Developing Applications with Google Cloud

Developing Applications with Google CloudDAGCPGOGoogleGO-DAGCP2.0<p>This course teaches participants the following skills:</p> <ul> <li>Use best practices for application development</li><li>Choose the appropriate data storage option for application data</li><li>Implement federated identity management</li><li>Develop loosely coupled application components or microservices</li><li>Integrate application components and data sources</li><li>Debug, trace, and monitor applications</li><li>Perform repeatable deployments with containers and deployment services</li><li>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 Flex</li></ul><p>To get the most of out of this course, participants should have:</p> <ul> <li>Completed Google Cloud Platform Fundamentals or have equivalent experience</li><li>Working knowledge of Node.js</li><li>Basic proficiency with command-line tools and Linux operating system environments</li></ul><p>Application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud Platform.</p><h5>Module 1: Best Practices for Application Development</h5><ul> <li>Code and environment management</li><li>Design and development of secure, scalable, reliable, loosely coupled application components and microservices</li><li>Continuous integration and delivery</li><li>Re-architecting applications for the cloud</li></ul><h5>Module 2: Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK</h5><ul> <li>How to set up and use Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK</li><li>Lab: Set up Google Client Libraries, Google Cloud SDK, and Firebase SDK on a Linux instance and set up application credentials</li></ul><h5>Module 3: Overview of Data Storage Options</h5><ul> <li>Overview of options to store application data</li><li>Use cases for Google Cloud Storage, Google Cloud Datastore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner</li></ul><h5>Module 4: Best Practices for Using Cloud Datastore</h5><ul> <li>Best practices related to the following: <ul> <li>Queries</li><li>Built-in and composite indexes</li><li>Inserting and deleting data (batch operations)</li><li>Transactions</li><li>Error handling</li></ul></li><li>Bulk-loading data into Cloud Datastore by using Google Cloud Dataflow</li><li>Lab: Store application data in Cloud Datastore</li></ul><h5>Module 5: Performing Operations on Buckets and Objects</h5><ul> <li>Operations that can be performed on buckets and objects</li><li>Consistency model</li><li>Error handling</li></ul><h5>Module 6: Best Practices for Using Cloud Storage</h5><ul> <li>Naming buckets for static websites and other uses</li><li>Naming objects (from an access distribution perspective)</li><li>Performance considerations</li><li>Setting up and debugging a CORS configuration on a bucket</li><li>Lab: Store files in Cloud Storage</li></ul><h5>Module 7: Securing Your Application</h5><ul> <li>Cloud Identity and Access Management (IAM) roles and service accounts</li><li>User authentication by using Firebase Authentication</li><li>User authentication and authorization by using Cloud Identity-Aware Proxy</li><li>Lab: Authenticate users by using Firebase Authentication</li></ul><h5>Module 8: Using Google Cloud Pub/Sub to Integrate Components of Your Application</h5><ul> <li>Topics, publishers, and subscribers</li><li>Pull and push subscriptions</li><li>Use cases for Cloud Pub/Sub</li><li>Lab: Develop a backend service to process messages in a message queue</li></ul><h5>Module 9: Adding Intelligence to Your Application</h5><ul> <li>Overview of pre-trained machine learning APIs such as Cloud Vision API and Cloud Natural Language Processing API</li></ul><h5>Module 10: Using Cloud Functions for Event-Driven Processing</h5><ul> <li>Key concepts such as triggers, background functions, HTTP functions</li><li>Use cases</li><li>Developing and deploying functions</li><li>Logging, error reporting, and monitoring</li></ul><h5>Module 11: Using Cloud Endpoints to Deploy APIs</h5><ul> <li>Open API deployment configuration</li><li>Lab: Deploy an API for your application</li></ul><h5>Module 12: Debugging Your Application by Using Google Stackdriver</h5><ul> <li>Stackdriver Debugger</li><li>Stackdriver Error Reporting</li><li>Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting</li></ul><h5>Module 13: Deploying an Application by Using Google Cloud Container Builder, Google Cloud Container Registry, and Google Cloud Deployment Manager</h5><ul> <li>Creating and storing container images</li><li>Repeatable deployments with deployment configuration and templates</li><li>Lab: Use Deployment Manager to deploy a web application into Google App Engine Flex test and production environments</li></ul><h5>Module 14: Execution Environments for Your Application</h5><ul> <li>Considerations for choosing an execution environment for your application or service: <ul> <li>Google Compute Engine</li><li>Container Engine</li><li>App Engine Flex</li><li>Cloud Functions</li><li>Cloud Dataflow</li></ul></li><li>Lab: Deploying your application on App Engine Flex</li></ul><h5>Module 15: Monitoring and Tuning Performance</h5><ul> <li>Best practices and watchpoints for performance</li><li>Key concepts related to Stackdriver Trace and Stackdriver Monitoring</li><li>Detecting and resolving performance issues</li><li>Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performance</li></ul><h5>Module 1: Best Practices for Application Development</h5><ul> <li>Code and environment management</li><li>Design and development of secure, scalable, reliable, loosely coupled application components and microservices</li><li>Continuous integration and delivery</li><li>Re-architecting applications for the cloud</li></ul><h5>Module 2: Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK</h5><ul> <li>How to set up and use Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK</li><li>Lab: Set up Google Client Libraries, Google Cloud SDK, and Firebase SDK on a Linux instance and set up application credentials</li></ul><h5>Module 3: Overview of Data Storage Options</h5><ul> <li>Overview of options to store application data</li><li>Use cases for Google Cloud Storage, Google Cloud Datastore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner</li></ul><h5>Module 4: Best Practices for Using Cloud Datastore</h5><ul> <li>Best practices related to the following: <ul> <li>Queries</li><li>Built-in and composite indexes</li><li>Inserting and deleting data (batch operations)</li><li>Transactions</li><li>Error handling</li></ul></li><li>Bulk-loading data into Cloud Datastore by using Google Cloud Dataflow</li><li>Lab: Store application data in Cloud Datastore</li></ul><h5>Module 5: Performing Operations on Buckets and Objects</h5><ul> <li>Operations that can be performed on buckets and objects</li><li>Consistency model</li><li>Error handling</li></ul><h5>Module 6: Best Practices for Using Cloud Storage</h5><ul> <li>Naming buckets for static websites and other uses</li><li>Naming objects (from an access distribution perspective)</li><li>Performance considerations</li><li>Setting up and debugging a CORS configuration on a bucket</li><li>Lab: Store files in Cloud Storage</li></ul><h5>Module 7: Securing Your Application</h5><ul> <li>Cloud Identity and Access Management (IAM) roles and service accounts</li><li>User authentication by using Firebase Authentication</li><li>User authentication and authorization by using Cloud Identity-Aware Proxy</li><li>Lab: Authenticate users by using Firebase Authentication</li></ul><h5>Module 8: Using Google Cloud Pub/Sub to Integrate Components of Your Application</h5><ul> <li>Topics, publishers, and subscribers</li><li>Pull and push subscriptions</li><li>Use cases for Cloud Pub/Sub</li><li>Lab: Develop a backend service to process messages in a message queue</li></ul><h5>Module 9: Adding Intelligence to Your Application</h5><ul> <li>Overview of pre-trained machine learning APIs such as Cloud Vision API and Cloud Natural Language Processing API</li></ul><h5>Module 10: Using Cloud Functions for Event-Driven Processing</h5><ul> <li>Key concepts such as triggers, background functions, HTTP functions</li><li>Use cases</li><li>Developing and deploying functions</li><li>Logging, error reporting, and monitoring</li></ul><h5>Module 11: Using Cloud Endpoints to Deploy APIs</h5><ul> <li>Open API deployment configuration</li><li>Lab: Deploy an API for your application</li></ul><h5>Module 12: Debugging Your Application by Using Google Stackdriver</h5><ul> <li>Stackdriver Debugger</li><li>Stackdriver Error Reporting</li><li>Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting</li></ul><h5>Module 13: Deploying an Application by Using Google Cloud Container Builder, Google Cloud Container Registry, and Google Cloud Deployment Manager</h5><ul> <li>Creating and storing container images</li><li>Repeatable deployments with deployment configuration and templates</li><li>Lab: Use Deployment Manager to deploy a web application into Google App Engine Flex test and production environments</li></ul><h5>Module 14: Execution Environments for Your Application</h5><ul> <li>Considerations for choosing an execution environment for your application or service: <ul> <li>Google Compute Engine</li><li>Container Engine</li><li>App Engine Flex</li><li>Cloud Functions</li><li>Cloud Dataflow</li></ul></li><li>Lab: Deploying your application on App Engine Flex</li></ul><h5>Module 15: Monitoring and Tuning Performance</h5><ul> <li>Best practices and watchpoints for performance</li><li>Key concepts related to Stackdriver Trace and Stackdriver Monitoring</li><li>Detecting and resolving performance issues</li><li>Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performance</li></ul>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 FlexTo get the most of out of this course, participants should have: - Completed Google Cloud Platform Fundamentals or have equivalent experience - Working knowledge of Node.js - Basic proficiency with command-line tools and Linux operating system environmentsApplication developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud Platform.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, Google 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, Google Cloud Datastore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner Module 4: Best Practices for Using Cloud Datastore - Best practices related to the following: - Queries - Built-in and composite indexes - Inserting and deleting data (batch operations) - Transactions - Error handling - Bulk-loading data into Cloud Datastore by using Google Cloud Dataflow - Lab: Store application data in Cloud Datastore Module 5: Performing Operations on Buckets and Objects - 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: Securing Your Application - 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 Google Cloud 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: Using Cloud Endpoints to Deploy APIs - Open API deployment configuration - Lab: Deploy an API for your application Module 12: Debugging Your Application by Using Google Stackdriver - Stackdriver Debugger - Stackdriver Error Reporting - Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting Module 13: Deploying an Application by Using Google Cloud Container Builder, Google Cloud Container Registry, and Google Cloud Deployment Manager - 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 Flex test and production environments Module 14: Execution Environments for Your Application - Considerations for choosing an execution environment for your application or service: - Google Compute Engine - Container Engine - App Engine Flex - Cloud Functions - Cloud Dataflow - Lab: Deploying your application on App Engine Flex Module 15: Monitoring and Tuning Performance - Best practices and watchpoints for performance - Key concepts related to Stackdriver Trace and Stackdriver Monitoring - Detecting and resolving performance issues - Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performanceModule 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, Google 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, Google Cloud Datastore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner Module 4: Best Practices for Using Cloud Datastore - Best practices related to the following: - Queries - Built-in and composite indexes - Inserting and deleting data (batch operations) - Transactions - Error handling - Bulk-loading data into Cloud Datastore by using Google Cloud Dataflow - Lab: Store application data in Cloud Datastore Module 5: Performing Operations on Buckets and Objects - 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: Securing Your Application - 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 Google Cloud 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: Using Cloud Endpoints to Deploy APIs - Open API deployment configuration - Lab: Deploy an API for your application Module 12: Debugging Your Application by Using Google Stackdriver - Stackdriver Debugger - Stackdriver Error Reporting - Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting Module 13: Deploying an Application by Using Google Cloud Container Builder, Google Cloud Container Registry, and Google Cloud Deployment Manager - 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 Flex test and production environments Module 14: Execution Environments for Your Application - Considerations for choosing an execution environment for your application or service: - Google Compute Engine - Container Engine - App Engine Flex - Cloud Functions - Cloud Dataflow - Lab: Deploying your application on App Engine Flex Module 15: Monitoring and Tuning Performance - Best practices and watchpoints for performance - Key concepts related to Stackdriver Trace and Stackdriver Monitoring - Detecting and resolving performance issues - Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performance3 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