Question 702 of 724
DVA-C02 Troubleshooting and Optimization Practice Question
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?
⚠ Common exam trap
Candidates often think increasing batch size or timeout will help, but they overlook that the root cause is the reserved concurrency cap, which directly limits the number of concurrent executions and is the primary driver of throttles.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
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 analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Increase the reserved concurrency of the Lambda function to 50
Why this is correct
Increasing the reserved concurrency for a Lambda function dedicates a specific number of concurrent execution slots exclusively to that function. This action guarantees that the function can scale up to 50 simultaneous invocations, preventing it from being throttled by the account's general unreserved concurrency pool. For an SQS-triggered Lambda, this directly enables more parallel processing of messages, significantly improving throughput and reducing the backlog in the queue.
- ✗
Increase the batch size in the SQS event source mapping to 100
Why it's wrong here
Increasing the batch size in the SQS event source mapping means each Lambda invocation will process up to 100 messages in a single execution. While this can reduce the total number of Lambda invocations for a given volume of messages, it does not increase the concurrent execution capacity of the function itself. If the function is already experiencing throttling due to concurrency limits, a larger batch size will not alleviate this issue and might even increase the processing time per invocation, further delaying overall message processing.
- ✗
Increase the function timeout to 120 seconds
Why it's wrong here
Increasing the function timeout to 120 seconds only extends the maximum duration a single Lambda invocation is permitted to run before being terminated. This setting is crucial for long-running tasks to complete successfully without interruption. However, it has no impact whatsoever on the number of concurrent invocations that Lambda can execute simultaneously or the rate at which the function scales up to process messages from an SQS queue. It addresses individual invocation duration, not overall parallelism.
- ✗
Decrease the reserved concurrency to 5
Why it's wrong here
Decreasing the reserved concurrency to 5 would explicitly limit the Lambda function to a maximum of only five concurrent executions at any given time. This action would severely restrict the function's ability to process messages in parallel, leading to increased throttling and a significant reduction in overall throughput. Messages would accumulate rapidly in the SQS queue, exacerbating any existing processing delays rather than resolving them.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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Last reviewed: Jun 11, 2026
This DVA-C02 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DVA-C02 exam.
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