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.
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.
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.
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.
5 - Performing Operations on Cloud Storage
Operations that can be performed on buckets and objects.Consistency model.Error handling.
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.
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.
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.
9 - Adding Intelligence to Your Application
Overview of pre-trained machine learning APIs such as Cloud Vision API and Cloud Natural Language Processing API.
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.
11 - Managing APIs with Cloud Endpoints
Open API deployment configuration.Lab: Deploy an API for your application.
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.
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.
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.
Actual course outline may vary depending on offering center. Contact your sales representative for more information.