Google Cloud Platform Training Program
Harness the Power of Google Cloud Platform
Google Cloud Platform Training Program Overview
Google is a global leader in technology, with its infrastructure supporting over 6 billion active users daily. The same robust infrastructure powering services like Google Workspace and Google Search also underpins Google Cloud Platform (GCP), making it a highly reliable, efficient, and scalable cloud service. GCP is trusted by thousands of companies, including many in the Fortune 500.
In recent years, Google Cloud Platform has been one of the fastest-growing public cloud providers, with a remarkable growth rate of 55% in 2020 and 2021. This makes GCP a solid choice for anyone looking to build a secure and dynamic career in the cloud computing industry.
Program Overview
Our Google Cloud & DevOps Training Program is a six-month course designed to prepare you for in-demand cloud careers, including:
- Solutions Architect
- Cloud Engineer
- DevOps Engineer
- Security Architect/Engineer
Whether you’re new to IT or looking to transition into the cloud space, this program is structured to take you from basic skills to becoming a proficient cloud professional. The training is hands-on, and you’ll gain the technical expertise needed to succeed in today’s competitive market.
In addition to technical training, we offer:
- Interview preparation: Ensuring you’re ready for job interviews.
- Resume development: Helping you craft a resume that highlights the skills gained during the program.
Certification Preparation
Upon completing the course, you’ll be fully prepared to take the following Google Cloud certification exams:
- Google Cloud Solutions Architect Associate (GCSA)
- Google Associate Cloud Engineer (GACE)
- Google Cloud DevOps Engineer (GCDE)
Course Fees
The entire End-to-End Training Program is available for $1,000, with a flexible payment option. You can start with a $400 deposit, followed by monthly payments of $200 for the remaining balance.
Course Prerequisites
No prior IT experience is required. We guide you step by step, providing all the knowledge and resources needed to succeed. All you need is the motivation to learn and grow in the cloud industry.
For a detailed curriculum and training schedule, please refer to our latest technology stack.
What You’ll Need
- Laptop
- Notebook/Desktop
- Passion
Curriculum
GCP DevOps Training Program
Module 1: Introduction to Google Cloud Platform
1.1 Cloud Computing Basics
- What is Cloud Computing?: Overview of IaaS, PaaS, and SaaS.
- GCP Overview: Understanding GCP’s global infrastructure, regions, zones, and edge locations.
- Google Cloud Platform Services: Compute, Storage, Networking, and Databases.
- GCP vs Other Cloud Providers: Key differences between GCP, AWS, and Azure.
1.2 Introduction to GCP Core Services
- Compute Services: Google Compute Engine (VMs), Google Kubernetes Engine (GKE), App Engine.
- Storage Services: Google Cloud Storage, Persistent Disks, Filestore.
- Networking Services: Virtual Private Cloud (VPC), Cloud Load Balancing, Cloud CDN, Cloud Interconnect.
- Database Services: Cloud SQL, Bigtable, Firestore, Datastore, Spanner.
1.3 Identity and Access Management (IAM)
- GCP IAM Overview: Users, Roles, and Policies.
- Managing Permissions: Assigning and managing roles for resource access.
- Service Accounts: Managing and securing applications with service accounts.
1.4 Cost Management and Billing
- GCP Pricing Models: On-demand, Preemptible VMs, Committed Use Discounts.
- Budgeting and Monitoring: Using Google Cloud Billing to track usage and manage costs.
Hands-On Labs:
- Setting up a GCP account and managing projects.
- Deploying a virtual machine (VM) on Google Compute Engine.
- Configuring roles and permissions using IAM.
- Setting up budgets and monitoring costs.
Module 2: DevOps Fundamentals with GCP
2.1 Introduction to DevOps
- DevOps Principles: Collaboration, automation, continuous integration (CI), and continuous delivery (CD).
- DevOps on GCP: How GCP supports DevOps culture and practices.
- Version Control with Git: Working with Git repositories and managing source code.
2.2 CI/CD Pipelines
- Continuous Integration (CI): Automating code integration using Cloud Build.
- Continuous Delivery (CD): Deploying applications using Cloud Deploy and Cloud Run.
- Google Kubernetes Engine (GKE): Managing CI/CD pipelines with GKE.
2.3 Infrastructure as Code (IaC)
- Introduction to IaC: Benefits of managing infrastructure as code.
- Terraform on GCP: Automating resource provisioning using Terraform.
- Google Cloud Deployment Manager: Automating GCP resource creation using templates.
2.4 Containers and Container Orchestration
- Introduction to Containers: Docker fundamentals and containerization.
- Container Orchestration with Kubernetes: Deploying and managing Kubernetes clusters on GKE.
- Google Cloud Run: Serverless containerization with Cloud Run for automatic scaling.
Hands-On Labs:
- Building and deploying a CI/CD pipeline with Cloud Build and Cloud Run.
- Creating and managing GKE clusters for containerized applications.
- Writing Terraform configurations to deploy GCP infrastructure.
- Containerizing a sample application using Docker and deploying to GKE.
Module 3: Intermediate GCP DevOps Practices
3.1 Advanced CI/CD Automation
- Advanced CI/CD Pipelines: Using Cloud Build and Cloud Deploy for multi-environment deployment.
- GitOps with GCP: Automating Kubernetes deployments using GitOps practices.
- Jenkins on GCP: Setting up Jenkins for CI/CD pipelines in GCP environments.
3.2 Monitoring and Logging
- Google Cloud Operations Suite (formerly Stackdriver): Monitoring and logging in GCP.
- Cloud Monitoring: Setting up metrics, dashboards, and alerts for infrastructure and applications.
- Cloud Logging: Collecting and analyzing logs for debugging and security auditing.
3.3 Security in DevOps (DevSecOps)
- DevSecOps Principles: Integrating security into DevOps practices.
- Identity Management: Implementing robust identity and access management strategies.
- Securing CI/CD Pipelines: Using Google Key Management Service (KMS) and Secret Manager for securing credentials.
3.4 GCP Networking
- Advanced VPC Configurations: VPC peering, shared VPCs, and network segmentation.
- Hybrid Connectivity: Configuring VPN and Interconnect for hybrid cloud environments.
- Load Balancing and Traffic Management: Using HTTP(S), TCP, and SSL Load Balancers.
Hands-On Labs:
- Implementing multi-environment CI/CD pipelines with Cloud Build.
- Setting up monitoring and alerts for GKE clusters using Cloud Monitoring.
- Configuring Google Key Management Service (KMS) for securing pipelines.
- Setting up a VPN for hybrid connectivity between on-prem and GCP.
Module 4: Advanced GCP DevOps and Automation
4.1 Serverless DevOps and Event-Driven Architectures
- Google Cloud Functions: Building event-driven serverless architectures.
- Cloud Pub/Sub: Messaging for asynchronous application integration.
- Cloud Tasks and Cloud Scheduler: Automating workflows and task scheduling.
4.2 Infrastructure as Code – Advanced
- Managing Infrastructure at Scale with Terraform: Best practices for multi-environment deployments using Terraform.
- Advanced Google Cloud Deployment Manager: Building complex deployments with deployment templates and modules.
- CI/CD Pipeline for IaC: Automating infrastructure deployment using Cloud Build and Terraform.
4.3 Cloud Security and Compliance
- Google Cloud Security Best Practices: Implementing network security, firewall rules, and encryption.
- Google Cloud Security Command Center (SCC): Monitoring and managing cloud security risks.
- Compliance Automation: Managing regulatory requirements and automating compliance with GCP tools.
4.4 Data Processing and Big Data Tools
- BigQuery for Data Analytics: Managing and querying large datasets in GCP.
- Dataflow and Dataproc: Building data pipelines and running batch/stream processing jobs.
- Cloud Composer (Apache Airflow): Orchestrating workflows for automated data processing.
Hands-On Labs:
- Building a serverless application using Google Cloud Functions and Pub/Sub.
- Deploying multi-environment infrastructure using Terraform and Cloud Build.
- Configuring security monitoring with Google Cloud Security Command Center (SCC).
- Analyzing large datasets using BigQuery and building data pipelines with Dataflow.
Module 5: Security and Governance in GCP
5.1 Governance and Compliance Automation
- IAM Governance Best Practices: Implementing role-based access control (RBAC) and managing least privilege.
- Audit Logging and Cloud Asset Inventory: Monitoring and tracking changes to resources in GCP.
- Google Organization Policies: Implementing policies for governance and compliance across multiple projects.
5.2 Securing GCP Infrastructure
- Firewall Rules and VPC Service Controls: Implementing network security policies.
- Identity-Aware Proxy (IAP): Securing access to apps and services without using a VPN.
- Data Encryption: Managing encryption for data at rest and in transit with Cloud KMS.
5.3 Monitoring and Incident Response
- Real-time Monitoring with Cloud Monitoring: Setting up alerting systems and custom dashboards.
- Google Cloud Operations Suite: Monitoring, logging, and error reporting in production environments.
- Automated Incident Response: Using Cloud Functions for incident response automation.
Hands-On Labs:
- Configuring IAM roles and audit logging for governance.
- Implementing network security with firewall rules and VPC Service Controls.
- Setting up real-time monitoring and incident response automation.
Module 6: Linux and Open-Source Tools for GCP DevOps
6.1 Introduction to Linux for DevOps
- Linux Fundamentals: Command-line basics, managing users and file permissions.
- Remote Management: Using SSH and secure access to Linux instances on GCP.
- Linux Scripting: Writing Bash scripts to automate tasks in Linux environments.
6.2 Configuration Management and Automation with Ansible
- Ansible Basics: Setting up Ansible to automate configuration and deployment on GCP.
- Playbooks and Roles: Writing Ansible playbooks and managing roles for multi-node deployments.
- GCP Modules in Ansible: Automating GCP resource provisioning using Ansible GCP modules.
6.3 Docker and Kubernetes on Linux
- Docker on Linux: Installing Docker and managing containers on Linux environments.
- Kubernetes and GKE: Deploying Kubernetes clusters with GKE and managing workloads using kubectl.
- Monitoring and Scaling with Linux Tools: Using Prometheus and Grafana for monitoring containers and Kubernetes clusters.
Hands-On Labs:
- Managing Linux VMs on GCP with SSH and writing automation scripts.
- Automating GCP infrastructure deployment with Ansible and GCP modules.
- Setting up Docker containers and Kubernetes clusters on Linux.
Module 7: Capstone Project – End-to-End DevOps Implementation in GCP
Participants will complete a capstone project
Course Duration and Enrollment Details
Upcoming Batch Details:
🔷 Training Start Date: November 23, 2024
🔷 Enrollment Deadline: November 15, 2024
🔷 Duration: 6 Months
Pricing Options
🔷 Discounted Rate: $1000 USD
🔷 Payment Plan:
- Initial Deposit: $400 USD
- Monthly Payment: $200 USD
🔷 One-Time Payment Option: $800 USD
Please note: All sales and payments are final – NO REFUNDS.
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