GCP Professional Cloud Architect Exam Study Guide

Google cloud professional cloud architect Certificate Exam study guide-2

GCP Professional Cloud Architect Prep

Preparing for the GCP Professional Cloud Architect exam? Don’t know where to start? This post is the GCP Professional Cloud Architect Certification Study Guide (with links to each objective in the exam domain).

I have curated a detailed list of articles from the Google documentation and other blogs for each objective of the Google Cloud Platform Professional Cloud Architect exam. Please share the post within your circles so it helps them to prepare for the exam.

GCP Professional Cloud Architect Course

Pluralsight (Learning Path)GCP certified Cloud Architect course
Coursera (Professional Cert.)Cloud Architect Professional preparation
UdemyProfessional Cloud Architect certification

Google Professional Cloud Architect Practice Test

Whizlabs Exam QuestionsGCP Architect (300+ Qs & FREE Labs)
Udemy Practice TestsCloud Architect Practice Questions
Amazon e-book (PDF)Professional Cloud Architect Study Guide

Check out all the other GCP certificate study guides

Full Disclosure: Some of the links in this post are affiliate links. I receive a commission when you purchase through them.

Section 1. Designing and planning a cloud solution architecture

1.1 Designing a solution infrastructure that meets business requirements. Considerations include:

Business use cases and product strategy

Help secure data workloads: Google Cloud use cases

Real-world ​use ​cases

Cost optimization

Optimize your Google Cloud costs

Cost optimization on Google Cloud

Supporting the application design

Google Cloud architecture framework

Design your company architecture on GCP

Integration with external systems

Integrate Google Cloud Deploy with other systems

Integration with Google Cloud services

Movement of data

Transferring your large datasets

Design decision trade-offs

Trade-offs in the choice of cloud service

Build, buy, modify, or deprecate

Update, deprecate, & delete container images

Success measurements (e.g., key performance indicators [KPI], return on investment [ROI], metrics)

KPIs for APIs: How do metrics change over time?

9 things to consider when measuring ROI in the cloud

Compliance and observability

Cloud compliance & regulations

Designing for observability on Google Cloud

1.2 Designing a solution infrastructure that meets technical requirements. Considerations include:

High availability and failover design

Design for scale and high availability

High Availability, Failover design

The elasticity of cloud resources with respect to quotas and limits

Quotas & Limits

Working with quotas

Scalability to meet growth requirements

Patterns for scalable and resilient apps

Using autoscaling for highly scalable applications

Performance and latency

Measure and compare the performance

Optimizing application latency with load balancing

1.3 Designing network, storage, and compute resources. Considerations include:

Integration with on-premises/multicloud environments

GKE on-prem integration with GCP & enterprise network

Multicloud solutions

Cloud-native networking (VPC, peering, firewalls, container networking)

VPC network overview

VPC network peering overview

Firewall rules overview

Container networking overview

Choosing data processing technologies

Processing large-scale data

Choosing appropriate storage types (e.g., object, file, databases)

Object vs block vs file: which one to choose?

Cloud storage options

Choosing compute resources (e.g., preemptible, custom machine type, specialized workload)

Custom machine types

Mapping compute needs to platform products

Products and services

1.4 Creating a migration plan (i.e., documents and architectural diagrams). Considerations include:

Integrating solutions with existing systems

Integration with Google Cloud services and tools

Migrating systems and data to support the solution

Migration to Google Cloud

Software license mapping

Bringing your own licenses

Network planning

Reference architectures for VPC design

Testing and proofs of concept

Creating a test clone  |  Migrate for Compute Engine

Testing overview

Dependency management planning

Dependency management

1.5 Envisioning future solution improvements. Considerations include:

Cloud and technology improvements

Improvements to Google Cloud infrastructure

Evolution of business needs

Your business evolution strategy

Evangelism and advocacy

Developers, Evangelists, and Champions

GCP Professional Cloud Architect

Amazon link (affiliate)

Section 2. Managing and provisioning a solution infrastructure

2.1 Configuring network topologies. Considerations include:

Extending to on-premises environments (hybrid networking)

Google Cloud Hybrid Connectivity

Hybrid connectivity and network management

Extending to a multi-cloud environment that may include Google Cloud to Google Cloud communication

Multicloud solutions

Hybrid and multi-cloud patterns and practices

Security protection (e.g. intrusion protection, access control, firewalls)

Cloud IDS overview

Overview of access control

Firewalls: Network security

2.2 Configuring individual storage systems. Considerations include:

Data storage allocation

Best practices for Cloud Storage

Data processing/compute provisioning

Provisioning VMs on sole-tenant nodes

Security and access management

Security command center

Identity and Access Management

Network configuration for data transfer and latency

Configuring VMs for networking use cases

5 steps to better GCP network performance

Data retention and data life cycle management

Set a retention policy

Object lifecycle management

Data growth planning

How does your cloud storage grow?

2.3 Configuring compute systems. Considerations include:

Compute resource provisioning

Creating and starting a VM instance

Compute volatility configuration (preemptible vs. standard)

Preemptible VMs, a compute available at 70% off standard pricing

Network configuration for Compute resources (Google Compute Engine, Google Kubernetes Engine, serverless networking)

Configuring VMs for networking use cases

Network overview in Kubernetes Engine

Configuring network settings

Infrastructure orchestration, resource configuration, and patch management

Choosing the right orchestrator in Google Cloud

Automating infrastructure with Cloud Composer

OS patch management

Container orchestration

Containers at Google

Section 3. Designing for security and compliance

3.1 Designing for security. Considerations include:

Identity and access management (IAM)

Overview of IAM

Resource hierarchy (organizations, folders, projects)

Resource hierarchy

Quickstart using organizations

Folder resource

Project resource

Data security (key management, encryption, secret management)

Cloud Key Management Service deep dive

Data encryption options

Secret Manager conceptual overview

Separation of duties (SoD)

Separation of duties

Separation of duties & IAM roles

Security controls (e.g., auditing, VPC Service Controls, context-aware access, organization policy)

Cloud Audit Logs overview

VPC Service Controls

Setting up context-aware access with Identity-Aware Proxy

Introduction to the Organization Policy Service

Managing customer-managed encryption keys with Cloud Key Management Service

Customer-managed encryption keys

Remote access

Configure remote access for Compute Engine VMs

3.2 Designing for compliance. Considerations include:

Legislation (e.g., health record privacy, children’s privacy, data privacy, and ownership)

HIPAA Compliance on Google Cloud Platform

COPPA Compliance

Privacy resource center

Commercial (e.g., sensitive data such as credit card information handling, personally identifiable information [PII])

PCI DSS Compliance

PCI Data Security Standard compliance

Comprehensive protection of PII in GCP

Industry certifications (e.g., SOC 2)

SOC 2 Compliance

Audits (including logs)

Cloud Compliance & regulations resources

Section 4. Analyzing and optimizing technical and business processes

4.1 Analyzing and defining technical processes. Considerations include:

Software development life cycle (SDLC)

Google introduces SLSA framework

Continuous integration / continuous deployment

Continuous integration

Continuous deployment from Git using Cloud Build

CI/CD with Google Cloud

Troubleshooting/root cause analysis best practices

Troubleshooting tips that can help your cloud provider help you

Testing and validation of software and infrastructure

Testing overview

Service catalog and provisioning

Private Catalog

Dedicated interconnect provisioning overview

Business continuity and disaster recovery

Business continuity planning and disaster recovery

4.2 Analyzing and defining business processes. Considerations include:

Stakeholder management (e.g. influencing and facilitation)

Cloud stakeholders as per NIST

Change management

Managing change in the cloud

Team assessment/skills readiness

Assessing and discovering your workloads

Decision-making processes

Why Google Cloud?

Customer success management

Customers | Google Cloud

Cost optimization / resource optimization (CAPEX / OPEX)

CapEx vs OpEx in cloud computing

4.3 Developing procedures to ensure the reliability of solutions in production (e.g., chaos engineering, penetration testing)

Chaos: Break your systems to make the unbreakable

Google Cloud penetration testing

Section 5. Managing implementation

5.1 Advising development/operation team(s) to ensure successful deployment of the solution. Considerations include:

Application development

Developing made easy on Google Cloud Platform

Build cloud applications

API best practices

API design guide

Design & manage APIs: Best practices & common pitfalls

Testing frameworks (load/unit/integration)

Load testing and monitoring AI Platform models

Distributed load testing using Google Kubernetes Engine

Developing unit tests

Continuous integration testing with Cloud Build

Data and system migration and management tooling

Management tools

Management tools

5.2 Interacting with Google Cloud programmatically. Considerations include:

Google Cloud Shell

Running gcloud commands with Cloud Shell

Google Cloud SDK (gcloud, gsutil and bq)

Cloud SDK

Installing the gcloud CLI

gsutil tool

Using the bq command-line tool

Cloud Emulators (e.g. Cloud Bigtable, Datastore, Spanner, Pub/Sub, Firestore)

Use the emulator for Cloud Bigtable

Running the Datastore Emulator

Using the Cloud Spanner Emulator

Testing apps locally with the emulator

gcloud beta emulators firestore

Section 6. Ensuring solution and operations reliability

6.1 Monitoring/logging/profiling/alerting solution

How to get started with Google Cloud Monitoring?

Centralized logging solution for Google Cloud Platform

Measure app performance by using Cloud Profiler

See how your code executes with Stackdriver Profiler

Alerting best practices for Google Cloud Monitoring

6.2 Deployment and release management

Google Cloud Deploy automates deploys to GKE

Best practices for securing your cloud deployment

Release Management

6.3 Assisting with the support of deployed solutions

Support Hub | Google Cloud

Active Assist Cloud Management

6.4 Evaluating quality control measures

Cloud Compliance & regulations resources

This brings us to the end of the GCP Professional Cloud Architect Study Guide.

What do you think? Let me know in the comments section if I have missed out on anything. Also, I love to hear from you about how your preparation is going on!

In case you are preparing for other GCP certification exams, check out the GCP study guide for those exams.

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