Google Cloud Professional Engineer

Introduction:

The Google Cloud Professional Engineer course is designed to prepare participants for the Google Cloud Professional Cloud Engineer certification, equipping them with the knowledge and skills to design, develop, and manage robust, scalable, and secure cloud architectures on Google Cloud Platform (GCP). The course covers essential GCP services like Compute Engine, Kubernetes Engine, BigQuery, Cloud Storage, and VPC Networking, as well as best practices for security, automation, and cost optimization. Whether you're an aspiring cloud engineer or IT professional, this course will help you master GCP for enterprise-level cloud solutions.

Course Objective:

By the end of this course, participants will:

• Understand key components and services of Google Cloud Platform (GCP).

• Learn to design and implement cloud-based solutions using GCP services.

• Gain hands-on experience with GCP products such as Compute Engine, Kubernetes Engine, and Cloud SQL.

• Implement best practices for cloud security, networking, and identity management.

• Manage GCP resources efficiently using Cloud Monitoring, Cloud IAM, and Cloud Billing.

• Prepare for the Google Cloud Professional Cloud Engineer certification exam.

Course Outline:

Module 1: Introduction to Google Cloud Platform (GCP)

• Overview of Google Cloud Platform (GCP) services and architecture.

• Understanding GCP’s global infrastructure and key services.

• Introduction to GCP regions, zones, and projects.

• Hands-On: Setting up your first GCP project and managing resources.

Module 2: Compute Services on Google Cloud

• Introduction to Compute Engine: Virtual machines (VMs) and auto-scaling.

• Creating and managing VMs on GCP.

• Introduction to Google Kubernetes Engine (GKE): Container orchestration.

• Deploying and managing Kubernetes clusters on GCP.

• Hands-On: Creating and deploying VMs and Kubernetes clusters.

Module 3: Networking in Google Cloud

• Introduction to Google Cloud VPC Networking: Subnets, firewalls, and VPNs.

• Managing network routing and peering in GCP.

• Load balancing in GCP: HTTP(S) Load Balancer, Network Load Balancer.

• Securing network traffic with Cloud Armor and SSL certificates.

• Hands-On: Configuring VPC networks, firewalls, and load balancers.

Module 4: Google Cloud Storage and Databases

• Overview of Cloud Storage: Buckets, objects, and lifecycle management.

• Managing relational databases with Cloud SQL.

• Introduction to BigQuery for data analytics and warehousing.

• NoSQL solutions with Cloud Firestore and Bigtable.

• Hands-On: Configuring storage and managing databases in GCP.

Module 5: Identity and Access Management (IAM) in GCP

• Introduction to Cloud IAM: Managing users, roles, and permissions.

• Best practices for identity management and access control in GCP.

• Setting up multi-factor authentication (MFA) and identity federation.

• Hands-On: Configuring IAM roles and policies for security.

Module 6: Security and Compliance in Google Cloud

• Best practices for securing GCP resources.

• Encrypting data at rest and in transit with Cloud KMS.

• Implementing Google Cloud Security Command Center for threat detection.

• Managing compliance and audits with Cloud Audit Logs.

• Hands-On: Implementing security best practices and compliance tools.

Module 7: Automation and Management on Google Cloud

• Introduction to Google Cloud Deployment Manager for infrastructure automation.

• Managing GCP resources with Terraform and Cloud Functions.

• Monitoring and logging with Google Cloud Monitoring and Cloud Logging.

• Cost optimization and budget management using Cloud Billing.

• Hands-On: Automating resource deployment and managing costs in GCP.

Module 8: Hybrid and Multi-Cloud Solutions

• Overview of hybrid cloud architectures using Anthos.

• Integrating on-premise infrastructure with GCP.

• Managing multi-cloud environments with Google Cloud Interconnect.

• Hands-On: Configuring hybrid cloud solutions with Anthos and Cloud Interconnect.

Module 9: Google Cloud DevOps and CI/CD

• Introduction to DevOps practices on Google Cloud.

• Implementing Continuous Integration/Continuous Deployment (CI/CD) with Cloud Build.

• Managing version control and code repositories with Cloud Source Repositories.

• Automating deployments using Cloud Run and App Engine.

• Hands-On: Building and deploying CI/CD pipelines on GCP.

Module 10: Big Data and Machine Learning with Google Cloud

• Introduction to Google Cloud AI and Machine Learning services.

• Analyzing large datasets using BigQuery and Cloud Dataflow.

• Implementing machine learning models with AI Platform and TensorFlow.

• Hands-On: Building and deploying a machine learning solution on GCP.

Final Assessment and Certification Preparation:

• Google Cloud Professional Engineer certification exam overview.

• Practice exams and mock tests for certification.

• Final project: Designing and implementing a secure, scalable, and cost-effective solution using GCP services.

Course Duration: 40-50 hours of instructor-led or self-paced learning.
Delivery Mode: Instructor-led online/live sessions or self-paced learning modules.
Target Audience: Cloud engineers, DevOps professionals, system administrators, and anyone looking to become a Google Cloud Professional Cloud Engineer.