Demonstration: Getting Started with Deployment Manager and Stackdriver

Loading...

From the course by Google Cloud

Google Cloud Platform Fundamentals: Core Infrastructure

10235 ratings

Explore Related Videos

At Coursera, you will find the best lectures in the world. Here are some of our personalized recommendations for you

Google Cloud

Google Cloud Platform Fundamentals: Core Infrastructure

10235 ratings

Course 1 of 3 in the Specialization Security in Google Cloud Platform

***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.

From the lesson

Developing, Deploying and Monitoring in the Cloud

Popular tools for development, deployment, and monitoring just work in GCP. Customers also have options for tools in each of these three areas that are tightly integrated with GCP. This module covers those tools.

Demonstration: Getting Started with Deployment Manager and Stackdriver9:14

Meet the Instructors

Google Cloud Training

In this demonstration, I'll use

Deployment Manager to create a GCP deployment and maintain it.

I'll also view resource usage in a virtual machine using Google Stackdriver.

I'll work with Deployment Manager using Cloud Shell.

For the sake of convenience,

I'm going to define an environment variable containing my preferred GCP zone.

I already have an environment variable containing my GCP Project ID.

Now, I will create my Deployment Manager template using a text editor.

I've created my template in another window,

and I'll paste it in here.

Now, let's take a look at what we have.

This template defines a virtual machine as a resource.

It's named My VM.

This virtual machine is defined to have a startup script apt get

update which calls for its database of the applications to be updated.

Be aware that the SIM tags of Deployment Manager requires you to specify

the preferred zone in a few places and the GCP project ID in a few places.

We'll substitute them into this file using the sed to

command or write my file out to disk.

Now, let's use sed to substitute in our project ID.

The sed command has no output when it is successful.

Similarly, we'll use the sed command to substitute in our preferred zone.

Let's look at the file again and see our results.

Our GCP zone has been substituted into the template as has our GCP project ID.

Now, we're ready to build a deployment from this template.

The template will create a new deployment and compute engine.

It will be called My First Depl,

and it will use the template mydeploy.yaml.

It's done. We can confirm his status using the gcloud command.

There's our deployment, My First Depl.

Now, let's look at the resulting virtual machine.

We'll go to the computer engine VM instances page.

There's our virtual machine My-VM.

We click on its name to open its details and scroll down,

and there's it's startup script apt get update.

Now, let's make a change to our template.

I'm going to add a command to the startup script.

This new command installs the nginx light web server.

Now, we'll update our deployment.

Now that the update is complete,

let's go back to our virtual machine instance detail

page and now look again at the startup script.

The startup script has been updated.

Now, let's put some CPU load on the VM we created and monitor it using Stackdriver.

First, we'll log into the virtual machine by connecting to it using SHH.

This Linux command creates an artificial CPU load on the virtual machine.

In essence, it forces the CPU to continuously attempt to compress random data.

Now, let's return to the GCP console and set up Stackdriver Monitoring.

In the products and services menu,

we scroll down to Stackdriver Monitoring.

We confirmed that we want to create an account

and we'll confirm that we wish to monitor our GCP project.

We don't want to monitor any AWS accounts,

so we'll click Skip AWS Set Up.

For this particular activity,

there is no need to install the Stackdriver Monitoring Agent,

so we just click Continue.

We don't need to get reports by email for this demonstration,

so we click No Reports.

Now, we click launch monitoring.

We'll click Continue with the Trial.

Notice that our CPU utilization increased sharply

a few minutes ago when we started our artificial load.

In this demonstration, I used two GCP services,

Deployment Manager, and Google Stackdriver.

Using Deployment Manager, I created a deployment and I maintained it.

Using Google Stackdriver, I viewed resource usage inside of a virtual machine.

Explore our Catalog

Join for free and get personalized recommendations, updates and offers.

Coursera provides universal access to the world’s best education, partnering with top universities and organizations to offer courses online.

© 2019 Coursera Inc. All rights reserved.

Download on the App Store

Get it on Google Play