Serverless vs GKE decision in GCP - Quick Revision & Key Differences

Recall & Review

beginner

What is Serverless computing in GCP?

Serverless computing means you run your code without managing servers. GCP handles the infrastructure, scaling, and maintenance automatically.

beginner

What is Google Kubernetes Engine (GKE)?

GKE is a managed service to run containerized applications using Kubernetes. You control the cluster and how your apps run inside it.

intermediate

When should you choose Serverless over GKE?

Choose Serverless when you want simple deployment, automatic scaling, and no server management. It fits well for event-driven or small apps.

intermediate

What are reasons to pick GKE instead of Serverless?

Pick GKE when you need full control over your environment, complex app orchestration, or want to run many containers with custom settings.

intermediate

How does scaling differ between Serverless and GKE?

Serverless scales automatically based on demand without user action. GKE requires configuring autoscaling or manual scaling of nodes and pods.

Which option best describes Serverless computing?

A You manage servers and scaling manually

B Infrastructure is fully managed and scales automatically

C You run virtual machines with full control

D You deploy containers without orchestration

Serverless means the cloud provider manages infrastructure and scaling automatically.

What is a key benefit of using GKE?

A No need to manage containers

B Automatic scaling without configuration

C Full control over container orchestration

D No need to write code

GKE gives you control over how containers run and scale using Kubernetes.

When is Serverless a better choice than GKE?

A For simple event-driven apps with variable load

B When you want to manage infrastructure

C For complex multi-container apps

D When you need custom networking

Serverless fits simple apps that respond to events and scale automatically.

Which is true about scaling in GKE?

A You must configure autoscaling or scale manually

B It never scales

C It scales automatically without any setup

D Scaling is handled by serverless functions

GKE requires you to set up autoscaling or scale your cluster manually.

What is a disadvantage of Serverless compared to GKE?

A It requires managing Kubernetes clusters

B It needs manual server maintenance

C It cannot scale automatically

D You have less control over the environment

Serverless abstracts infrastructure, so you have less control over environment details.

Explain the main differences between Serverless and GKE in GCP.

Think about control, scaling, and complexity.

Describe scenarios where you would choose Serverless over GKE and vice versa.

Focus on app complexity and operational needs.

Practice

1. Which option best describes a key benefit of using serverless computing in GCP?

easy

A. No need to manage servers and automatic scaling happens

B. You get full control over the underlying hardware

C. You must manually configure load balancers

D. You need to manage container orchestration

Solution

1. Step 1: Understand serverless basics

   Serverless means the cloud provider handles server management and scaling automatically.

2. Step 2: Compare options

   The other options describe manual management or container orchestration, which are not serverless benefits.

3. Final Answer:

   No need to manage servers and automatic scaling happens -> Option A

4. Quick Check:

   Serverless = No server management + auto scaling [OK]

Hint: Serverless means no servers to manage, auto scales itself [OK]

Common Mistakes:

• Confusing serverless with container management
• Thinking serverless requires manual scaling
• Assuming serverless means full hardware control

2. Which of the following is the correct way to deploy a containerized app on GKE?

easy

A. Use gcloud run deploy command

B. Use kubectl apply -f deployment.yaml command

C. Use firebase deploy command

D. Use gsutil cp to upload container image

Solution

1. Step 1: Identify GKE deployment command

   GKE uses Kubernetes commands like kubectl apply to deploy resources from YAML files.

2. Step 2: Check other commands

   gcloud run deploy is for serverless Cloud Run, firebase deploy is for Firebase apps, and gsutil cp uploads files to storage, not deploy containers.

3. Final Answer:

   Use kubectl apply -f deployment.yaml command -> Option B

4. Quick Check:

   GKE deploy = kubectl apply [OK]

Hint: GKE uses kubectl with YAML files to deploy containers [OK]

Common Mistakes:

• Using Cloud Run commands for GKE
• Confusing Firebase deploy with container deployment
• Uploading images with gsutil instead of container registry

3. You have a web app with unpredictable traffic spikes and want minimal management. Which GCP service behavior fits best?

medium

A. Serverless auto-scales instantly with no server management

B. GKE requires manual scaling and cluster management

C. GKE automatically scales without any configuration

D. Serverless requires you to provision VM instances

Solution

1. Step 1: Analyze traffic and management needs

   Unpredictable spikes need fast scaling and minimal management.

2. Step 2: Match service behavior

   Serverless auto-scales instantly and requires no server management. GKE needs manual or configured scaling and cluster upkeep.

3. Final Answer:

   Serverless auto-scales instantly with no server management -> Option A

4. Quick Check:

   Unpredictable traffic + minimal management = Serverless [OK]

Hint: Unpredictable traffic? Choose serverless for auto scaling [OK]

Common Mistakes:

• Assuming GKE scales automatically without config
• Thinking serverless needs VM provisioning
• Confusing manual and automatic scaling

4. You deployed a container on GKE but it fails to start. Which fix is most likely needed?

medium

A. Enable serverless API in GCP console

B. Increase Cloud Run memory allocation

C. Check and fix container image path in deployment YAML

D. Upload container image to Firebase hosting

Solution

1. Step 1: Identify cause of container start failure

   Common cause is incorrect container image path or tag in deployment YAML.

2. Step 2: Evaluate options

   Increasing Cloud Run memory or enabling serverless API does not affect GKE container start. Firebase hosting is unrelated to container images.

3. Final Answer:

   Check and fix container image path in deployment YAML -> Option C

4. Quick Check:

   Container start fail? Fix image path in YAML [OK]

Hint: Check container image path in YAML if GKE pod fails [OK]

Common Mistakes:

• Trying serverless fixes for GKE issues
• Uploading images to wrong services
• Ignoring deployment YAML errors

5. Your app needs custom networking, persistent storage, and runs long background jobs. Which GCP choice fits best?

hard

A. Use serverless Cloud Run for easy scaling and no management

B. Use Firebase hosting for backend processing

C. Use App Engine standard environment for background jobs

D. Use GKE for full control over networking and storage

Solution

1. Step 1: Identify app requirements

   Custom networking, persistent storage, and long background jobs require control and flexibility.

2. Step 2: Match requirements to GCP services

   GKE offers container orchestration with networking and storage control. Serverless Cloud Run lacks persistent storage and complex networking. App Engine standard has limitations on background jobs. Firebase hosting is for static content.

3. Final Answer:

   Use GKE for full control over networking and storage -> Option D

4. Quick Check:

   Custom network + storage + long jobs = GKE [OK]

Hint: Need control and storage? Choose GKE over serverless [OK]

Common Mistakes:

• Choosing serverless despite storage needs
• Using App Engine for heavy background jobs
• Confusing Firebase hosting with backend services