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来自 Google Cloud 的课程

Google Cloud Platform Fundamentals: Core Infrastructure

13018 个评分

Google Cloud

Google Cloud Platform Fundamentals: Core Infrastructure

13018 个评分

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

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. 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'll 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 runtime 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

runtimes and offers finer-grained scaling and scaled to zero.

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 inbound traffic.

Use Global HTTP(S) load balancing to put

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

It load balances traffic among all your backend 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 a 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,

at its 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

the 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 of single-keyed 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 Coldline for archiving and disaster recovery.

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