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来自 Google Cloud 的课程

Google Cloud Platform Fundamentals: Core Infrastructure

11116 个评分

Google Cloud

Google Cloud Platform Fundamentals: Core Infrastructure

11116 个评分

课程 1（共 4 门，Specialization Architecting with Google Kubernetes Engine）

***NEW! Specialization Completion Challenge, receive Qwiklabs credits valued up to $180! See below for details.*** This course introduces you to important concepts and terminology for working with Google Cloud Platform (GCP). You learn about, and compare, many of the computing and storage services available in Google Cloud Platform, including Google App Engine, Google Compute Engine, Google Kubernetes Engine, Google Cloud Storage, Google Cloud SQL, and BigQuery. You learn about important resource and policy management tools, such as the Google Cloud Resource Manager hierarchy and Google Cloud Identity and Access Management. Hands-on labs give you foundational skills for working with GCP. SPECIALIZATION COMPLETION CHALLENGE As if learning new skills wasn’t enough of an incentive, we're excited to announce a special completion challenge for the 'Infrastructure' specializations. Here’s how it works: Our completion challenge runs through 11:59pm PT May 5, 2019. Complete any course in this Specialization including this one, anytime in this period and we'll send you 30 Qwiklabs credits for each course completed (upto $180 value given there are 6 courses in the Architecting with GCP specialization). You can use these credits to take additional labs and earn badges, which you can then add to your resume and social profiles. Your challenge awaits – begin learning on Coursera today! Note: •Google services are currently unavailable in China.

从本节课中

Summary and Review

This module reviews the GCP services covered in this course and reminds learners of the differences among them. The module compares GCP compute services, GCP storage services, and important Google VPC networking capabilities.

与讲师见面

Google Cloud Training

In this short module, I look back on what we covered in this course.

Remember the continuum that this course discussed at the very beginning.

The continuum between managed infrastructure and dynamic infrastructure.

GCP's compute services are arranged along this continuum,

and you can choose where you want to be on it.

Choose Compute Engine if you want to deploy your application

in virtual machines that run on Google's infrastructure.

Choose Kubernetes Engine if you want instead to deploy

your application in containers that run on Google's infrastructure.

In a Kubernetes cluster you're defining control.

Choose App Engine instead if you just want to focus on your code,

leaving most infrastructure and provisioning to Google.

App Engine flexible environment lets you use any run time you want,

and gives you full control of the environment in which your application runs.

App Engine standard environment lets you choose from a set of standard

run times and offers finer grain scaling and scaled Azira.

To completely relieve yourself from the chore of managing infrastructure,

build or extend your application using Cloud Functions.

You supply chunks of code for business logic,

and your code get spun up on demand in response to events.

GCP offers a variety of ways to load balance in bound traffic.

Use Global HTTPS load balancing to put

your Web application behind a single anycast IP to the entire Internet.

It load balances traffic among all your back-end instances in regions around the world.

And it's integrated with GCP's Content Delivery Network.

If your traffic isn't HTTP or HTTPS,

you can use the global TCP or SSL Proxy for traffic on many ports.

For other ports or for UDP traffic,

use the regional load balancer.

Finally, to load balance the internal tiers of multi-tier application,

use the internal load balancer.

GCP also offers a variety of ways for you to interconnect

your On-premises or other cloud networks with your Google VPC.

It's simple to set up a VPN and you can use cloud router to make it dynamic.

You can also peer with Google,

edits many worldwide points of presence either directly or through a carrier partner.

Or if you need a service level agreement and can adopt one of

their required network typologies, use Dedicated Interconnect.

Consider using Cloud datastore if you need to store structured objects,

or if you require support for transactions and SQL-like queries.

Consider using Cloud Bigtable if you need to store

a large amount a single key data, especially structured objects.

Consider using Cloud Storage if you need to store immutable binary objects.

Consider using Cloud SQL or Cloud Spanner if you need

full SQL support for an online transaction processing system.

Cloud SQL provides terabytes of capacity while

Cloud Spanner provides petabytes and horizontal scalability.

Consider BigQuery if you need interactive querying in

an online analytical processing system with petabytes of scale.

I'd like to zoom into one of those services we just discussed,

Cloud Storage and remind you of its four storage classes.

Multi-regional and regional are the classes for warm and hot data.

Use Multi-regional especially for content that's being served to a global Web audience.

And use Regional for working storage for compute operations.

Nearline and Coldline are the classes for,

as you'd guess cooler data.

Use Nearline for backups and for infrequently accessed content.

And use Codeline for archiving and disaster recovery.

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