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Design for New SolutionshardMultiple ChoiceObjective-mapped

SAP-C02 Design for New Solutions Practice Question

A company is migrating a monolithic application to a serverless architecture using AWS Lambda. The application reads and writes to an Amazon RDS for PostgreSQL database. The database connection pool is exhausted during peak traffic. Which design change should a solutions architect recommend to avoid connection exhaustion?

⚠ Common exam trap

Candidates often think increasing max_connections or using a queue (SQS) is sufficient, but they overlook that Lambda's concurrent execution model requires connection pooling at the database layer, which RDS Proxy uniquely provides.

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

Use Amazon RDS Proxy to pool and share database connections.

Amazon RDS Proxy sits between the Lambda function and the RDS database, managing a pool of database connections and reusing them across multiple invocations. This prevents the Lambda function from exhausting the database connection pool during traffic spikes, as each Lambda instance does not need to open its own connection. RDS Proxy also handles connection multiplexing and reduces the overhead of establishing new connections.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Use Amazon SQS to buffer write requests to the database.

    Why it's wrong here

    SQS does not address connection pooling; it would add latency.

  • Use DynamoDB Accelerator (DAX) as a caching layer.

    Why it's wrong here

    DAX caches DynamoDB, not RDS.

  • Use Amazon RDS Proxy to pool and share database connections.

    Why this is correct

    RDS Proxy manages connection pooling, reducing connection exhaustion from Lambda.

  • Increase the max_connections parameter in the RDS parameter group.

    Why it's wrong here

    Increasing max_connections may hit instance limits and is not a scalable solution.

Quick reference

Cloud Service Model Comparison

ModelYou ManageProvider ManagesExamples
IaaSOS, runtime, apps, dataHardware, hypervisor, networkingEC2, Azure VMs, GCP Compute Engine
PaaSApps and dataOS, runtime, middleware, hardwareElastic Beanstalk, Azure App Service
SaaSData and settings onlyEverything elseMicrosoft 365, Salesforce, Workday
FaaS / ServerlessFunction code onlyInfra, scaling, runtimeLambda, Azure Functions, Cloud Run
CaaSContainers and appsKubernetes, OS, hardwareEKS, AKS, GKE

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