DVA-C02 Troubleshooting and Optimization Practice Test 3 — 15 Questions

Question 1

A developer is monitoring an AWS Lambda function that processes messages from an SQS queue. CloudWatch metrics show that the function's throttles are high when the queue backlog grows. The function has a reserved concurrency of 50 and a batch size of 10. The SQS queue has a visibility timeout of 30 seconds. The function processes each batch in about 5 seconds. Which action will most effectively reduce throttles?

Accepted Answer

Increase the Lambda function's batch size. Option C is correct because increasing the batch size allows each Lambda invocation to process more messages per batch (e.g., from 10 to a higher value up to 10,000 for standard queues). This reduces the number of concurrent invocations needed to clear the backlog, directly lowering the throttle count without requiring additional reserved concurrency. Since the function processes each batch in ~5 seconds and the visibility timeout is 30 seconds, there is ample time to handle larger batches, making this the most effective adjustment.

Answer

Increase the SQS queue visibility timeout

Answer

Increase the Lambda function's reserved concurrency

Answer

Decrease the SQS queue message retention period

Question 2

A developer is using AWS X-Ray to trace a microservices application. The trace shows that a downstream service is failing with HTTP 500 errors intermittently. The developer wants to set up trace annotations to capture the error details for further analysis. Which AWS service can the developer use to search and filter traces based on these annotations?

Accepted Answer

AWS X-Ray console search. Option B is correct because AWS X-Ray's console search feature allows developers to query traces using annotations and metadata that are indexed by X-Ray. Annotations are key-value pairs attached to trace segments, and the X-Ray console search can filter traces based on these annotations, enabling the developer to isolate the intermittent HTTP 500 errors and analyze their details.

Answer

Amazon CloudWatch Logs Insights

Answer

Amazon Athena queries on X-Ray data

Answer

Amazon Kinesis Data Analytics

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.. Option B is correct because 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.. Option B is correct because 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 is using Amazon DynamoDB and notices that read requests are frequently throttled. The table has provisioned read capacity of 100 read capacity units (RCUs) and is used by a web application that experiences bursty traffic. The developer wants to minimize throttling without manual intervention. Which action should the developer take?

Accepted Answer

Enable DynamoDB Accelerator (DAX). Enabling DynamoDB Accelerator (DAX) reduces the number of read requests hitting the table by serving them from an in-memory cache. This offloads read traffic, effectively reducing the consumed RCUs and minimizing throttling during bursty traffic without requiring manual intervention or capacity changes.

Answer

Increase the write capacity

Answer

Use a global table

Answer

Enable auto scaling for read capacity

Question 9

A developer is troubleshooting an application that uses Amazon ElastiCache for Redis to cache database query results. The application experiences high latency during cache misses. The developer notices that frequently accessed keys (hot keys) are often missing from the cache, suggesting they are being evicted. Which action should the developer take to reduce cache misses for hot keys?

Accepted Answer

Switch to the 'allkeys-lru' eviction policy.. Option B is correct because the 'allkeys-lru' eviction policy allows Redis to evict any key (including those with TTL) based on least-recently-used access, which helps retain frequently accessed hot keys. By default, ElastiCache for Redis uses the 'volatile-lru' policy, which only evicts keys with an expiration set, leaving hot keys without TTL vulnerable to eviction when memory pressure occurs. Switching to 'allkeys-lru' ensures that even keys without TTL can be considered for eviction, reducing the likelihood of hot keys being removed.

Answer

Increase the number of cache nodes.

Answer

Disable the TTL on all cached keys.

Answer

Increase the size of the cache cluster.

Question 10

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.

Answer

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

Answer

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

Question 11

A developer is troubleshooting an AWS Lambda function that processes files uploaded to an Amazon S3 bucket. The function sometimes times out when processing large files. CloudWatch Logs show that the function's execution time correlates with file size. The function is configured with 128 MB memory and a timeout of 30 seconds. Which action should the developer take to resolve the timeout for large files without refactoring the code?

Accepted Answer

Increase the Lambda function's timeout. The Lambda function times out because processing large files exceeds the 30-second timeout. Since the execution time correlates with file size and the code cannot be refactored, the only way to resolve the timeout is to increase the function's timeout setting. This directly extends the maximum allowed execution duration, allowing large files to complete processing without code changes.

Answer

Increase the Lambda function's memory

Answer

Increase the S3 event notification batch size

Answer

Enable Lambda function reserved concurrency

Question 12

A developer has an AWS Lambda function that processes messages from an Amazon SQS queue. The function is configured with a reserved concurrency of 5. Recently, the SQS queue has experienced a high volume of messages, and the developer notices that many invocations are being throttled, leading to increased processing time. What is the most likely cause of the throttling?

Accepted Answer

The reserved concurrency is too low, causing SQS to throttle Lambda invocations.. The correct answer is B because reserved concurrency limits the maximum number of concurrent executions for a Lambda function. When the SQS queue has a high volume of messages, Lambda attempts to scale up to process them, but with a reserved concurrency of 5, it can only run 5 concurrent invocations. Any additional invocation requests are throttled with a 429 error, causing messages to remain in the queue and increasing processing time.

Answer

The function's execution role lacks permissions to invoke the function.

Answer

The SQS queue visibility timeout is set too high.

Answer

The Lambda function has a VPC configuration that causes cold starts.

Question 13

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.. Option B is correct because 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 14

A Lambda function behind API Gateway intermittently times out only during cold starts. Which two actions can reduce cold-start impact?

Accepted Answer

Use provisioned concurrency for predictable low latency. Provisioned concurrency keeps a specified number of Lambda execution environments initialized and ready to respond immediately, eliminating the cold-start latency for those invocations. This is the most direct way to ensure predictable low latency for a function that intermittently times out during cold starts.

Answer

Move all logs to S3 Glacier

Answer

Disable all retries

Question 15

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