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Module 3 challenge :Configuration Management and the Cloud (Google IT Automation with Python Professional Certificate) Answers 2025

1. Service model with most control
❌ PaaS
✔️ IaaS
❌ RaaS
❌ SaaS

2. Downsides of opting for manual scaling (select all that apply)
✔️ You might experience unexpected increases in demand
✔️ You will have to plan ahead for scaling needs
❌ Changes are controlled by software (this is automated scaling, not a downside of manual)
❌ No monitoring or alerts (monitoring can still exist)

3. True statements about cloud migration approaches (select all that apply)
✔️ Multi-cloud deployment increases resilience
✔️ Containers simplify migration
❌ Migrating always requires rewriting all applications
✔️ Lift and shift involves minimal changes

4. Two main interfaces for VMs; preferred for automation
❌ Text editor + remote desktop
✔️ GUI + CLI; CLI preferred for automation
❌ API + SDK; SDK preferred
❌ GUI + CLI; GUI preferred

5. Correct order to create an instance template
1️⃣ Stop the VM
2️⃣ Create a disk image from the boot disk
3️⃣ Create an instance template using a disk image

6. Distinctions between instance, disk image, and snapshot
❌ Snapshot = reusable template
✔️ Instance = running VM, Disk image = reusable template, Snapshot = point-in-time backup
❌ Instance = template, Disk image = running VM
❌ All interchangeable

7. Typical components of large-scale cloud web architecture (select all that apply)
✔️ Autoscaling
❌ Single powerful VM (not scalable)
✔️ Load balancer
✔️ Multiple layers of caching

8. How orchestration tools interact with cloud providers
✔️ Through APIs
❌ Primarily GUI
❌ Directly modifying VM config files
❌ Sending commands via SSH

9. Primary benefit of Infrastructure as Code (IaC)
❌ Manual GUI configuration
❌ Automatically optimizes code
✔️ Repeatable deployments, version control, easy rollbacks
❌ Eliminates need for scripting

10. Relationship between autoscaling and data persistence
✔️ Persistent data should be stored separately from instances
❌ Autoscaling automatically handles persistence
❌ Autoscaling incompatible with persistence
❌ Store persistent data on local disks only


📌 Summary Table

Q# Correct Answer(s)
1 IaaS ✔️
2 Unexpected demand ✔️, Plan ahead ✔️
3 Multi-cloud ✔️, Containers ✔️, Lift & shift ✔️
4 GUI + CLI; CLI preferred ✔️
5 Stop VM → Disk image → Template ✔️
6 Instance = running, Disk image = template, Snapshot = backup ✔️
7 Autoscaling ✔️, Load balancer ✔️, Caching ✔️
8 APIs ✔️
9 Repeatable deployments, version control, rollbacks ✔️
10 Persistent data separate from instances ✔️