Google Certified Professional Cloud Architect For 2022

Rating 4.4 out of 5 (215 ratings in Udemy)

What you'll learn

Students will lean about Google cloud and its services. It help in what's the purpose of each Google Service and achieving Professional Cloud certificate
Student can learn how Google cloud is different from other cloud
What all computation options are available in Google cloud like compute engine, Cloud Function, Kubernetes
How to decide which compute service should be use based on need
Students will learn about data storage …

Rating 4.4 out of 5 (215 ratings in Udemy)

What you'll learn

Students will lean about Google cloud and its services. It help in what's the purpose of each Google Service and achieving Professional Cloud certificate
Student can learn how Google cloud is different from other cloud
What all computation options are available in Google cloud like compute engine, Cloud Function, Kubernetes
How to decide which compute service should be use based on need
Students will learn about data storage options like Persistent disk, Local Disk, Cloud SQL, Cloud DataStore, BigQuery
What are various machine learning and AI offerings by Google cloud
How to use load balancer in GCP
What are the various data storing options in Cloud for different use case.
How to capture logs for the application in log
How to monitor and debug application in cloud
How to use IAC to create cloud resources
How CI/CD pipeline works in GCP
How to run big data processing pipeline in Google Cloud

Description

This course will help you in becoming a Google Cloud Certified Architect. It will help in learning what are the various cloud offerings in Google cloud platform and how to use those offerings.

This is an ideal course to learn about Google cloud for all developers and aspiring cloud architects.

It will help in boosting your career.

This course covers

1. What is Cloud

2. Why use Google Cloud

3. How to use IAM in Google cloud and ensure security in Cloud

4 What are the compute offerings in GCP and how to use those compute offerings. It also covers where to use which compute offerings

5. What are the data storage services offered in Google Cloud and what are the best practices to store and analyze data in Google Cloud.

6. How to distribute request traffic among application backends using various load balancer options in GCP and how to decide which load balancer is best suitable for a particular use case.

7. How to migrate existing Bigdata applications in GCP.

8. How to set up a new Bigdata ETL pipeline in Google Cloud by using Dataflow

9. How to capture and analyze logs in GCP

10. How to monitor applications in Google Cloud

11. How to do application tracing to find performance bottlenecks in Google Cloud

12. How to set up CI/CD pipeline in Google Cloud

13. How to use IAC in Google cloud.

14. Practice questions.

Duration 15 Hours 58 Minutes

Paid

Self paced

All Levels

English (US)

1042

Rating 4.4 out of 5 (215 ratings in Udemy)

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