Google Cloud Certified – Professional Cloud Developer (Bundle)
Duration
4 Days
This track includes :
Google Cloud Fundamentals: Core Infrastructure – 1 Day
Developing Applications with Google Cloud Platform – 3 Days
Description
Introductory 1 day
This course uses lectures, demos, and hands-on labs to give you an overview of Google Cloud products and services so that you can learn the value of Google Cloud and how to incorporate cloud-based solutions into your business strategies.
Topics covered
- Infrastructure
- Application Development
- Business Transformation
- Security
Prerequisites
Familiarity with application development, systems operations, Linux operating systems, and data analytics/machine learning is helpful in understanding the technologies covered.
Objectives:
- Identify the purpose and value of Google Cloud products and services. Interact with Google Cloud services.
- Describe ways in which customers have used Google Cloud.
- Choose among and use application deployment environments on Google Cloud: App Engine, Google Kubernetes Engine, and Compute Engine.
- Choose among and use Google Cloud storage options: Cloud Storage, Cloud SQL, Cloud Bigtable, and Firestore.
- Make basic use of BigQuery, Google’s managed data warehouse for analytics.
Audience:
- Individuals planning to deploy applications and create application environments on Google Cloud.
- Developers, systems operations professionals, and solution architects getting started with Google Cloud.
- Executives and business decision makers evaluating the potential of Google Cloud to address their business needs.
Course Outline
The course includes presentations, demonstrations, and hands-on labs.
Module 1: Introducing Google Cloud Platform
- Explain the advantages of Google Cloud Platform.
- Define the components of Google’s network infrastructure, including: Points of presence, data centers, regions, and zones.
- Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS).
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.
Module 9: Summary and Review
- Summary and Review.
- What’s Next?.
Developing Applications with Google Cloud
Fundamental 3 days
Learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. This course uses lectures, demos, and hands-on labs to show you how to use Google Cloud services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications.
Topics covered
- Infrastructure
- Application Development
Prerequisites:
- Completed Google Cloud Platform Fundamentals or have equivalent experience
- Working knowledge of Node.js, Python, or Java
- Basic proficiency with command-line tools and Linux operating system environments
Objectives:
This course teaches participants the following skills:
- Use best practices for application development.
- Choose the appropriate data storage option for application data.
- Implement federated identity management.
- Develop loosely coupled application components or microservices.
- Integrate application components and data sources.
- Debug, trace, and monitor applications.
- Perform repeatable deployments with containers and deployment services.
- Choose the appropriate application runtime environment; use Google Container Engine as a runtime environment and later switch to a no-ops solution with Google App Engine flexible environment.
Audience:
Application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud Platform
Course Outline
The course includes presentations, demonstrations, and hands-on labs.
Module 1: Best Practices for Application Development
- Code and environment management.
- Design and development of secure, scalable, reliable, loosely coupled application components and microservices.
- Continuous integration and delivery.
- Re-architecting applications for the cloud.
Module 2: Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK
- How to set up and use Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK.
- Lab: Set up Google Client Libraries, Cloud SDK, and Firebase SDK on a Linux instance and set up application credentials.
Module 3: Overview of Data Storage Options
- Overview of options to store application data.
- Use cases for Google Cloud Storage, Cloud Firestore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner.
Module 4: Best Practices for Using Cloud Firestore
- Best practices related to using Cloud Firestore in Datastore mode for:Queries, Built-in and composite indexes, Inserting and deleting data (batch operations),Transactions,Error handling.
- Bulk-loading data into Cloud Firestore by using Google Cloud Dataflow.
- Lab: Store application data in Cloud Datastore.
Module 5: Performing Operations on Cloud Storage
- Operations that can be performed on buckets and objects.
- Consistency model.
- Error handling.
Module 6: Best Practices for Using Cloud Storage
- Naming buckets for static websites and other uses.
- Naming objects (from an access distribution perspective).
- Performance considerations.
- Setting up and debugging a CORS configuration on a bucket.
- Lab: Store files in Cloud Storage.
Module 7: Handling Authentication and Authorization
- Cloud Identity and Access Management (IAM) roles and service accounts.
- User authentication by using Firebase Authentication.
- User authentication and authorization by using Cloud Identity-Aware Proxy.
- Lab: Authenticate users by using Firebase Authentication.
Module 8: Using Pub/Sub to Integrate Components of Your Application
- Topics, publishers, and subscribers.
- Pull and push subscriptions.
- Use cases for Cloud Pub/Sub.
- Lab: Develop a backend service to process messages in a message queue.
Module 9: Adding Intelligence to Your Application
- Overview of pre-trained machine learning APIs such as Cloud Vision API and Cloud Natural Language Processing API.
Module 10: Using Cloud Functions for Event-Driven Processing
- Key concepts such as triggers, background functions, HTTP functions.
- Use cases.
- Developing and deploying functions.
- Logging, error reporting, and monitoring.
Module 11: Managing APIs with Cloud Endpoints
- Open API deployment configuration.
- Lab: Deploy an API for your application.
Module 12: Deploying Applications
- Creating and storing container images.
- Repeatable deployments with deployment configuration and templates.
- Lab: Use Deployment Manager to deploy a web application into Google App Engine flexible environment test and production environments.
Module 13: Execution Environments for Your Application
- Considerations for choosing an execution environment for your application or service:Google Compute Engine (GCE),Google Kubernetes Engine (GKE), App Engine flexible environment, Cloud Functions, Cloud Dataflow, Cloud Run.
- Lab: Deploying your application on App Engine flexible environment.
Module 14: Debugging, Monitoring, and Tuning Performance
- Application Performance Management Tools.
- Stackdriver Debugger.
- Stackdriver Error Reporting.
- Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting.
- Stackdriver Logging.
- Key concepts related to Stackdriver Trace and Stackdriver Monitoring.
- Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performance.
Certification
Google Cloud Certified – Professional Cloud Developer
Schedule
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*Weekend Class
