Google cloud devops course

Module 1: Introduction to DevOps and Google Cloud

1.1 Understanding DevOps Principles

Okay, here’s an explanation of the subtopic “Understanding DevOps Principles” within a Google Cloud DevOps course, focusing on a straightforward description with examples:

Core Idea: DevOps principles are the fundamental beliefs and values that guide how teams operate when adopting a DevOps approach. They emphasize collaboration, automation, continuous improvement, and customer focus to deliver software faster and more reliably.

Key Principles and Examples:

1. Collaboration and Communication: Break down silos between development and operations teams (and other teams like security, testing, etc.). Encourage open communication, shared responsibility, and a “we’re all in this together” mindset.
   • Example: Instead of developers “throwing code over the wall” to operations, have developers and operations engineers participate in sprint planning meetings together. This allows operations to provide input on deployment feasibility and developers to understand operational constraints.
2. Automation: Automate as many repeatable tasks as possible, from code building and testing to deployment and infrastructure provisioning. This reduces manual errors, increases speed, and frees up engineers for more strategic work.
   • Example: Use Infrastructure as Code (IaC) tools like Terraform or Cloud Deployment Manager to automatically create and configure Google Cloud resources (like VMs, databases, and networks) instead of manually clicking through the Cloud Console.
3. Continuous Integration (CI): Frequently integrate code changes into a central repository and automatically run tests. This helps to detect and fix bugs early in the development cycle.
   • Example: Every time a developer commits code to a Git repository, a CI pipeline automatically builds the application, runs unit tests, and performs static code analysis. If any tests fail, the developer is immediately notified.
4. Continuous Delivery (CD): Automatically deploy code changes to staging or production environments after they pass automated testing. This enables faster and more frequent releases.
   • Example: After code passes all tests in the CI pipeline, the CD pipeline automatically deploys the updated application to a staging environment for further testing. If everything looks good, it’s automatically deployed to production.
5. Continuous Monitoring and Feedback: Constantly monitor the performance and health of applications and infrastructure in production. Gather feedback from users and use it to improve the software.
   • Example: Use Cloud Monitoring to track metrics like CPU utilization, memory usage, and response times of your applications. Set up alerts to notify engineers when performance thresholds are breached. Collect user feedback through surveys or in-app feedback forms and use it to prioritize bug fixes and new features.
6. Infrastructure as Code (IaC): Treat infrastructure configuration as code, enabling version control, automation, and repeatability.
   • Example: Using Terraform configurations to define the exact specifications of your Kubernetes cluster on Google Kubernetes Engine (GKE). This allows you to recreate the same environment reliably and consistently.
7. Embrace Failure: View failures as opportunities to learn and improve. Conduct blameless postmortems to identify the root causes of incidents and implement changes to prevent them from happening again.
   • Example: After a production outage, the team conducts a blameless postmortem to analyze the cause of the failure. The goal isn’t to blame individuals, but to identify systemic issues that contributed to the outage and implement improvements to the process or the infrastructure.
8. Customer-Centric Action: Focus on delivering value to customers. Prioritize features and improvements based on customer needs and feedback.
   • Example: A/B test new features on a small subset of users to measure their impact on key metrics like user engagement or conversion rates. Use this data to make informed decisions about whether to roll out the feature to all users.

In essence: Understanding DevOps principles means recognizing how these concepts work together to create a culture of continuous improvement and rapid, reliable software delivery within an organization. It’s about how teams work, not just what tools they use.

1.2 Google Cloud Platform Overview

1.3 DevOps on Google Cloud: Benefits and Use Cases

Module 2: Infrastructure as Code (IaC) with Terraform

2.1 Terraform Basics and Configuration

2.2 Managing Google Cloud Resources with Terraform

2.3 Terraform Modules and Best Practices

Module 3: Containerization with Docker and Kubernetes on GKE

3.1 Docker Fundamentals and Containerization

3.2 Kubernetes Basics and GKE Setup

3.3 Deploying and Managing Applications on GKE

3.4 Scaling and Autoscaling Kubernetes Deployments

Module 4: Implement CI/CD with Google Cloud Tools

4.1 Cloud Build Configuration and Pipelines

4.2 Automated Testing and Code Quality Checks

4.3 Deployment Strategies (Blue/Green, Canary)

4.4 Integrating CI/CD with Version Control Systems (Git)

Module 5: Configuration Management with Ansible

5.1 Ansible Fundamentals and Playbooks

5.2 Automating Infrastructure Configuration with Ansible on GCP

5.3 Managing User Accounts and Permissions with Ansible

Module 6: Monitoring and Logging with Google Cloud Operations (formerly Stackdriver)

6.1 Setting up Cloud Logging and Monitoring

6.2 Creating Dashboards and Alerts

6.3 Troubleshooting Applications with Cloud Trace and Profiler

Module 7: Security Best Practices in Google Cloud DevOps

7.1 IAM Roles and Permissions Management

7.2 Network Security (Firewall Rules, VPC)

7.3 Secret Management with Google Cloud Secret Manager

Module 8: Automation with Google Cloud Tools

8.1 Using Cloud Functions for Event-Driven Automation

8.2 Cloud Scheduler for Scheduled Tasks

8.3 Automating Infrastructure Management with Cloud SDK and gcloud CLI