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Associate Cloud Engineer Study Notes

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Google Compute Engine

Virtual machines running in Google's data centers

Exam Domain

Deploying and implementing cloud solutions represents approximately 23% of the exam. Compute Engine is heavily tested.

Machine Types

Type	Use Case	Characteristics
E2	General purpose, cost-optimized	Shared-core available, best price-performance
N2/N2D	General purpose, balanced	Intel/AMD processors, sustained use discounts
C2/C2D	Compute-intensive	Highest per-core performance
M2/M3	Memory-optimized	Up to 12TB RAM, SAP HANA certified
A2/G2	GPU workloads	NVIDIA GPUs for ML/rendering
Custom	Flexible sizing	Specify exact vCPUs and memory

Preemptible vs Spot VMs

Preemptible VMs: Up to 80% discount, max 24-hour runtime, 30-second shutdown notice
Spot VMs: Same pricing as preemptible, no 24-hour limit, dynamic pricing
Use Cases: Batch processing, fault-tolerant workloads, distributed computing

Instance Groups

Type	Description	Use Case
Managed (MIG)	Identical VMs from template	Autoscaling, autohealing, rolling updates
Unmanaged	Different VM configurations	Legacy, heterogeneous workloads

Exam Focus Areas

Use Managed Instance Groups for stateless, scalable workloads
Sustained use discounts apply automatically (up to 30% for month-long use)
Committed use discounts require 1 or 3-year commitment for up to 57% savings
Custom machine types allow exact CPU/memory specification
Use startup scripts or custom images for consistent configuration

Practice what you just read

10 free practice questions. No credit card.

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Google Kubernetes Engine (GKE)

Managed Kubernetes for containerized applications

Cluster Modes

Mode	Management	Best For
Standard	You manage nodes	Full control, custom configurations
Autopilot	Google manages nodes	Simplified ops, pay per pod

Key Components

Pods: Smallest deployable unit, contains one or more containers
Deployments: Manage ReplicaSets, enable rolling updates
Services: Stable network endpoint for pods (ClusterIP, NodePort, LoadBalancer)
Ingress: HTTP(S) load balancing with URL-based routing
ConfigMaps/Secrets: Configuration and sensitive data management

Node Pool Configuration

Autoscaling: Cluster autoscaler adds/removes nodes based on pod demands
Node Auto-repair: Automatically repairs unhealthy nodes
Node Auto-upgrade: Automatically upgrades nodes to latest stable version
Surge Upgrades: Maintain capacity during upgrades

Exam Focus Areas

Use Autopilot for simplified management, Standard for full control
Workload Identity is the recommended way to authenticate to GCP APIs from GKE
Regional clusters provide higher availability than zonal clusters
Use Pod Disruption Budgets for controlled disruptions
Node service account is set at node pool creation and cannot be changed later

Practice what you just read

10 free practice questions. No credit card.

Try 10 free Associate Cloud Engineer questions

Associate Cloud Engineer Study Notes

Try 10 Free Questions

Google Compute Engine

Virtual machines running in Google's data centers

Exam Domain

Deploying and implementing cloud solutions represents approximately 23% of the exam. Compute Engine is heavily tested.

Machine Types

Type	Use Case	Characteristics
E2	General purpose, cost-optimized	Shared-core available, best price-performance
N2/N2D	General purpose, balanced	Intel/AMD processors, sustained use discounts
C2/C2D	Compute-intensive	Highest per-core performance
M2/M3	Memory-optimized	Up to 12TB RAM, SAP HANA certified
A2/G2	GPU workloads	NVIDIA GPUs for ML/rendering
Custom	Flexible sizing	Specify exact vCPUs and memory

Preemptible vs Spot VMs

Preemptible VMs: Up to 80% discount, max 24-hour runtime, 30-second shutdown notice
Spot VMs: Same pricing as preemptible, no 24-hour limit, dynamic pricing
Use Cases: Batch processing, fault-tolerant workloads, distributed computing

Instance Groups

Type	Description	Use Case
Managed (MIG)	Identical VMs from template	Autoscaling, autohealing, rolling updates
Unmanaged	Different VM configurations	Legacy, heterogeneous workloads

Exam Focus Areas

Use Managed Instance Groups for stateless, scalable workloads
Sustained use discounts apply automatically (up to 30% for month-long use)
Committed use discounts require 1 or 3-year commitment for up to 57% savings
Custom machine types allow exact CPU/memory specification
Use startup scripts or custom images for consistent configuration

Practice what you just read

10 free practice questions. No credit card.

Try 10 free Associate Cloud Engineer questions

Google Kubernetes Engine (GKE)

Managed Kubernetes for containerized applications

Cluster Modes

Mode	Management	Best For
Standard	You manage nodes	Full control, custom configurations
Autopilot	Google manages nodes	Simplified ops, pay per pod

Key Components

Pods: Smallest deployable unit, contains one or more containers
Deployments: Manage ReplicaSets, enable rolling updates
Services: Stable network endpoint for pods (ClusterIP, NodePort, LoadBalancer)
Ingress: HTTP(S) load balancing with URL-based routing
ConfigMaps/Secrets: Configuration and sensitive data management

Node Pool Configuration

Autoscaling: Cluster autoscaler adds/removes nodes based on pod demands
Node Auto-repair: Automatically repairs unhealthy nodes
Node Auto-upgrade: Automatically upgrades nodes to latest stable version
Surge Upgrades: Maintain capacity during upgrades

Exam Focus Areas

Use Autopilot for simplified management, Standard for full control
Workload Identity is the recommended way to authenticate to GCP APIs from GKE
Regional clusters provide higher availability than zonal clusters
Use Pod Disruption Budgets for controlled disruptions
Node service account is set at node pool creation and cannot be changed later