The below learning path courses are available in both Plural sight and Coursera.
Google Cloud Fundamentals: Core Infrastructure
Module 2: Getting Started with Google Cloud Platform
- Identify the purpose of projects on Google Cloud Platform.
- Understand the purpose of and use cases for Identity and Access Management.
- List the methods of interacting with Google Cloud Platform.
- Lab: Getting Started with Google Cloud Platform.
Module 3: Google Compute Engine and Networking
- Identify the purpose of and use cases for Google Compute Engine.
- Understand the basics of networking in Google Cloud Platform.
- Lab: Deploying Applications Using Google Compute Engine.
Module 4: Google Cloud Platform Storage Options
- Understand the purpose of and use cases for: Google Cloud Storage, Google Cloud SQL, and Google Cloud Bigtable.
- Learn how to choose between the various storage options on Google Cloud Platform.
- Lab: Integrating Applications with Google Cloud Storage.
Module 5: Google Container Engine
- Define the concept of a container and identify uses for containers.
- Identify the purpose of and use cases for Google Container Engine and Kubernetes.
- Introduction to Hybrid and Multi-Cloud computing (Anthos).
- Lab: Deploying Applications Using Google Container Engine.
Module 6: Google App Engine and Google Cloud Datastore
- Understand the purpose of and use cases for Google App Engine and Google Cloud Datastore.
- Contrast the App Engine Standard environment with the App Engine Flexible environment.
- Understand the purpose of and use cases for Google Cloud Endpoints.
- Lab: Deploying Applications Using App Engine and Cloud Datastore.
Module 7: Deployment and Monitoring
- Understand the purpose of template-based creation and management of resources.
- Understand the purpose of integrated monitoring, alerting, and debugging.
- Lab: Getting Started with Stackdriver and Deployment Manager.
Module 8: Big Data and Machine Learning
- Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms.
- Lab: Getting Started with BigQuery.
Architecting with Google Compute Engine
Module 2: Virtual Networks
- List the VPC objects in Google Cloud.
- Differentiate between the different types of VPC networks.
- Implement VPC networks and firewall rules.
- Implement Private Google Access and Cloud NAT.
Module 3: Virtual Machines
- Recall the CPU and memory options for virtual machines.
- Describe the disk options for virtual machines.
- Explain VM pricing and discounts.
- Use Compute Engine to create and customize VM instances.
Module 4: CloudIAM
- Describe the Cloud IAM resource hierarchy.
- Explain the different types of IAM roles.
- Recall the different types of IAM members.
- Implement access control for resources using Cloud IAM.
Module 5: Storage and Database Services
- Differentiate between Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Firestore and Cloud Bigtable.
- Choose a data storage service based on your requirements.
- Implement data storage services.
Module 6: Resource Management
- Describe the cloud resource manager hierarchy.
- Recognize how quotas protect Google Cloud customers.
- Use labels to organize resources.
- Explain the behavior of budget alerts in Google Cloud.
- Examine billing data with BigQuery.
Module 7: Resource Monitoring
- Describe the services for monitoring, logging, error reporting, tracing, and debugging.
- Create charts, alerts, and uptime checks for resources with Cloud Monitoring.
- Use Cloud Debugger to identify and fix errors.
Module 8: Interconnecting Networks
- Recall the Google Cloud interconnect and peering services available to connect your infrastructure to Google Cloud.
- Determine which Google Cloud interconnect or peering service to use in specific circumstances.
- Create and configure VPN gateways.
- Recall when to use Shared VPC and when to use VPC Network Peering.
Module 9: Load Balancing and Autoscaling
- Recall the various load balancing services.
- Determine which Google Cloud load balancer to use in specific circumstances.
- Describe autoscaling behavior.
- Configure load balancers and autoscaling.
Module 10: Infrastructure Modernization
- Automate the deployment of Google Cloud services using Deployment Manager or Terraform.
- Outline the Google Cloud Marketplace.
Module 11: Managed Services
- Describe the managed services for data processing in Google Cloud.
Architecting with Google Cloud: Design and Process
Module 1: Defining the Service
- Describe users in terms of roles and personas.
- Write qualitative requirements with user stories.
- Write quantitative requirements using key performance indicators (KPIs).
- Evaluate KPIs using SLOs and SLIs.
- Determine the quality of application requirements using SMART criteria.
Module 2: Microservice Design and Architecture
- Decompose monolithic applications into microservices.
- Recognize appropriate microservice boundaries.
- Architect stateful and stateless services to optimize scalability and reliability.
- Implement services using 12-factor best practices.
- Build loosely coupled services by implementing a well-designed REST architecture.
- Design consistent, standard RESTful service APIs.
Module 3: DevOps Automation
- Automate service deployment using CI/CD pipelines.
- Leverage Cloud Source Repositories for source and version control.
- Automate builds with Cloud Build and build triggers.
- Manage container images with Google Container Registry.
- Create infrastructure with code using Deployment Manager and Terraform.
Module 4: Choosing Storage Solutions
- Choose the appropriate Google Cloud data storage service based on use case, durability, availability, scalability and cost.
- Store binary data with Cloud Storage.
- Store relational data using Cloud SQL and Spanner.
- Store NoSQL data using Firestore and Cloud Bigtable.
- Cache data for fast access using Memorystore.
- Build a data warehouse using BigQuery.
Module 5: Google Cloud and Hybrid Network Architecture
- Design VPC networks to optimize for cost, security, and performance.
- Configure global and regional load balancers to provide access to services.
- Leverage Cloud CDN to provide lower latency and decrease network egress.
- Evaluate network architecture using the Cloud Network Intelligence Center.
- Connect networks using peering and VPNs.
- Create hybrid networks between Google Cloud and on-premises data centers using Cloud Interconnect.
Module 6: Deploying Applications to Google Cloud
- Choose the appropriate Google Cloud deployment service for your applications.
- Configure scalable, resilient infrastructure using Instance Templates and Groups.
- Orchestrate microservice deployments using Kubernetes and GKE.
- Leverage App Engine for a completely automated platform as a service (PaaS).
- Create serverless applications using Cloud Functions.
Module 7: Designing Reliable Systems
- Design services to meet requirements for availability, durability, and scalability.
- Implement fault-tolerant systems by avoiding single points of failure, correlated failures, and cascading failures.
- Avoid overload failures with the circuit breaker and truncated exponential backoff design patterns.
- Design resilient data storage with lazy deletion.
- Analyze disaster scenarios and plan for disaster recovery using cost/risk analysis.
Module 8: Security
- Design secure systems using best practices like separation of concerns, principle of least privilege, and regular audits.
- Leverage Cloud Security Command Center to help identify vulnerabilities.
- Simplify cloud governance using organizational policies and folders.
- Secure people using IAM roles, Identity-Aware Proxy, and Identity Platform.
- Manage the access and authorization of resources by machines and processes using service accounts.
- Secure networks with private IPs, firewalls, and Private Google Access.
- Mitigate DDoS attacks by leveraging Cloud DNS and Cloud Armor.
Module 9: Maintenance and Monitoring
- Manage new service versions using rolling updates, blue/green deployments, and canary releases.
- Forecast, monitor, and optimize service cost using the Google Cloud pricing calculator and billing reports and by analyzing billing data.
- Observe whether your services are meeting their SLOs using Cloud Monitoring and Dashboards.
- Use Uptime Checks to determine service availability.
- Respond to service outages using Cloud Monitoring Alerts.
Getting started with Google Kubernetes Engine
Module 2: Containers and Kubernetes in Google Cloud
- Create a container using Cloud Build.
- Store a container in Container Registry.
- Understand the relationship between Kubernetes and Google Kubernetes Engine (GKE).
- Understand how to choose among Google Cloud Compute platforms.
Module 3: Kubernetes Architecture
- Understand the architecture of Kubernetes: pods, namespaces.
- Understand the control-plane components of Kubernetes.
- Create container images using Cloud Build.
- Store container images in Container Registry.
- Create a Kubernetes engine cluster.
Module 4: Introduction to Kubernetes Workloads
- The kubectl command.
- Introduction to deployments.
- Pod networking.
- Volumes overview.