HTTPS API. The function is configured with a 30-second timeout and runs in a VPC with a public subnet and NAT Gateway. The developer checks CloudWatch logs and sees that the function is timing out at exactly 30 seconds. What is the most likely cause?

Accepted Answer

The Lambda function's security group does not allow outbound traffic.. Lambda functions running in a VPC do not automatically get internet access; they require a route to a NAT Gateway or NAT instance. Even with a NAT Gateway, the Lambda function's security group must allow outbound traffic (e.g., HTTPS on port 443) to reach the external API. Without this rule, outbound packets are dropped, causing the function to hang until the configured timeout (30 seconds) expires, resulting in a timeout error.

Answer

The NAT Gateway is not configured with a route to the internet.

Answer

The external API's response time exceeds 30 seconds.

Answer

The Lambda function's VPC does not have an internet gateway.

Question 10

A DynamoDB application receives ProvisionedThroughputExceededException during predictable daily peaks. The workload is not cacheable. What should be changed?

Accepted Answer

Use on-demand capacity or configure autoscaling/scheduled scaling for the table. The ProvisionedThroughputExceededException indicates that the table's read/write capacity is insufficient during peak loads. Since the workload is predictable but not cacheable, the correct solution is to either switch to on-demand capacity mode, which automatically scales to handle any traffic level, or configure auto scaling with scheduled scaling to match the predictable peaks. This directly addresses the capacity shortfall without requiring application changes.

Answer

Enable S3 Transfer Acceleration

Answer

Disable CloudWatch metrics

Answer

Move all reads to strongly consistent mode

Question 11

Messages in an SQS queue are processed successfully but later reappear and are processed again. What is the most likely configuration issue?

Accepted Answer

The visibility timeout is shorter than the processing time or messages are not deleted after processing. When a message is processed but not deleted from the SQS queue, or when the visibility timeout expires before processing completes, the message becomes visible again in the queue and can be consumed by another worker. This causes duplicate processing. The correct fix is to ensure the visibility timeout is set longer than the expected processing time and that the message is explicitly deleted after successful processing.

Answer

The queue uses long polling

Answer

The queue has a dead-letter queue

Answer

The messages are encrypted with SSE-SQS

Question 12

A developer needs to trace a request across API Gateway, Lambda, and downstream AWS service calls. Which service should be enabled?

Accepted Answer

AWS X-Ray. AWS X-Ray is the correct service because it provides end-to-end tracing for requests flowing through distributed applications, including API Gateway, Lambda functions, and downstream AWS services like DynamoDB or S3. It captures trace data as the request traverses each component, allowing developers to identify performance bottlenecks and errors across the entire request path. X-Ray integrates natively with API Gateway and Lambda via the X-Ray SDK or active tracing configuration, requiring no code changes for basic tracing.

Answer

AWS Budgets

Answer

AWS Artifact

Answer

AWS License Manager

Question 13

A Lambda function using a Kinesis event source repeatedly retries one bad record and blocks progress in the shard. Which feature helps isolate failed records after retry limits?

Accepted Answer

Configure failure handling with bisect batch on error and an on-failure destination where supported. Lambda's Kinesis event source mapping supports a 'bisect batch on error' feature that splits a failed batch into two smaller batches, allowing the bad record to be isolated and retried separately. Additionally, configuring an on-failure destination (e.g., an SQS queue or SNS topic) sends the record to a dead-letter destination after the retry limit is exhausted, preventing the shard from blocking progress.

Answer

Increase memory to 10 GB only

Answer

Disable batch processing

Answer

Convert the stream to an S3 bucket

Question 14

An API backed by Lambda returns high p95 latency after deployment. Which two telemetry sources are most useful first?

Accepted Answer

CloudWatch Lambda duration/init duration/logs. CloudWatch Lambda duration and init duration metrics directly measure the time your function spends executing and initializing, which are the primary drivers of p95 latency. Logs can reveal cold starts, timeouts, or inefficient code paths that cause high latency. These are the most immediate telemetry sources to identify performance bottlenecks in the Lambda function itself.

Answer

AWS Billing console only

Answer

S3 Inventory reports

Question 15

A DynamoDB table shows throttling on one partition key value. Which two signs point to a hot partition problem?

Accepted Answer

Most traffic targets the same partition key. A hot partition occurs when a single partition key value receives a disproportionate share of read/write traffic, causing throttling on that partition even if the table's total provisioned capacity is not fully utilized. This imbalance means the partition's capacity is exhausted while other partitions remain underutilized, leading to request throttling for that specific key.

Answer

The table has point-in-time recovery enabled

Answer

CloudTrail is enabled in all regions