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Overview

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.

Duration: 24h

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Objective

After completing the course, students will have the following knowledge:

  • 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.
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Audience

Application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud Platform

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prerequisite
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OUTLINE

01

Best Practices for Application Development

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Code and environment management.
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Design and development of secure, scalable, reliable, loosely coupled application components and microservices.
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Continuous integration and delivery.
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Re-architecting applications for the cloud.

02

Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK

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How to set up and use Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK.
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Lab: Set up Google Client Libraries, Cloud SDK, and Firebase SDK on a Linux instance and set up application credentials.

03

Overview of Data Storage Options

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Overview of options to store application data.
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Use cases for Google Cloud Storage, Cloud Firestore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner.

04

Best Practices for Using Cloud Firestore

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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.
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Bulk-loading data into Cloud Firestore by using Google Cloud Dataflow.
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Lab: Store application data in Cloud Datastore.

05

Performing Operations on Cloud Storage

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Operations that can be performed on buckets and objects.
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Consistency model.
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Error handling.

06

Best Practices for Using Cloud Storage

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Naming buckets for static websites and other uses.
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Naming objects (from an access distribution perspective).
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Performance considerations.
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Setting up and debugging a CORS configuration on a bucket.
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Lab: Store files in Cloud Storage.

07

Handling Authentication and Authorization

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Cloud Identity and Access Management (IAM) roles and service accounts.
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User authentication by using Firebase Authentication.
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User authentication and authorization by using Cloud Identity-Aware Proxy.
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Lab: Authenticate users by using Firebase Authentication.

08

Using Pub/Sub to Integrate Components of Your Application

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Topics, publishers, and subscribers.
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Pull and push subscriptions.
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Use cases for Cloud Pub/Sub.
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Lab: Develop a backend service to process messages in a message queue.

09

Adding Intelligence to Your Application

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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

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Key concepts such as triggers, background functions, HTTP functions.
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Use cases.
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Developing and deploying functions.
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Logging, error reporting, and monitoring.

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Managing APIs with Cloud Endpoints

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Open API deployment configuration.
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Lab: Deploy an API for your application.

12

Deploying Applications

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Creating and storing container images.
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Repeatable deployments with deployment configuration and templates.
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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

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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.
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Lab: Deploying your application on App Engine flexible environment.

14

Debugging, Monitoring, and Tuning Performance

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Application Performance Management Tools.
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Stackdriver Debugger.
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Stackdriver Error Reporting.
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Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting.
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Stackdriver Logging.
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Key concepts related to Stackdriver Trace and Stackdriver Monitoring.
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Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performance.
Study with
Google Cloud expert

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Student feedback

Cloud Ace Training
Bringing great experiences to students

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Trần Tuấn Anh

IT

After completing the Associate Cloud Engineer course, I knew how to operate and deploy projects on Google Cloud and confidently took the Google Cloud certification exam.

Nguyễn Ngọc Minh Thy

Data Engineer

After completing the Professional Data Engineer course, I have enough knowledge and confidence to take the Google Cloud certification exam to prepare for my upcoming job.

Trương Quốc Thắng

Data Engineer

I learned how to choose tools and apply them to businesses to process data effectively through the Professional Data Engineer course.

Phạm Văn Hùng

IT

Khóa học rất chi tiết và đầy đủ, sau khi học xong khóa học Associate Cloud Engineer, mình rất muốn có cơ hội học thêm các khóa học khác để hiểu rõ hơn về Google Cloud

Dương Minh Phương

Engineer

Sau khi học xong khóa học Associate Cloud Engineer, mình đã hiểu rõ về Google Cloud và có thể đưa ra các giải pháp cho doanh nghiệp triển khai các dự án trên GCP
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REGISTER NOW

TO BECOME " GOOGLE CLOUD EXPERT"

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    câu hỏi thường gặp

    Cloud Ace is a Google Cloud training unit, so it does not organize exams and provide Google Cloud certifications. Cloud Ace only supports providing certificates of course completion for students while waiting for the Google Cloud certification exam

    In addition, if you want to take the Google Cloud certification exam, Cloud Ace will guide you to register for the Online or Offline exam at the authorized Google Cloud test centers in Vietnam.

    Of course, during the learning process, you will constantly be solving quizzes, simulated mock tests that are similar to Google Cloud's actual exam questions. In addition, Cloud Ace also provides Dump questions that are constantly updated with question types, exam questions from Google Cloud to help you have the best preparation for the exam.

    Of course. You will be supported by Cloud Ace during the learning process and even at the end of the course. You can interact with the Trainer via Slack, email hoặc qua Group Google Cloud Plartform User HCM để được các Trainer hỗ trợ nhé.

    After completing the course, if you have any questions about the knowledge or have difficulties in implementing the project on Google Cloud, you can contact the Trainer for answers.

    The Google Cloud course is not only suitable for software engineers or system development engineers, but also suitable for data processing engineers such as Data Analytics, Data Engineer, Data Scientist.

    In addition, if you are a Marketer or working in the field of finance, banking, e-commerce, logistics .... constantly faced with big data to solve, then you can refer to the courses Big Data Machine Learning Fundamental or From Data to Insight on Google Cloud Platform courses to refer to simple data processing and create professional reports on Google Cloud.