DVA-C02 Deployment Practice Question
A company is deploying a microservices architecture using AWS Lambda and Amazon API Gateway. The developer wants to implement a canary release deployment for the API. Which THREE steps should the developer take? (Choose THREE.)
⚠ Common exam trap
Watch out — candidates often confuse Lambda alias weighted routing (Option E) with API Gateway canary releases, but the question explicitly asks for API-level canary deployment, which requires API Gateway's native canary settings, not just Lambda-level traffic shifting.
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
✓
Configure stage variables to point the canary stage to a different Lambda function alias.
Stage variables in API Gateway can be configured to point the canary stage to a different Lambda function alias, enabling the canary to invoke a separate version of the function for testing. This allows the canary to route a percentage of traffic to a new Lambda version while the main stage continues using the stable alias, supporting gradual rollouts.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Configure stage variables to point the canary stage to a different Lambda function alias.
Why this is correct
Configuring stage variables within the API Gateway canary stage is the precise mechanism to direct a portion of incoming requests to a specific Lambda function alias, representing the new version of the backend service. This allows the canary stage to dynamically resolve the target Lambda version, ensuring that only the designated traffic percentage interacts with the updated code. It's fundamental for separating the base deployment from the experimental one.
- ✓
Enable canary by setting the traffic percentage in the API Gateway stage.
Why this is correct
Enabling canary functionality involves setting a specific traffic percentage directly within the API Gateway stage configuration. This crucial setting dictates what proportion of incoming client requests will be routed to the canary deployment, which typically points to a new Lambda alias. This gradual traffic shift allows for real-world testing of the new service version with a controlled subset of users before a full rollout.
- ✓
Use API Gateway canary release settings to create a canary stage.
Why this is correct
Utilizing API Gateway's built-in canary release settings is the foundational step to establish a controlled deployment strategy for microservices. This feature allows for the creation of a dedicated canary stage, which operates in parallel with the primary stage, enabling the safe introduction of new service versions. It provides the necessary infrastructure within API Gateway to manage the lifecycle of a gradual rollout.
- ✗
Use Amazon CloudFront to distribute traffic between two API Gateway stages.
Why it's wrong here
Amazon CloudFront is primarily a Content Delivery Network (CDN) and is not the native or recommended service for managing canary releases directly between API Gateway stages. While CloudFront can route traffic based on various rules, integrating it for this purpose would introduce unnecessary complexity and overhead, as API Gateway itself provides robust, built-in capabilities for canary deployments. The core traffic distribution logic for API Gateway canaries resides within API Gateway's own features.
- ✗
Use Lambda canary releases to gradually shift traffic.
Why it's wrong here
AWS Lambda functions, by themselves, do not possess native capabilities for performing canary releases that involve gradual, percentage-based traffic shifting. While Lambda supports versioning and aliases, the mechanism to intelligently route a controlled percentage of live traffic to a new alias for a canary deployment must be managed by an upstream service. API Gateway is specifically designed to provide this sophisticated traffic management for Lambda-backed microservices.
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
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