Implementing Gradual Traffic Shifting to a New AKS Version with Istio
You are designing a release pipeline for a microservices application deployed to Azure Kubernetes Service (AKS). You need to implement a strategy that minimizes downtime during updates by gradually shifting traffic to the new version while monitoring for errors. Which deployment strategy should you use?
Quick Answer
Canary deployment is built for exactly this: shift a small slice of traffic to the new version, watch for errors, and only ramp up further once it looks healthy — keeping most users on the stable version the whole time. On AKS this is typically implemented with a service mesh like Istio or a progressive-delivery tool like Flagger, managing the traffic split declaratively.
⚠ Common exam trap
It's easy for candidates to confuse canary deployment with rolling update, but rolling update does not support traffic splitting or error-monitoring-based rollback—it simply replaces pods without the ability to route a controlled percentage of traffic to the new version for validation.
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
✓
Canary deployment
Canary deployment is the correct choice because it gradually shifts a small percentage of traffic to the new version while monitoring for errors, allowing you to detect issues early and roll back quickly without impacting all users. In AKS, this can be implemented using a service mesh like Istio or a progressive delivery tool like Flagger, which manages traffic splitting via VirtualService and DestinationRule configurations. This minimizes downtime by ensuring the majority of users remain on the stable version until the new version is verified.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Recreate deployment
Why it's wrong here
Incorrect: Recreate kills all pods then creates new ones, causing downtime.
- ✗
Blue-green deployment
Why it's wrong here
Incorrect: Blue-green switches all traffic at once, not gradual.
- ✓
Canary deployment
Why this is correct
Correct: Canary releases a small subset of new version and gradually increases traffic with monitoring.
- ✗
Rolling update
Why it's wrong here
Incorrect: Rolling update replaces pods incrementally but traffic is not shifted gradually; it's immediate per pod.
Go deeper
Related to this question
Learn chapter
Introduction to DevOps and Azure DevOps
Key term
Release pipeline
A Release pipeline is an automated sequence of steps that takes software from code commit to production deployment, ensuring quality and consistency.
Key term
Anthos
Anthos is a Google Cloud platform that lets you run applications consistently across different computing environments, like on-premises data centers and multiple public clouds.
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Same concept, more angles
3 more ways this is tested on AZ-400
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. You are designing a release pipeline for a containerized application deployed to Azure Kubernetes Service (AKS). You want to implement a strategy where the new version is deployed to a small subset of pods first, and if healthy, gradually rolled out to all pods. Which Kubernetes deployment strategy should you use?
medium- ✓ A.Canary deployment
- B.Rolling update
- C.Blue-green deployment
- D.Recreate deployment
Why A: A canary deployment is the correct strategy because it allows you to route a small percentage of traffic (e.g., 5%) to the new version of the application running on a subset of pods in AKS. If the canary is healthy (e.g., passes liveness and readiness probes), you can gradually increase the traffic percentage until 100% of pods run the new version, providing controlled rollout and rollback capabilities.
Variation 2. You are implementing a release pipeline for a containerized application using Azure Kubernetes Service (AKS). The pipeline should use canary deployments to gradually shift traffic from the stable version to the new version. Which strategy should you use to manage the traffic shift?
hard- A.Blue-green deployment strategy
- B.Rolling update strategy
- C.A/B testing with feature flags
- ✓ D.Canary deployment using a service mesh (e.g., Istio)
Why D: A service mesh like Istio provides fine-grained traffic management capabilities (e.g., using VirtualService and DestinationRule resources) that allow you to route a specific percentage of traffic to the new canary version while the rest goes to the stable version. This enables gradual traffic shifting without modifying application code, and supports advanced routing rules based on headers or weights, which is essential for canary deployments in AKS.
Variation 3. Your team uses Azure Pipelines to deploy a microservices application to Azure Kubernetes Service (AKS). You need to implement a strategy that minimizes downtime during updates. Which TWO options should you use?
medium- A.Set the deployment replica count to zero before updating.
- B.Use a canary deployment with a service mesh.
- ✓ C.Configure a rolling update strategy in the Kubernetes manifest.
- D.Use a recreate deployment strategy.
- ✓ E.Implement a blue-green deployment pattern using separate namespaces.
Why C: A rolling update (C) is the built-in Kubernetes deployment strategy that avoids downtime. A blue-green deployment (E) using separate namespaces also provides zero downtime. A canary deployment (B) can also minimize downtime, but if exactly two choices are required, the intended pair is C and E. Setting replicas to zero (A) or using recreate (D) causes downtime.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AZ-400 practice question is part of Courseiva's free Microsoft 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 AZ-400 exam.