Cloud computing overview & Technical intro to Google Cloud

Cloud computing overview & Google Cloud technical intro 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)

Why and Agenda ● Cloud has taken industry by storm (all?) ● Not enough developer awareness of cloud computing ● Need to prep next-generation cloud-ready workforce ● Challenging to keep up with latest industry trends 1 Cloud computing overview 2 Google Cloud (GCP + G Suite) 3 Serverless platforms 4 Inspirational Ideas 5 Summary & wrap-up Cloud computing overview All you need to know about the cloud1

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, App Maker Salesforce1/force.com G Suite (Google Apps) Yahoo!Mail, Hotmail, Salesforce, Netsuite Google App Engine, Cloud Functions Heroku, Cloud Foundry, Engine Yard, AWS Lambda

Google Compute Engine, Google Cloud Storage AWS EC2 & S3; Rackspace; Joyent Outsourcing of apps (SaaS) 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, App Maker Salesforce1/force.com Google App Engine, Cloud Functions Heroku, Cloud Foundry, Engine Yard, AWS Lambda G Suite (Google Apps) Yahoo!Mail, Hotmail, Salesforce, Netsuite Google Compute Engine, Google Cloud Storage AWS EC2 & S3; Rackspace; Joyent Outsourcing of hardware (IaaS) 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, App Maker Salesforce1/force.com G Suite (Google Apps) Yahoo!Mail, Hotmail, Salesforce, Netsuite Google App Engine, Cloud Functions Heroku, Cloud Foundry, Engine Yard, AWS Lambda

Google Compute Engine, Google Cloud Storage AWS EC2 & S3; Rackspace; Joyent Outsourcing of logic-hosting (PaaS) 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, App Maker Salesforce1/force.com G Suite (Google Apps) Yahoo!Mail, Hotmail, Salesforce, Netsuite Google App Engine, Cloud Functions Heroku, Cloud Foundry, Engine Yard, AWS Lambda Google Compute Engine, Google Cloud Storage AWS EC2 & S3; Rackspace; Joyent IaaS/PaaS gray area (DataB/S/P-aaS?) SaaS Software as a Service PaaS Platform as a Service IaaS Infrastructure as a Service Google Apps Script, App Maker Salesforce1/force.com G Suite (Google Apps) Yahoo!Mail, Hotmail, Salesforce, Netsuite 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 Compute Engine, Google Cloud Storage AWS EC2 & S3; Rackspace; Joyent SaaS/PaaS gray area 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 G Suite (Google Apps) Yahoo!Mail, Hotmail, Salesforce, Netsuite Google App Engine, Cloud Functions Heroku, Cloud Foundry, Engine Yard, AWS Lambda Google Apps Script, App Maker Salesforce1/force.com 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

G Suite APIs Top-level documentation and comprehensive developers overview video at developers.google.com/gsuite

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, App Maker Salesforce1/force.com G Suite (Google Apps) Yahoo!Mail, Hotmail, Salesforce, Netsuite 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 Compute (running code)

Running Code: Compute Engine > Google Compute Engine cloud Running Code: App Engine Google App Engine we > cloud

Running Code: Cloud Functions Google Cloud Functions cloud firebase Running Code: Cloud Run Google Cloud Run cloud

Storage (where to put your data) Storing Data: Cloud Storage & Cloud Filestore cloud cloud

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

Storing Data: Firebase Firebase JSON real-time firebase Storing Data: Cloud Firestore Cloud Datastore Firebase cloud

Machine Learning (analyze your data) Machine Learning… where are you? ● Aware: read up on ML its ability to help derive insights based on a massive amount of data ● User: awareness, but putting ML to use by using existing tools or calling APIs; requires ZERO prior knowledge of ML ● Scientist: know enough about ML, have the technical skills to build, train, and deploy predictive models & make new predictions

Full Spectrum of AI & ML Offerings App Developer Data Scientist ML Scientist/Researcher Use pre-built models Use/extend OSS SDK ML EngineAuto ML Build custom models ML APIs Storing and Analyzing Data: BigQuery Google BigQuery cloud

Machine Learning: Cloud Natural Language Google Cloud Natural Language API cloud Machine Learning: Cloud Vision & Video Intelligence Google Cloud Vision & Video Intelligence APIs cloud cloud

Machine Learning: Cloud Speech Google Cloud Speech APIs cloud cloud Machine Learning: AutoML AutoML: cloud cloud

Machine Learning: Cloud ML Engine Google Cloud Machine Learning Engine cloud Data transformation/ETL ● Open sourced as Apache Beam (supports Apache Spark and Flink)

G Suite (collaborate & communicate) G Suite: Gmail Gmail API read & send messages labels search manage settings developers

G Suite: Google Calendar Calendar API access modify create events developers G Suite: Google Docs & Slides Docs & Slides APIs developers developers

G Suite: Google Sheets Sheets API developers G Suite: Google Drive Drive API read write permissions/sharing import/export developers

REST API examples Short Python code snippets using GCP & G Suite APIs API key (public data) vs. OAuth2 access (private data)

BUT ... wait, there’s more...

The first word on Security Authentication ("authn") vs authorization ("authz") ● authn: you are who you say you are ○ login & passwd ○ handprint authentication ○ retina scan ● authz: okay, you are who you say you are, but can you haz data? ○ OAuth2 - mostly authz, but some authn ○ Mostly about 3rd-party access to data ○ Users must give YOUR code access to THEIR data ○ Most of the time when you see "auth", it refers to authz ● Some refer to this as "consent" vs. "credentials…" which is which? Cloud/GCP console console.cloud.google.com ● Hub of all developer activity ● Applications == projects ○ New project for new apps ○ Projects have a billing acct ● Manage billing accounts ○ Financial instrument required ○ Personal or corporate credit cards, Free Trial, and education grants ● Access GCP product settings ● Manage users & security ● Manage APIs in devconsole

● View application statistics ● En-/disable Google APIs ● Obtain application credentials Using Google APIs goo.gl/RbyTFD API manager aka Developers Console (devconsole) console.developers.google.com OAuth2 or API key HTTP-based REST APIs 1 HTTP 2 Google APIs request-response workflow ● Application makes request ● Request received by service ● Process data, return response ● Results sent to application (typical client-server model)

Google APIs client libraries for many languages; demos in developers.google.com/ api-client-library SIMPLE AUTHORIZED Which do you choose?

List (first 100) files/folders in Google Drive from __future__ import print_function from googleapiclient import discovery from httplib2 import Http from oauth2client import file, client, tools SCOPES = 'https://www.googleapis.com/auth/drive.metadata.readonly' store = file.Storage('storage.json') creds = store.get() if not creds or creds.invalid: flow = client.flow_from_clientsecrets('client_secret.json', SCOPES) creds = tools.run_flow(flow, store) DRIVE = discovery.build('drive', 'v3', http=creds.authorize(Http())) files = DRIVE.files().list().execute().get('files', []) for f in files: print(f['name'], f['mimeType']) Listing your ﬁles goo.gl/ZIgf8k Try our Node.js customized reporting tool codelab: g.co/codelabs/sheets Why use the Sheets API? data visualization customized reports Sheets as a data source

Migrate SQL data to a Sheet # read SQL data then create new spreadsheet & add rows into it FIELDS = ('ID', 'Customer Name', 'Product Code', 'Units Ordered', 'Unit Price', 'Status') cxn = sqlite3.connect('db.sqlite') cur = cxn.cursor() rows = cur.execute('SELECT * FROM orders').fetchall() cxn.close() rows.insert(0, FIELDS) DATA = {'properties': {'title': 'Customer orders'}} SHEET_ID = SHEETS.spreadsheets().create(body=DATA, fields='spreadsheetId').execute().get('spreadsheetId') SHEETS.spreadsheets().values().update(spreadsheetId=SHEET_ID, range='A1', body={'values': rows}, valueInputOption='RAW').execute() Migrate SQL data to Sheets goo.gl/N1RPwC Try our Node.js BigQuery GitHub license analyzer codelab: g.co/codelabs/slides Why use the Slides API? data visualization presentable reports

Try our Node.js Markdown-to-Google-Slides generator: github.com/gsuitedevs/md2googleslides Why use the Slides API? customized presentations Replace text & images from template deck requests = [ # (global) search-and-replace text {'replaceAllText': { 'findText': '{{TITLE}}', 'replaceText': 'Hello World!', }}, # replace text-based image placeholders (global) {'replaceAllShapesWithImage': { 'imageUrl': IMG_URL, # link to product logo 'replaceMethod': 'CENTER_INSIDE', 'containsText': {'text': '{{LOGO}}'}, }}, ] SLIDES.presentations().batchUpdate(body={'requests': requests}, presentationId=DECK_ID, fields='').execute() Replacing text and images goo.gl/o6EFwk

+ Mail merge = Mail merge (template search & replace) requests = [ # (global) search-and-replace text {'replaceAllText': { 'containsText': {'text': '{{TITLE}}'}, 'replaceText': 'Hello World!', }}, ] DOCS.documents().batchUpdate(body={'requests': requests}, documentId=DOC_ID, fields='').execute() Mail merge goo.gle/2KrPNeG

BigQuery: querying Shakespeare words TITLE = "The top 10 most common words in all of Shakespeare's works" QUERY = ''' SELECT LOWER(word) AS word, sum(word_count) AS count FROM [bigquery-public-data:samples.shakespeare] GROUP BY word ORDER BY count DESC LIMIT 10 ''' rsp = BQ.query(body={'query': QUERY}, projectId=PROJ_ID).execute() print('n*** Results for %r:n' % TITLE) for col in rsp['schema']['fields']: # HEADERS print(col['name'].upper(), end='t') print() for row in rsp['rows']: # DATA for col in row['f']: print(col['v'], end='t') print() Top 10 most common Shakespeare words $ python bq_shake.py *** Results for "The most common words in all of Shakespeare's works": WORD COUNT the 29801 and 27529 i 21029 to 20957 of 18514 a 15370 you 14010 my 12936 in 11722 that 11519

Simple sentiment & classification analysis TEXT = '''Google, headquartered in Mountain View, unveiled the new Android phone at the Consumer Electronics Show. Sundar Pichai said in his keynote that users love their new Android phones.''' print('TEXT:', TEXT) data = {'type': 'PLAIN_TEXT', 'content': TEXT} NL = discovery.build('language', 'v1', developerKey=API_KEY) # sentiment analysis sent = NL.documents().analyzeSentiment( body={'document': data}).execute().get('documentSentiment') print('nSENTIMENT: score (%s), magnitude (%s)' % (sent['score'], sent['magnitude'])) # content classification print('nCATEGORIES:') cats = NL.documents().classifyText(body={'document': data}).execute().get('categories') for cat in cats: print('* %s (%s)' % (cat['name'][1:], cat['confidence'])) Simple sentiment & classification analysis $ python nl_sent_simple.py TEXT: Google, headquartered in Mountain View, unveiled the new Android phone at the Consumer Electronics Show. Sundar Pichai said in his keynote that users love their new Android phones. SENTIMENT: score (0.3), magnitude (0.6) CATEGORIES: * Internet & Telecom (0.76) * Computers & Electronics (0.64) * News (0.56)

Text-to-Speech: synthsizing audio text # request body (with text body using 16-bit linear PCM audio encoding) body = { 'input': {'text': text}, 'voice': { 'languageCode': 'en-US', 'ssmlGender': 'FEMALE', }, 'audioConfig': {'audioEncoding': 'LINEAR16'}, } # call Text-to-Speech API to synthesize text (write to text.wav file) T2S = discovery.build('texttospeech', 'v1', developerKey=API_KEY) audio = T2S.text().synthesize(body=body).execute().get('audioContent') with open('text.wav', 'wb') as f: f.write(base64.b64decode(audio)) Speech-to-Text: transcribing audio text # request body (16-bit linear PCM audio content, i.e., from text.wav) body = { 'audio': {'content': audio}, 'config': { 'languageCode': 'en-US', 'encoding': 'LINEAR16', }, } # call Speech-to-Text API to recognize text S2T = discovery.build('speech', 'v1', developerKey=API_KEY) rsp = S2T.speech().recognize( body=body).execute().get('results')[0]['alternatives'][0] print('** %.2f%% confident of this transcript:n%r' % ( rsp['confidence']*100., rsp['transcript']))

Speech-to-Text: transcribing audio text $ python s2t_demo.py ** 92.03% confident of this transcript: 'Google headquarters in Mountain View unveiled the new Android phone at the Consumer Electronics Show Sundar pichai said in his keynote that users love their new Android phones' Video intelligence: make videos searchable # request body (single payload, base64 binary video) body = { "inputContent": video, "features": ['LABEL_DETECTION', 'SPEECH_TRANSCRIPTION'], "videoContext": {"speechTranscriptionConfig": {"languageCode": 'en-US'}}, } # perform video shot analysis followed by speech analysis VINTEL = discovery.build('videointelligence', 'v1', developerKey=API_KEY) resource = VINTEL.videos().annotate(body=body).execute().get('name') while True: results = VINTEL.operations().get(name=resource).execute() if results.get('done'): break time.sleep(random.randrange(8)) # expo-backoff probably better

Video intelligence: make videos searchable # display shot labels followed by speech transcription for labels in results['response']['annotationResults']: if 'shotLabelAnnotations' in labels: print('n** Video shot analysis labeling') for shot in labels['shotLabelAnnotations']: seg = shot['segments'][0] print(' - %s (%.2f%%)' % ( shot['entity']['description'], seg['confidence']*100.)) if 'speechTranscriptions' in labels: print('** Speech transcription') speech = labels['speechTranscriptions'][0]['alternatives'][0] print(' - %r (%.2f%%)' % ( speech['transcript'], speech['confidence']*100.)) Video intelligence: make videos searchable $ python3 vid_demo.py you-need-a-hug.mp4 ** Video shot analysis labeling - vacation (30.62%) - fun (61.53%) - interaction (38.93%) - summer (57.10%) ** Speech transcription - 'you need a hug come here' (79.27%)

Higher-level GCP SDK & API client libraries 1. Bad news: Just showed you the "harder way" of using Google Cloud Platform APIs 2. Good news: it's even easier with the GCP SDK and higher-level client libraries 3. Why (not)? Not all Google APIs have high- level client libraries. Lower-level serves as "LCD" for accessing more Google APIs cloud.google.com/sdk cloud.google.com/apis/docs 3 Run your code on Google Cloud serverless GCP: Google App Engine , Google Cloud Functions G Suite: Google Apps Script , Google App Maker

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 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 G Suite (Google Apps) Yahoo!Mail, Hotmail, Salesforce, Netsuite 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, App Maker Salesforce1/force.com

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

Hello World (3 files: 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: https://PROJECT_ID.appspot.com Open source repo at github.com/GoogleCloudPlatform/python-docs-samples/ tree/master/appengine/standard_python37/hello_world 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 ○ Auto-scaling & highly-available ○ Pay per use ● Familiar development environment ○ Cmd-line or developer console ● 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 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")

Google Apps Script Customized JS runtime for automation, extension, and integration with G Suite and other Google or external services What can you do with this?

Accessing maps from spreadsheets?!? goo.gl/oAzBN9 This… with help from Google Maps & Gmail function sendMap() { var sheet = SpreadsheetApp.getActiveSheet(); var address = sheet.getRange("A2").getValue(); var map = Maps.newStaticMap().addMarker(address); GmailApp.sendEmail('friend@example.com', 'Map', 'See below.', {attachments:[map]}); } JS Google Cloud Run Container-hosting in the cloud

The rise of containers ● Any language ● Any library ● Any binary ● Ecosystem of base images ● Industry standard “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 not accessible to everyone...

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 (native or GKE) StateHTTP https://yourservice.run.app Cloud Run Fully serverless No cluster to manage Pay for what you use Cloud Run on GKE Serverless experience Access custom nodes, GPUs, VPC Simplicity of Cloud Run With flexibility of GKE Fully-managed Kubernetes cluster Serverless containers, where you want them Deploy to your self-managed Kubernetes cluster Cloud Run compatible With Knative open API Runs on-prem or in other cloud on Self-managed Kubernetes cluster

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

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

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 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

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

Store big data results Visualize big data results

Ingest data from Sheets Link to chart in Sheets

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

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

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) References ● G Suite & GCP home pages & documentation ○ developers.google.com/gsuite ○ developers.google.com/apps-script ○ github.com/gsuitedevs ● Google Cloud Platform (GCP) documentation & open source repos ○ cloud.google.com/gcp ○ cloud.google.com/docs ○ github.com/GoogleCloudPlatform/{python,nodejs}-docs-samples ○ Know AWS? Compare w/GCP at: cloud.google.com/docs/compare/aws ● Google APIs Client Libraries (G Suite & GCP) & Google Cloud SDK (GCP-only) ○ developers.google.com/api-client-library ○ cloud.google.com/sdk

More references ● Relevant videos ○ goo.gl/RbyTFD (new Google APIs project setup) ○ goo.gl/KMfbeK (common Python OAuth2 boilerplate code review) ○ goo.gl/ZIgf8k (APIs intro codelab [Drive API]) ● Relevant codelabs ○ g.co/codelabs/gsuite-apis-intro (Drive API) ○ g.co/codelabs/apps-script-intro ○ codelabs.developers.google.com/codelabs/cloud-app-engine-python ○ codelabs.developers.google.com/codelabs/cloud-starting-cloudfunctions ● Inspirational apps ○ bit.ly/2OcptaG ○ cloud.google.com/blog/products/application-development/ adding-custom-intelligence-to-gmail-with-serverless-on-gcp ○ cloud.withgoogle.com/next/sf/sessions?session=DEV212 Learning resources ● Codelabs: self-paced, hands-on tutorials ○ Google codelabs: need a Gmail account, always free ■ g.co/codelabs/cloud ○ Qwiklabs codelabs: don't need a Gmail acct; typically not free ■ google.qwiklabs.com ■ Puchase credits a la carte, or discounted in-bulk / via subscription ● Official GCP documentation ○ cloud.google.com/gcp/getting-started ○ Recommended: Getting Started, Cloud Console, Cloud Shell, Cloud SDK, Community ● YouTube video series: ○ youtube.com/GoogleCloud ○ Recommended: Cloud Minute shorts & Cloud NEXT videos ○ G Suite Dev Show: goo.gl/JpBQ40

Security in Google Cloud ● Google Cloud Security home page: cloud.google.com/security ● Google Cloud Security whitepaper: bit.ly/2Qb3wXX ● Compliance: stds, regulations, certifications: cloud.google.com/security/compliance ● Transparency report (incl. service disruptions): transparencyreport.google.com ● G Suite Security and Trust (PDF "eBook;" links disabled): bit.ly/2WQ1fnI ● G Suite Encryption whitepaper (PDF): bit.ly/2JrmdGy ● GCP Encryption-at-rest whitepaper (PDF): cloud.google.com/security/encryption-at-rest/default-encryption ● Google Cloud Encryption-in-transit whitepaper (PDF): cloud.google.com/security/encryption-in-transit ● Google data centers: google.com/about/datacenters Thank you! Questions? Wesley Chun @wescpy Progress bars: goo.gl/69EJVw

Cloud computing overview & Technical intro to Google Cloud

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Cloud computing overview & Technical intro to Google Cloud