This is a 20-30 minute technical talk introducing developers to cloud computing including an overview of Google Cloud computing products. There is a special focus on serverless tools as a convenient way for developers to run code. The talk ends with several inspirational apps showcasing what is possible with Google Cloud tools meant to plant a seed as to consider what is possible.

1. Introduction to Cloud Computing
with Google Cloud
Wesley Chun
Developer Advocate, Google
G Suite Dev Show
goo.gl/JpBQ40
About the speaker
Developer Advocate, Google Cloud
● Mission: enable current and future
developers everywhere to be
successful using Google Cloud and
other Google developer tools & APIs
● Videos: host of the G Suite Dev Show
on YouTube
● Blogs: developers.googleblog.com &
gsuite-developers.googleblog.com
● Twitters: @wescpy, @GoogleDevs,
@GSuiteDevs
Previous experience / background
● Software engineer & architect for 20+ years
● One of the original Yahoo!Mail engineers
● Author of bestselling "Core Python" books
(corepython.com)
● Technical trainer, teacher, instructor since
1983 (Computer Science, C, Linux, Python)
● Fellow of the Python Software Foundation
● AB (Math/CS) & CMP (Music/Piano), UC
Berkeley and MSCS, UC Santa Barbara
● Adjunct Computer Science Faculty, Foothill
College (Silicon Valley)

2. Agenda
1
Cloud computing
overview
2
Introduction to
Google Cloud
3
Run your code on
serverless
4
All of Cloud
(inspiration)
5
Wrap-up
Cloud computing overview
All you need to know about the cloud1

3. What is cloud computing?
spar
Google Compute Engine, Google Cloud Storage
AWS EC2 & S3; Rackspace; Joyent
Cloud service levels/"pillars"
SaaS
Software as a Service
PaaS
Platform as a Service
IaaS
Infrastructure as a Service
Google BigQuery, Cloud SQL,
Cloud Datastore, NL, Vision, Pub/Sub
AWS Kinesis, RDS; Windows Azure SQL, Docker
Google Apps Script
Salesforce1/force.com
G Suite (Google Apps)
Yahoo!Mail, Hotmail, Salesforce, Netsuite, Office 365
Google App Engine, Cloud Functions
Heroku, Cloud Foundry, Engine Yard, AWS Lambda

4. Summary of responsibility
SaaS
Software as a Service
Applications
Data
Runtime
Middleware
OS
Virtualization
Servers
Storage
Networking
Applications
Data
Runtime
Middleware
OS
Virtualization
Servers
Storage
Networking
IaaS
Infrastructure as a Service
Applications
Data
Runtime
Middleware
OS
Virtualization
Servers
Storage
Networking
PaaS
Platform as a Service
Managed by YOU Managed by cloud vendor
Applications
Data
Runtime
Middleware
OS
Virtualization
Servers
Storage
Networking
on-prem
all you, no cloud
2 Introduction to
Google Cloud
GCP and G Suite

5. Google Compute Engine, Google Cloud Storage
AWS EC2 & S3; Rackspace; Joyent
SaaS
Software as a Service
PaaS
Platform as a Service
IaaS
Infrastructure as a Service
Google Apps Script
Salesforce1/force.com
G Suite (Google Apps)
Yahoo!Mail, Hotmail, Salesforce, Netsuite, Office 365
Google App Engine, Cloud Functions
Heroku, Cloud Foundry, Engine Yard, AWS Lambda
Google BigQuery, Cloud SQL,
Cloud Datastore, NL, Vision, Pub/Sub
AWS Kinesis, RDS; Windows Azure SQL, Docker
Google Cloud Platform vs. G Suite
G Suite
APIs
GCP
APIs

6. Select Google Cloud product categories
Storage
Compute
Machine Learning
G Suite
Compute
Compute Engine (GCE) virtual machines
App Engine (GAE) app-hosting
Cloud Functions (GCF) function-hosting
Cloud Run (GCR) container-hosting
Kubernetes Engine (GKE) container orchestration
serverless

7. Storing Data: Cloud SQL
cloud
Storing Data: Cloud Datastore
Cloud Datastore
NoSQL
cloud

8. Storing Data: Firebase
Firebase
JSON
real-time
firebase
Storing Data: Cloud Firestore
Cloud Datastore
Firebase
(For choosing between Firebase & Cloud Firestore: see
firebase.google.com/docs/firestore/rtdb-vs-firestore;
for choosing between Cloud Datastore & Firestore: see
cloud.google.com/datastore/docs/firestore-or-datastore)
cloud

9. Machine Learning
(analyze your data)
Machine Learning: Cloud Vision & Video Intelligence
Google Cloud Vision & Video
Intelligence APIs
cloud
cloud

10. Machine Learning: Cloud Natural Language
Google Cloud Natural Language API
cloud
Machine Learning: Cloud Translation
Google Translate
cloud

11. Machine Learning: Cloud Speech
Google Cloud Speech APIs
cloud
cloud
● What is it, and how does it work?
○ Google Cloud ML APIs use pre-trained models
○ Perhaps those models less suitable for your data
○ Further customize/train our models for your data
○ Without sophisticated ML background
○ Translate, Vision, Natural Language, Video Intelligence, Tables
○ cloud.google.com/automl
● Steps
a. Prep your training data
b. Create dataset
c. Import items into dataset
d. Create/train model
e. Evaluate/validate model
f. Make predictions
Cloud AutoML

12. Storing and Analyzing Data: BigQuery
Google BigQuery
cloud
G Suite APIs
Top-level documentation and comprehensive developers
overview video at developers.google.com/gsuite

13. 3
Run your code on
Google Cloud serverless
GCP: Google App Engine , Google Cloud Functions
G Suite: Google Apps Script , Google App Maker
> Google Compute Engine
Google
Cloud Storage
cloud
cloud
Yeah, we got VMs & big disk… but why*?

14. Serverless: what & why
● What is serverless?
○ Misnomer
○ "No worries"
○ Developers focus on writing code & solving business problems*
● Why serverless?
○ Fastest growing segment of cloud... per analyst research*:
■ $1.9B (2016) and $4.25B (2018) ⇒ $7.7B (2021) and $14.93B (2023)
○ What if you go viral? Autoscaling: your new best friend
○ What if you don't? Code not running? You're not paying.
* in USD; source:Forbes (May 2018), MarketsandMarkets™ & CB Insights (Aug 2018)
Google App Engine
App-hosting in the cloud

15. Why does App Engine exist?
● Focus on app not DevOps
○ Web app
○ Mobile backend
○ Cloud service
● Enhance productivity
● Deploy globally
● Fully-managed
● Auto-scaling
● Pay-per-use
● Familiar languages
Hello World (Python "MVP")
app.yaml
runtime: python37
main.py
from flask import Flask
app = Flask(__name__)
@app.route('/')
def hello():
return 'Hello World!'
requirements.txt
Flask==1.0.2
Deploy:
$ gcloud app deploy
Access globally:
PROJECT_ID.appspot.com
Quickstart tutorial and open source repo at
cloud.google.com/appengine/docs/standard/python3/quickstart

16. Google Cloud Functions
Function-hosting in the cloud
Why does Cloud Functions exist?
● Don't have entire app?
○ No framework "overhead" (LAMP, MEAN...)
○ Deploy microservices
● Event-driven
○ Triggered via HTTP or background events
■ Pub/Sub, Cloud Storage, Firebase, etc.
○ Auto-scaling & highly-available; pay per use
● Flexible development environment
○ Cmd-line or developer console (in-browser)
● Cloud Functions for Firebase
○ Mobile app use-cases
● Available runtimes
○ JS/Node.js 6, 8, 10
○ Python 3.7
○ Go 1.11, 1.12
○ Java 8

17. main.py
def hello_world(request):
return 'Hello World!'
Deploy:
$ gcloud functions deploy hello --runtime python37 --trigger-http
Access globally (curl):
curl -X POST https://GCP_REGION-PROJECT_ID.cloudfunctions.net/hello
-H "Content-Type:application/json"
Access globally (browser):
GCP_REGION-PROJECT_ID.cloudfunctions.net/hello
Hello World (Python "MVP")
Quickstart tutorial and open source repo at
cloud.google.com/functions/docs/quickstart-python
Google Cloud Run
Container-hosting in the cloud

18. Cloud Run: code, build, deploy
.js .rb .go
.sh.py ...
● Any language, library, binary
○ HTTP port, stateless
● Bundle into container
○ Build w/Docker OR
○ Google Cloud Build
○ Image ⇒ Container Registry
● Deploy to Cloud Run (managed or GKE)
StateHTTP
CONT_NAME-RANDOM_HASH-
uREGION.a.run.app
Hello World (Python "MVP")
app.py
import os
from flask import Flask
app = Flask(__name__)
@app.route('/')
def hello_world():
target = os.environ.get('TARGET', 'World')
return 'Hello {}!'.format(target)
if __name__ == '__main__':
app.run(debug=True, host='0.0.0.0', port=int(os.environ.get('PORT', 8080)))
cloud.google.com/run/docs/quickstarts/build-and-deploy or
github.com/knative/docs/tree/master/docs/serving/samples/h
ello-world/helloworld-python

19. Hello World (Python "MVP")
Dockerfile
FROM python:3-slim
WORKDIR /app
COPY . .
RUN pip install -r requirements.txt
CMD ["python", "main.py"]
.dockerignore
Dockerfile
README.md
*.pyc
*.pyo
*.pyd
__pycache__
Build (think docker build):
$ gcloud builds submit --tag gcr.io/PROJ_ID/CONT_NAME
Deploy (think docker push):
$ gcloud run deploy --image gcr.io/PROJ_ID/CONT_NAME --platform managed
Deploy (think docker push):
$ gcloud run deploy --image
gcr.io/PROJ_ID/CONT_NAME
--platform managed
Access globally:
CONT_NAME-RANDOM_HASH-uREGION.a.run.app
Google Apps Script
Customized serverless JS runtime for automation, and extension
and integration with G Suite, Google, or other external services

20. “Hello World!” in Apps Script
Sheets-bound “Hello World!”
Apps Script intro
goo.gl/1sXeuD

21. 4 All of Cloud (inspiration)
Build with both GCP tools and G Suite
Custom intelligence in Gmail
Analyze G Suite data with GCP

22. Gmail message processing with GCP
Gmail
Cloud
Pub/Sub
Cloud
Functions
Cloud
Vision
G Suite GCP
Star
message
Message
notification
Trigger
function
Extract
images
Categorize
images

23. Inbox augmented with Cloud Function
● Gmail API: sets up notification forwarding to Cloud Pub/Sub
● developers.google.com/gmail/api/guides/push
● Pub/Sub: triggers logic hosted by Cloud Functions
● cloud.google.com/functions/docs/calling/pubsub
● Cloud Functions: "orchestrator" accessing GCP (and G Suite) APIs
● Combine all of the above to add custom intelligence to Gmail
● Deep dive code blog post
● cloud.google.com/blog/products/application-development/
adding-custom-intelligence-to-gmail-with-serverless-on-gcp
● Application source code
● github.com/GoogleCloudPlatform/cloud-functions-gmail-nodejs
App summary

24. Big data analysis to slide presentation
Access GCP tools from G Suite

25. Store big data results
Visualize big data results

26. Ingest data from Sheets
Link to chart in Sheets

27. Supercharge G Suite with GCP
G Suite GCP
BigQuery
Apps Script
Slides Sheets
Application
request
Big data
analytics

28. App summary
● Leverage GCP and build the "final mile" with G Suite
● Driven by Google Apps Script
● Google BigQuery for data analysis
● Google Sheets for visualization
● Google Slides for presentable results
● "Glued" together w/G Suite serverless
● Build this app (codelab): g.co/codelabs/bigquery-sheets-slides
● Video and blog post: bit.ly/2OcptaG
● Application source code: github.com/googlecodelabs/bigquery-sheets-slides
● Presented at Google Cloud NEXT (Jul 2018 [DEV229] & Apr 2019 [DEV212])
● cloud.withgoogle.com/next18/sf/sessions/session/156878
● cloud.withgoogle.com/next/sf/sessions?session=DEV212
Online resources & summary
What's available for students & educators?5

29. Cloud computing session summary
● Why go cloud?
○ Cloud computing has taken the world by storm
○ You're behind if you're not already using it… it's not too late!
○ Help train the next generation cloud-ready workforce!
● Google Cloud and why serverless?
○ Many features: compute, storage, AI/ML, NW, data processing, etc.
○ Serverless lets users focus on just their logic (apps or functions)
○ Interesting possibilities using both platforms (GCP + G Suite)
Other Google APIs & platforms
● Firebase (mobile development platform + RT DB; ML Kit)
○ firebase.google.com & firebase.google.com/docs/ml-kit
● Google Data Studio (data visualization, dashboards, etc.)
○ datastudio.google.com/overview
○ goo.gle/datastudio-course
● Actions on Google/Assistant/DialogFlow (voice apps)
○ developers.google.com/actions
● YouTube (Data, Analytics, and Livestreaming APIs)
○ developers.google.com/youtube
● Google Maps (Maps, Routes, and Places APIs)
○ developers.google.com/maps
● Flutter (native apps [Android, iOS, web] w/1 code base[!])
○ flutter.dev

30. ● Documentation
○ GCP: cloud.google.com/{docs,appengine,functions,run,vision,automl,translate,language,
speech,texttospeech,video-intelligence,firestore,bigquery,compute,storage,gpu,tpu}
○ G Suite: developers.google.com/{gsuite,drive,calendar,gmail,docs,sheets,slides,apps-script}
● Introductory "codelabs" ([free] self-paced, hands-on tutorials)
○ G Suite APIs: g.co/codelabs/gsuite-apis-intro (featuring Drive API)
○ Apps Script: g.co/codelabs/apps-script-intro
○ App Engine: codelabs.developers.google.com/codelabs/cloud-app-engine-python
○ Cloud Functions: codelabs.developers.google.com/codelabs/cloud-starting-cloudfunctions
○ Cloud Run: codelabs.developers.google.com/codelabs/cloud-run-hello-python3
● Other codelabs: gcplab.me (GCP) and codelabs.developers.google.com/?cat=G+Suite (G Suite)
● Videos: youtube.com/GoogleCloudPlatform (GCP) and goo.gl/JpBQ40 (G Suite)
● Code samples: github.com/GoogleCloudPlatform (GCP) and github.com/gsuitedevs (G Suite)
● Free trial (new users) and Always Free (daily/monthly tier) - cloud.google.com/free
● Know AWS/Azure? Compare w/GCP at cloud.google.com/docs/compare/{aws,azure}
Resources (industry)
Thank you! Questions?
Wesley Chun
@wescpy