For more information contact us      Phone: 03-6176066   Fax: 03-6176677   info@sela.co.il Coming courses 25/10/2021 - Morning More courses from Cloud  Developing Serverless Solutions on AWS Developing On Aws Using solr search engine on Azure Microsoft Azure Administrator Microsoft Azure Administrator Kubernetes Developing Microsoft Azure and Web Services (.NET Core) AWS Technical Essentials AWS Security Essentials Architecting with Google Cloud Platform: Design and Process Microsoft Azure and Big Data Analytics Microsoft Azure Fundamentals (1 day) Data Engineering on Google Cloud Platform Microsoft Azure Fundamentals Google Cloud Fundamentals: Core Infrastructure Elastic Search Big Data with Hadoop and Spark From Data to Insights with Google Cloud Platform Developing Microsoft Azure and Web Services Docker Workshop Architecting with Google Cloud Platform: Infrastructure Upgrade Your Skills to the Cloud Google Cloud Platform Fundamentals: Big Data & Machine Learning Azure DevOps Engineer Expert Microsoft Azure Architect Design Developing Solutions for Microsoft Azure Developing Applications with Google Cloud Platform Architecting on AWS Testing the Internet of Things (IoT) – An Exploratory Workshop Cloud Computing Designing and Implementing an Azure AI Solution Microsoft Azure Architect Technologies

CPD300 - Version: 1 Developing Applications with Google Cloud Platform 3 days course Description In this course, application developers learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. Through a combination of presentations, demos, and hands-on labs, participants learn how to use GCP services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native application Intended audience Application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud Platform Prerequisites Completed Google Cloud Platform Fundamentals or have equivalent experience Working knowledge of Node.js Basic proficiency with command-line tools and Linux operating system environments Objectives 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 source Debug, trace, and monitor applications. Perform repeatable deployments with containers and deployment services. Choose the appropriate application runtime environment; use Google Kubernetes Engine as a runtime environment and later switch to a no-ops solution with Google App Engine Flex. Topics 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 Google 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 Google 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 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 Google 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 Google Cloud Endpoints Open API deployment configuration Lab: Deploy an API for your application Module 12: 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 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 Kubernetes Engine App Engine flexible environment Cloud Functions Cloud Dataflow Lab: Deploying your application on App Engine flexible environment Module 14: Debugging, Monitoring, and Tuning Performance by Using Google Stackdriver 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

CPD300 Course
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