Designing flexible apps deployable to App
Engine, Cloud Functions, or Cloud Run
Wesley Chun - @wescpy
Developer Advocate, Google
Adjunct CS Faculty, Foothill College
Developer Advocate, Google Cloud
● Mission: enable current and future
developers everywhere to be
successful using Google Cloud and
other Google developer tools & APIs
● Focus: GCP serverless (App Engine,
Cloud Functions, Cloud Run); higher
education, Google Workspace, GCP
AI/ML APIs; multi-product use cases
● Content: speak to developers globally;
make videos, create code samples,
produce codelabs (free, self-paced,
hands-on tutorials), publish blog posts
About the speaker
Previous experience / background
● Software engineer & architect for 20+ years
○ Yahoo!, Sun, HP, Cisco, EMC, Xilinx
○ Original Yahoo!Mail engineer/SWE
● Technical trainer, teacher, instructor
○ Taught Math, Linux, Python since 1983
○ Private corporate trainer
○ Adjunct CS Faculty at local SV college
● Python community member
○ Popular Core Python series author
○ Python Software Foundation Fellow
● AB (Math/CS) & CMP (Music/Piano), UC
Berkeley and MSCS, UC Santa Barbara
● Adjunct Computer Science Faculty, Foothill
College (Silicon Valley)

Why & agenda
1
Introduction
2
Google Cloud
Serverless review
3
Nebulous, flexible
app(s)
4
Deployments
5
Summary
● Cloud computing has taken industry by storm (all?)
● App modernization top priority/key goal at many enterprises
○ Containerize apps, get them on VMs, move to cloud
● Serverless: let users focus on solutions not what they run on
● GCP: 3 (4) different serverless products for different use cases
● Similar yet different from each other, but flexible apps deployable to all
● Help prep next-generation (cloud-ready) workforce
01
Introduction
Why are you here?

Serverless: what & why
● What is serverless?
○ Misnomer (a "PMM") :-)
○ "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)
Serverless with Google
Operational
Model
Programming
Model
Low infra management Managed security Pay only for usage
Service-based
monoliths
Request +
event-driven
Open

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 Workspace (was 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
Serverless: PaaS-y compute/processing
Google Apps Script
Salesforce1/force.com
cloud.google.com/hosting-options#hosting-options
Google Cloud compute option spectrum
Compute
Engine
Kubernetes
Engine (GKE)
Cloud Run
on Anthos
Cloud Run
(fully-mgd)
App Engine
(Flexible)
App Engine
(Standard)
Cloud
Functions

Serverless common use cases App Engine Cloud Run
Cloud
Functions
Web services
Web app hosting/custom domains ✓ ✓
HTTP services ✓ ✓ ✓
Container hosting ✓
APIs
Web & mobile backends ✓ ✓
Internal APIs and services ✓ ✓
Data processing ✓ ✓
Automation
Workflow & orchestration ✓ ✓
Event-driven automation ✓ ✓
Common use cases
02
Google Cloud
serverless
...compute platforms review

Google App Engine
App-hosting in the cloud
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
● Test w/local dev server

App Engine to the rescue!!
● Focus on app not DevOps
● Enhance productivity
● Deploy globally
● Fully-managed
● Auto-scaling
● Pay-per-use
● Familiar standard runtimes
● 2nd gen std platforms
○ Python 3.7
○ Java 8, 11
○ PHP 7.2
○ Go 1.11
○ JS/Node.js 8, 10
○ Ruby 2.5
Hello World (Python "MVP")
app.yaml
runtime: python38
main.py
from flask import Flask
app = Flask(__name__)
@app.route('/')
def hello():
return 'Hello World!'
requirements.txt
Flask==1.1.2
Deploy:
$ gcloud app deploy
Access globally:
PROJECT_ID.appspot.com
cloud.google.com/appengine/docs/standard/python3/quickstart

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)
○ Develop/test locally with Functions Framework
● Cloud Functions for Firebase
○ Mobile app use-cases
● Available runtimes
○ JS/Node.js 8, 10, 12, 14
○ Python 3.7, 3.8, 3.9
○ Go 1.11, 1.13
○ Java 11
○ Ruby 2.6, 2.7
○ .NET Core 3.1

main.py
def hello_world(request):
return 'Hello World!'
Deploy:
$ gcloud functions deploy hello --runtime python38 --trigger-http
Access globally (curl):
$ curl REGION-PROJECT_ID.cloudfunctions.net/hello
Access globally (browser):
https://REGION-PROJECT_ID.cloudfunctions.net/hello
Hello World (Python "MVP")
cloud.google.com/functions/docs/quickstart-python

Google Cloud Run
Container-hosting in the cloud
The rise of containers... ● Any language
● Any library
● Any binary
● Ecosystem of base images
● Industry standard
FLEXIBILITY

“We can’t be locked in.”
“How can we use
existing binaries?”
“Why do I have to choose between
containers and serverless?”
“Can you support language _______ ?”
Serverless inaccessible for some...
CONVENIENCE
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)
● GitOps: (CI/)CD Push-to-deploy from Git
State
HTTP

Hello World (Python "MVP")
main.py
import os
from flask import Flask
app = Flask(__name__)
@app.route('/')
def hello_world():
return 'Hello World!'
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
requirements.txt
Flask==1.1.2
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
.git/
__pycache__
Build (think docker build and docker push) then deploy (think docker run):
$ gcloud builds submit --tag gcr.io/PROJ_ID/IMG_NAME
$ gcloud run deploy SVC_NAME --image gcr.io/PROJ_ID/IMG_NAME
OR… Build and Deploy (1-line combo of above commands):
$ gcloud run deploy SVC_NAME --source .
Access globally:
SVC_NAME-HASH-REG_ABBR.a.run.app
Docker &
Dockerfile
OPTIONAL!!

● Build containers easily & securely without creating/managing Dockerfiles
● Open source, open standard; based on CNCF Buildpacks spec v3
● Used by GCF Functions Framework to deploy locally-developed functions
● Supports most common development tools
○ Go 1.10+
○ Node.js 10+
○ Python 3.7+
○ Java 8 & 11
○ .NET Core 3.1+
● Blog posts
○ cloud.google.com/blog/products/containers-kubernetes/google-cloud-now-supports-buildpacks and
cloud.google.com/blog/products/serverless/build-and-deploy-an-app-to-cloud-run-with-a-single-command
Deploy to Cloud Run with Buildpacks
github.com/GoogleCloudPlatform/buildpacks
$ ls
index.js package.json
$ gcloud run deploy myapp --source .
$ ls
app.py requirements.txt
$ gcloud run deploy myapp --source .
03
Nebulous, flexible app(s)
Deployable to all platforms

Flexibility in options
Cloud
Functions
App
Engine
Cloud
Run
local
server
Cloud
Translation
My "Google Translate" MVP
github.com/googlecodelabs/cloud
-nebulous-serverless-python
● "Nebulous" sample web app
○ Flask/Python app
○ Python 2 & 3 compatible
○ Uses Cloud Translation API
● Deployable to on-prem server
● Also GCP serverless compute
○ App Engine
○ Cloud Functions
○ Cloud Run
● With only config changes
● No changes to app code
Nebulous files
● Application files
● Configuration files
● Administrative files
○ Information files
○ Testing - CI/CD files
● Files differ per deployment
● Mainly in configuration
● Application files identical
● Administrative files not part of
deployments*

Different nebulous deployments
1. Local (or hosted) Flask server (Python 2)
2. Local (or hosted) Flask server (Python 3)
3. Google App Engine (Python 2)
4. Google App Engine (Python 3)
5. Google Cloud Functions (Python 3)
6. Google Cloud Run (Python 2 via Docker)
7. Google Cloud Run (Python 3 via Docker)
8. Google Cloud Run (Python 3 via Cloud Buildpacks)
04
Deployments
& required configuration tweaks

Local (Flask)
● Python 2 or 3
● Application files
○ main.py and templates/index.html
● Config files
○ requirements.txt (install locally; see below)
○ Service acct pub/prv key-pair & download (credentials.json)
○ Point $GOOGLE_APPLICATION_CREDENTIALS env var to ^^^^
● Run pip install -U pip -r requirements.txt
● Run python main.py
Google App Engine
● Python 2
● Application files
○ main.py and templates/index.html
● Config files
○ requirements.txt (install locally; see below)
○ app.yaml
○ appengine_config.py
● Run pip install -t lib -r requirements.txt
● Run gcloud app deploy

Google App Engine
● Python 3
● Application files
○ main.py and templates/index.html
● Config files
○ requirements.txt
○ app.yaml (uncomment runtime: python38)
● Run gcloud app deploy
Google Cloud Functions
● Python 3
● Application files
○ main.py and templates/index.html
● Config files
○ requirements.txt
● Run gcloud functions deploy translate --runtime python37
--trigger-http --allow-unauthenticated

Google Cloud Run (Docker)
● Python 2
● Application files
○ main.py and templates/index.html
● Config files
○ requirements.txt (uncomment gunicorn)
○ Dockerfile (replace ENTRYPOINT with gunicorn)
● Run gcloud beta run deploy translate
--allow-unauthenticated --platform managed --source .
Google Cloud Run (Docker)
● Python 3
● Application files
○ main.py and templates/index.html
● Config files
○ requirements.txt (uncomment gunicorn)
○ Dockerfile (use Py3 base image & gunicorn ENTRYPOINT)
● Run gcloud beta run deploy translate
--allow-unauthenticated --platform managed --source .

Google Cloud Run (Cloud Buildpacks)
● Python 3
● Application files
○ main.py and templates/index.html
● Config files
○ requirements.txt (uncomment gunicorn)
○ Procfile (replace web: with gunicorn)
● Run gcloud beta run deploy translate
--allow-unauthenticated --platform managed --source .
05
Summary
Resources & conclusion

Possible courses for this sample app
● Software Engineering
● Intro to Cloud Computing
● Machine Learning/AI
● Web application development
● Mobile app (backends)
○ Suggest Cloud Functions for Firebase (vs. GCF)
● Data science/big data
● Business applications
Cost of Google Cloud serverless tools
● What is free in Google Cloud overall?
○ Free Trial (credit card required; expires)
■ $300USD credit good for first 90 days
○ Always Free tier (credit card required; no expiration; subject to change)
■ Independent of Free Trial & education grants (more below)
■ Some GCP products free up to usage limits
○ Learn about both programs at cloud.google.com/free
● Serverless Always Free tier (monthly)
○ App Engine (28 [or 9] hours, 1GB storage & 1GB egress) per day
○ Cloud Run (2M reqs, 350k GB-secs, 180k vCPU-secs, 1GB egress) per month
○ Cloud Functions (2M calls, 400k GB-secs, 200k vCPU-secs, 5GB egress) per month
● Higher education (teaching & research) grants
○ cloud.google.com/edu (credit card NOT required; expires)
○ Provides "free" usage for coursework and initial research
$$ FREE $$

Session summary
● What's the right tool for the job?
○ GAE, GCF, GCR: they've got different use cases
○ Goal: gain familiarity with all three (learn their differences)
○ They're not as different as you may think!
● One nebulous, flexible sample web app
○ Mini "My Google Translate MVP" featuring Cloud Translation API
○ Deployable to all serverless compute platforms
○ Only requires configuration changes
○ KISS: use default service account credentials
○ github.com/googlecodelabs/cloud-nebulous-serverless-python
Other Google APIs & platforms
● Google Workspace (G Suite) (code Gmail, Drive, Docs, Sheets, Slides!)
○ developers.google.com/gsuite
● Firebase (mobile development platform and RT DB plus ML-Kit)
○ firebase.google.com and 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

Invite me (or my team) to
your campus... it's our job!
● Faculty & grad students
● Researchers
● Undergrads
● University IT staff/CIO/CTO
● University entrepreneurship
centers/capstone project leads
Thank you! Questions?
Wesley Chun
@wescpy
Progress bars: goo.gl/69EJVw