SAA-C03 Design High-Performing Architectures Practice Question
Exhibit
CloudWatch metrics for Lambda function 'image-resize': - Average Duration: 220 ms - P95 Init Duration after idle: 1,400 ms - ConcurrentExecutions: 15 average, 60 during campaign launches - Throttles: 0 - User complaint: first upload after inactivity feels slow
Based on the exhibit, what change best reduces Lambda cold-start impact for a predictable user-upload workflow?
⚠ Common exam trap
Many exam-takers confuse reserved concurrency (which limits concurrency) with provisioned concurrency (which pre-warms instances), or they assume that increasing memory or timeout will solve cold starts, when in fact only provisioned concurrency directly addresses initialization latency for predictable workloads.
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
✓
Enable provisioned concurrency for the function.
Provisioned concurrency pre-warms a specified number of execution environments so that when a user upload triggers the Lambda function, there is no cold-start latency. This is the most direct way to eliminate initialization time for a predictable workload, as it keeps instances ready to handle requests immediately.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Set a reserved concurrency limit for the function to protect it from throttling.
Why it's wrong here
Reserved concurrency sets a guaranteed, per-function concurrency limit on the account, preventing other functions from consuming all available execution environments and thereby protecting against throttling. However, it does not initialize or warm any Lambda environment; when a request arrives after an idle period, the function still must go through the full cold-start path (downloading the code, initializing the runtime, and running initialization code). Thus, it only prevents throttling errors but leaves the latency problem unresolved.
- ✓
Enable provisioned concurrency for the function.
Why this is correct
Provisioned concurrency keeps a pre-initialized pool of Lambda execution environments ready to respond immediately. The exhibit shows long init duration after inactivity, which is the classic symptom of cold starts affecting user experience. Because the traffic pattern is predictable during launches, provisioned concurrency is the most direct way to reduce startup latency and smooth response times.
- ✗
Increase the function timeout to give more time for initialization.
Why it's wrong here
A function timeout is the maximum execution time a Lambda invocation is allowed to run before being terminated; increasing it simply gives a given execution more time to complete before failing. It has no effect on initialization time because cold-start delay occurs during the environment setup phase, before the handler starts executing. Extending the timeout only treats the symptom of slow handlers; it does nothing to keep a pre-warmed environment available to serve the request immediately.
- ✗
Move the function to a larger memory setting only to eliminate all initialization time.
Why it's wrong here
Configuring a larger memory size proportionally increases the CPU and network bandwidth allocated to the function, which can reduce the execution time of the handler and sometimes shorten the initialization phase because the runtime has more resources. But it cannot eliminate cold starts entirely: when no execution environment is already warm, Lambda still needs to create and initialize a new sandbox, and that per-request latency remains. This option is a performance tuning knob, not a cold-start elimination mechanism, and may incur extra cost without providing the on-demand responsiveness of a warm pool.
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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