GCA + GCP ( Combined)

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Google Cloud Associate (GCA): This certification is designed for individuals who are new to Google Cloud and want to establish a foundational understanding of its core services and capabilities.
Google Cloud Professional (GCP): This refers to one of the more advanced Google Cloud certifications, such as the Professional Cloud Architect (PCA), Professional Data Engineer (PDE), or other specialized professional-level certifications.

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Overview

The Syllabus

Curriculum Designed by Experts

Associate Cloud Engineer & GCP

Setting up a Google Cloud Environment:
- Creating and managing projects and billing accounts.
- Enabling and disabling services.
- Managing access control using IAM (Identity and Access Management).

GCP Computing:

- Understanding Google Compute Engine (GCE) and deploying virtual machines.
- Autoscaling and load balancing.
- Working with containers and Kubernetes Engine.

GCP Storage Services:

- Understanding and using Google Cloud Storage.
- Deploying and managing Cloud SQL and Cloud Spanner databases.
- Working with Cloud Firestore and Firebase Realtime Database.

GCP Networking:

- Setting up Virtual Private Cloud (VPC) networks.
- Configuring firewall rules.
- Implementing VPNs and Interconnect.

GCP Identity and Access Management:

- Managing IAM roles and permissions.
- Securing service accounts.
- Configuring resource-level permissions.

GCP Deployment and Monitoring:

- Deploying applications using Cloud Deployment Manager and Google Kubernetes Engine.
- Configuring monitoring and logging with Stackdriver (now called Google Cloud Operations).

GCP Services:

- Understanding various GCP services like Cloud Pub/Sub, Cloud Functions, and Cloud Run.
- Integrating services to build scalable and reliable applications.

GCP Security:

- Securing GCP resources using IAM, Cloud Identity-Aware Proxy (IAP), and other security features.
- Managing encryption and key management.

GCP Pricing and Cost Management:

- Understanding GCP pricing models.
- Managing and optimizing GCP costs.
- Setting up billing alerts and budgets.

Troubleshooting and Diagnostics:

- Identifying and resolving common issues.
- Using monitoring and logging tools to diagnose problems

1. Designing and planning a cloud solution architecture

1.1 Designing a solution infrastructure that meets business requirements

Business use cases and product strategy
Cost optimization
Supporting the application design
Integration with external systems
Movement of data
Design decision trade-offs
Build, buy, modify, or deprecate
Success measurements (e.g., key performance indicators [KPI], return on investment [ROI], metrics)
Compliance and observability

1.2 Designing a solution infrastructure that meets technical requirements

High availability and failover design
Elasticity of cloud resources with respect to quotas and limits
Scalability to meet growth requirements
Performance and latency

1.3 Designing network, storage, and compute resources

Integration with on-premises/multi-cloud environments
Cloud-native networking (VPC, peering, firewalls, container networking)
Choosing data processing technologies
Choosing appropriate storage types (e.g., object, file, databases)
Choosing compute resources (e.g., preemptible, custom machine type, specialized workload)
Mapping compute needs to platform products

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

Integrating solutions with existing systems
Migrating systems and data to support the solution
Software license mapping
Network planning
Testing and proofs of concept
Dependency management planning

1.5 Envisioning future solution improvements

Cloud and technology improvements
Evolution of business needs
Evangelism and advocacy

2. Managing and provisioning a solution infrastructure

2.1 Configuring network topologies

Extending to on-premises environments (hybrid networking)
Extending to a multi-cloud environment that may include Google Cloud to Google Cloud communication
Security protection (e.g. intrusion protection, access control, firewalls)

2.2 Configuring individual storage systems

Data storage allocation
Data processing/compute provisioning
Security and access management
Network configuration for data transfer and latency
Data retention and data life cycle management
Data growth planning

2.3 Configuring compute systems

Compute resource provisioning
Compute volatility configuration (preemptible vs. standard)
Network configuration for compute resources (Google Compute Engine, Google Kubernetes Engine, server less networking)
Infrastructure orchestration, resource configuration, and patch management
Container orchestration

3. Designing for security and compliance

3.1 Designing for security

Identity and access management (IAM)
Resource hierarchy (organizations, folders, projects)
Data security (key management, encryption, secret management)
Separation of duties (SoD)
Security controls (e.g., auditing, VPC Service Controls, context aware access, organization policy)
Managing customer-managed encryption keys with Cloud Key Management Service
Remote access

3.2 Designing for compliance

Legislation (e.g., health record privacy, children’s privacy, data privacy, and ownership)
Commercial (e.g., sensitive data such as credit card information handling, personally identifiable information [PII])
Industry certifications (e.g., SOC 2)
Audits (including logs)

4. Analyzing and optimizing technical and business processes

4.1 Analyzing and defining technical processes

Software development life cycle (SDLC)
Continuous integration / continuous deployment
Troubleshooting / root cause analysis best practices
Testing and validation of software and infrastructure
Service catalog and provisioning
Business continuity and disaster recovery

4.2 Analyzing and defining business processes

Stakeholder management (e.g. influencing and facilitation)
Change management
Team assessment / skills readiness
Decision-making processes
Customer success management
Cost optimization / resource optimization (capex / opex)

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

5. Managing implementation

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

Application development
API best practices
Testing frameworks (load/unit/integration)
Data and system migration and management tooling

5.2 Interacting with Google Cloud programmatically

Google Cloud Shell
Google Cloud SDK (gcloud, gsutil and bq)
Cloud Emulators (e.g. Cloud Bigtable, Datastore, Spanner, Pub/Sub, Firestore)

6. Ensuring solution and operations reliability

6.1 Monitoring/logging/profiling/alerting solution

6.2 Deployment and release management

6.3 Assisting with the support of deployed solutions

6.4 Evaluating quality control measures

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