DOP-C02 Incident and Event Response Practice Question
A company uses AWS Lambda with an Amazon DynamoDB trigger. Recently, the Lambda function started failing with 'ProvisionedThroughputExceededException' errors. The DevOps team needs to mitigate the issue. Which TWO actions should the team take? (Choose TWO.)
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 DynamoDB table's write capacity
To mitigate 'ProvisionedThroughputExceededException' errors when a Lambda function is triggered by DynamoDB Streams, two actions are effective. Option D: Increase the DynamoDB table's write capacity to handle the write demand from the stream processing. Option E: Reduce the batch size for the DynamoDB stream event source mapping to lower the number of writes per invocation, reducing the chance of exceeding throughput. Option A is wrong because Lambda reserved concurrency controls how many concurrent executions Lambda can run, but the issue is DynamoDB throttling, not Lambda capacity. Option B is wrong because disabling DynamoDB Streams would stop the trigger entirely, which is not a mitigation. Option C is wrong because DynamoDB Accelerator (DAX) is an in-memory cache for reads, not writes, and does not affect write throughput.
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 Lambda function's reserved concurrency
Why it's wrong here
Reserved concurrency limits the maximum number of concurrent Lambda executions, decoupling it from DynamoDB's write throughput. Throttling at the DynamoDB level is governed by your provisioned write capacity units (WCUs) or auto scaling, not by how many Lambda functions are running. Raising concurrency may actually increase the rate of DynamoDB throttling if Lambda attempts more concurrent writes, so it doesn't address the root cause.
- ✗
Disable DynamoDB Streams on the table
Why it's wrong here
Disabling streams removes the event source for the Lambda trigger, so the function would no longer be invoked by table changes. This would break the processing workflow entirely, rather than fix throttling or failures. Streams are required for the asynchronous event-driven integration, so this action is not a viable solution.
- ✗
Enable DynamoDB Accelerator (DAX) for the table
Why it's wrong here
DAX (DynamoDB Accelerator) is an in-memory cache that serves read requests, providing low-latency point reads and queries. It does not affect the table's write capacity, stream generation, or Lambda's ability to process stream records. Since the problem revolves around write throttling or stream consumption, DAX offers no benefit and might even add complexity without resolving the issue.
- ✓
Increase the DynamoDB table's write capacity
Why this is correct
DynamoDB throttling occurs when write requests exceed the provisioned write capacity (WCUs) of the table. If the Lambda function writes processed items back to the same table, insufficient WCUs will cause ProvisionedThroughputExceededException, leading to retries and stream processing failures. Increasing the write capacity reduces throttling, allowing the stream-triggered writes to succeed and the function to make progress.
- ✓
Reduce the batch size for the DynamoDB stream event source mapping
Why this is correct
Smaller batches in the event source mapping cause Lambda to receive fewer stream records per invocation, which reduces the number of DynamoDB writes performed in a single execution. This decreases the burst of write capacity consumed per invocation, lowering the chance of exceeding the table's provisioned throughput and triggering throttling. It also mitigates the impact of a single failed record, as retries affect fewer items and overall stream processing becomes more granular.
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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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DOP-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 DOP-C02 exam.