Pic-a-Daily Serverless Workshop on Google Cloud Platform

In this workshop, you will discover the various serverless options offered by Google Cloud Platform, such as Cloud Functions (functions as a service), App Engine (application as a service), and Cloud Run (container as a service). You will create an application that lets users upload, analyse, and share pictures. Data will be stored in Cloud Storage (images), Cloud Firestore (structured data). Along the way, additional services will be used such as Vision API (to analyze pictures), Cloud Logging (to track interesting events), Cloud Scheduler (to invoke workloads on a schedule), Cloud Pub/Sub, Eventarc (to receive events) and Workflows (to orchestrate services).

Transcript

1. Proprietary + Confidential
   Pic-a-Daily Serverless Workshop
   g.co/codelabs/serverless-workshop
   #gcpserverlessworkshop
   Guillaume Laforge — @glaforge
   Mete Atamel — @meteatamel
   

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2. 01
   The Pic-a-Daily
   Serverless Workshop:
   What you’re going to build!
   

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3. Proprietary + Confidential
   A photo-sharing application
   

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4. A photo-sharing application
   

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5. Final architecture diagram
   

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6. Codelabs g.co/codelabs/serverless-workshop
   

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7. 02
   The Serverless
   spectrum
   on Google Cloud
   Platform
   

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8. Proprietary + Confidential
   Operational
   Model
   Programming
   Model
   No Infra Management Managed Security Pay only for usage
   Service-based Event-driven Stateless
   Serverless
   

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9. Proprietary + Confidential
   Virtual Machine
   OS
   Application
   Runtime
   Application
   Virtual Hardware
   Dedicated Server
   OS
   Application
   Runtime
   Application
   Virtual Hardware
   Containers
   OS
   Application
   Runtime
   Application
   Virtual Hardware
   Functions Functions Functions
   Application Platform
   OS
   Application
   Runtime
   Application
   Virtual Hardware
   Functions
   Serverless
   OS
   Application
   Runtime
   Application
   Virtual Hardware
   Functions
   Infrastructure Container Platform Function
   Compute Engine Kubernetes Engine App Engine Cloud Functions
   On-Premises
   Serverless Zone
   Physical Hardware
   Cloud Run
   

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10. Proprietary + Confidential
    Serverless
    functions
    Serverless
    web applications
    Serverless
    HTTP workloads
    Source code-based event
    driven functions
    Source code-based web
    apps and API backends
    HTTP containers
    fully managed
    HTTP containers
    on GKE cluster
    Cloud
    Functions
    App Engine
    Cloud Run
    Serverless compute options
    

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11. 03
    Cloud
    Functions
    

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12. Back end code functions that automatically
    run in response to a trigger event
    Microservices
    Cloud "glue"
    Node.js, Python, Go, Java
    Cloud Functions
    

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13. Cloud Functions as cloud glue
    Access 20+
    Google services
    from GCF
    Cloud Storage
    Cloud Pub/Sub
    HTTPS
    Firebase
    Cloud Scheduler
    Cloud Tasks
    

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14. Good fit
    “Serverless”
    Using Pub/Sub and/or Cloud Storage
    Don't want to think about runtime env
    Data transformations (ETL)
    Cloud-based HTTP glue and webhooks
    Constraints
    Runtimes: Node.js, Python, Go, Java
    Function level granularity
    Must interact via events
    No custom domain name
    Concurrency level of 1 (more cold starts)
    Good fit? Constraints?
    

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15. Codelabs
    Lab 1 — Store and analyse pictures
    Storing pictures in Cloud Storage,
    trigger a Cloud Functions instance
    Calling the Cloud Vision API for analysis
    Storing metadata in Cloud Firestore
    Lab 3 — Create a collage of pictures
    At a regular interval, with Cloud Scheduler
    Invoking a Cloud Run instance,
    to create a collage of recent pictures
    found in Cloud Firestore
    Storing collage in Cloud Storage
    Lab 2 — Create thumbnails
    Cloud Storage notifications sent to Pub/Sub
    Triggering a Cloud Run instance via Pub/Sub
    Creating a thumbnail with ImageMagick, and
    storing back into Cloud Storage
    Lab 4 — Create a web frontend
    Creating a web application with App Engine
    Listing pictures from Cloud Firestore
    Displaying pictures & collage
    from Cloud Storage
    g.co/codelabs/serverless-workshop
    

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16. 04
    Cloud Run
    

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17. Containers
    Any language
    Any library
    Any binary
    Ecosystem of
    base images
    .js .rb .go
    .py .sh …
    0 1 0
    1 0 0
    1 1 1
    

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18. Containers
    Flexibility
    Serverless
    Velocity
    

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19. Cloud Run
    Fully managed, deploy your
    workloads and don’t see the
    cluster.
    Cloud Run on Anthos
    Deploy into Anthos, run
    serverless side-by-side with
    your existing workloads.
    Knative Everywhere
    Use the same APIs and
    tooling anywhere you run
    Kubernetes with Knative.
    Serverless containers with Knative & Cloud Run
    

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20. Container to
    production
    in seconds
    Natively
    Serverless
    One experience,
    where you want it
    Cloud Run
    Bringing serverless to containers
    

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21. HTTPS Endpoint
    Public
    • Website
    • API endpoint
    Private
    • Internal services
    • Async tasks
    • Mobile backend
    • Webhook
    

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22. Container contract
    Listen on 0.0.0.0 on port $PORT (default 8080)
    HTTP server must start < 4 min (timeout → 504)
    Request time < 15 min (default → 5 min)
    Stateless (in-memory file system, doesn’t persist)
    Computation only within request (No background activity)
    

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23. Container resources
    1 vCPU per container instance (configurable to 2vCPU)
    256 MiB of memory up to a max of 4 GiB (configurable)
    80 concurrent requests per container (configurable 1-80)
    1000 max containers by default (configurable 1-1000)
    Access to a Metadata Server
    Sandboxed by gVisor
    

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24. Pay per use
    CPU / Memory / Requests 100ms
    

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25. Billable time
    Instance
    Billable Time
    Request 1 Start Request 1 End
    Request 2 Start Request 2 End
    Instance Time
    Billable
    Non-billable
    

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26. Concurrency: up to 80 concurrent requests
    concurrency = 1
    concurrency = 80
    

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27. Pub/Sub triggered internal services
    Cloud Run
    Cloud
    Pub/Sub
    Queue
    Queue
    Queue
    

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28. Storage triggered internal services
    Cloud Run
    Cloud
    Pub/Sub
    Queue
    Queue
    Queue
    Cloud
    Storage
    

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29. Scheduled services
    Command Line
    Interface (CLI)
    User Interface
    (UI)
    Scheduler
    API
    Cloud Run
    Cloud
    Scheduler
    

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30. Services part of async tasks
    Cloud
    Tasks
    user_registration
    user_levelcompleted
    user_inapppurchase
    user_statechange
    Daily activity
    metrics service
    User profile service
    Payment processing
    service
    Game state service
    

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31. Proprietary + Confidential
    Good fit? Constraints?
    Good fit
    Stateless
    HTTP request-response workloads
    Scale: way up, down to zero, bursty
    Specific runtime requirements:
    language, dependencies, etc
    Constraints
    Must use containers
    Decide on build process (Cloud Build, etc)
    

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32. Codelabs
    Lab 1 — Store and analyse pictures
    Storing pictures in Cloud Storage,
    trigger a Cloud Functions instance
    Calling the Cloud Vision API for analysis
    Storing metadata in Cloud Firestore
    Lab 3 — Create a collage of pictures
    At a regular interval, with Cloud Scheduler
    Invoking a Cloud Run instance,
    to create a collage of recent pictures
    found in Cloud Firestore
    Storing collage in Cloud Storage
    Lab 2 — Create thumbnails
    Cloud Storage notifications sent to Pub/Sub
    Triggering a Cloud Run instance via Pub/Sub
    Creating a thumbnail with ImageMagick, and
    storing back into Cloud Storage
    Lab 4 — Create a web frontend
    Creating a web application with App Engine
    Listing pictures from Cloud Firestore
    Displaying pictures & collage
    from Cloud Storage
    g.co/codelabs/serverless-workshop
    

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33. Codelabs
    Lab 1 — Store and analyse pictures
    Storing pictures in Cloud Storage,
    trigger a Cloud Functions instance
    Calling the Cloud Vision API for analysis
    Storing metadata in Cloud Firestore
    Lab 3 — Create a collage of pictures
    At a regular interval, with Cloud Scheduler
    Invoking a Cloud Run instance,
    to create a collage of recent pictures
    found in Cloud Firestore
    Storing collage in Cloud Storage
    Lab 2 — Create thumbnails
    Cloud Storage notifications sent to Pub/Sub
    Triggering a Cloud Run instance via Pub/Sub
    Creating a thumbnail with ImageMagick, and
    storing back into Cloud Storage
    Lab 4 — Create a web frontend
    Creating a web application with App Engine
    Listing pictures from Cloud Firestore
    Displaying pictures & collage
    from Cloud Storage
    g.co/codelabs/serverless-workshop
    

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34. 05
    App Engine
    

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35. Dedicated Server
    Dedicated Server
    OS
    Application
    Runtime
    Application
    Virtual Hardware
    Functions
    Physical Hardware
    OS
    Application
    Runtime
    Application
    Hardware
    Functions
    Dedicated Server
    OS
    Application
    Runtime
    Application
    Hardware
    Functions
    Serverless
    OS
    Application
    Runtime
    Application
    Hardware
    Functions
    Function
    Cloud Functions
    On-Premises
    Virtual Machine
    OS
    Application
    Runtime
    Application
    Hardware
    Functions
    Infrastructure
    Compute Engine
    Containers
    OS
    Application
    Runtime
    Application
    Hardware
    Functions
    Container
    Kubernetes Engine
    Application Platform
    OS
    Application
    Runtime
    Application
    Hardware
    Functions
    Platform
    App Engine
    Highly customizable Highly managed
    

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36. What is App Engine?
    Serverless, but for your whole web app and not just single functions.
    App Engine goal: let developers focus on code, GCP handle the rest
    Can scale very quickly
    Open-source, idiomatic experience
    Use any library, extension, binary, or framework
    Python, Java, Node.js, PHP, Ruby, Go
    

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37. App Engine
    Standard (2nd gen)
    ● Open-source, idiomatic experience
    ● Use any extension, binary, or framework
    ● Supported Runtimes
    ○ Python 3.7 (3.8 in beta)
    ○ Java 11
    ○ Node.js 10 (12 in beta)
    ○ PHP 7.3
    ○ Go 1.12
    App Engine
    Flexible
    ● Runs Docker containers
    ● Open source runtimes for Node.js, Ruby,
    Java, Python, Go, PHP, .NET
    ● Also, if it runs in a Docker container,
    you can run it ← nearly everything
    ⚠Not serverless!
    

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38. App Engine runtimes
    Standard 1st generation Standard 2nd generation Flexible
    Python 2.X, Java, PHP, Go Node.js 10, Python 3.7,
    Go 1.12, PHP 7.3, Java 11
    Node.js, Ruby, Java, Python,
    Go, PHP, .NET
    & custom container images
    Sandboxed processes Runs on managed VMs
    GAE specific APIs + GCP APIs Use GCP APIs directly
    No binary modules / libraries any extension, binary, or framework
    open-source, idiomatic experience
    

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39. Concurrency
    & scaling
    Traffic
    Traffic
    •Scale up/down
    •Scale-up may lead to "cold starts"
    •One vs. multiple concurrent requests
    •Traffic splitting across versions
    •CDN static asset serving
    

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40. Why choose...
    App Engine
    The right abstraction: use a web framework
    that supports routes and HTTP methods
    Web traffic requires minimal latency
    Custom domains
    Java, Python, Node.js, Go, PHP, Ruby
    

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41. Good fit
    HTTP/S request-response
    Stateless serving applications
    Scaling to high traffic
    CDN static asset serving
    Constraints
    Standard (1st gen)
    ● Runtimes for Python, Java, PHP, Go, Node.js
    Standard (2nd gen)
    ● Can use use binary extensions
    ● Python, Node.js, Java, Go, Ruby, PHP
    Flexible runtimes
    ● Inherit Docker constraints
    ● Not best for very low traffic sites (no scale to 0)
    ● Slow deploy times
    Good fit? Constraints?
    

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42. Codelabs
    Lab 1 — Store and analyse pictures
    Storing pictures in Cloud Storage,
    trigger a Cloud Functions instance
    Calling the Cloud Vision API for analysis
    Storing metadata in Cloud Firestore
    Lab 3 — Run containers on schedule
    At a regular interval, with Cloud Scheduler
    Invoking a Cloud Run instance,
    to create a collage of recent pictures
    found in Cloud Firestore
    Storing collage in Cloud Storage
    Lab 2 — Create thumbnails
    Cloud Storage notifications sent to Pub/Sub
    Triggering a Cloud Run instance via Pub/Sub
    Creating a thumbnail with ImageMagick, and
    storing back into Cloud Storage
    Lab 4 — Create a web frontend
    Creating a web application with App Engine
    Listing pictures from Cloud Firestore
    Displaying pictures & collage
    from Cloud Storage
    g.co/codelabs/serverless-workshop
    

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43. 06
    Eventarc
    Trigger Cloud Run
    services with events
    from Google Cloud
    

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44. Proprietary + Confidential
    A new way of getting events to managed Cloud Run
    services
    Private alpha since early 2020 as Events for Cloud Run
    Public GA as Eventarc in Jan 2021
    Eventarc
    

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45. Eventarc - Vision
    

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46. Eventarc - Current State
    

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47. Proprietary + Confidential
    Create a trigger for new object creation in Cloud Storage → Cloud Run
    gcloud eventarc triggers create trigger-auditlog \
    --destination-run-service=${SERVICE_NAME} \
    --destination-run-region=${REGION}
    --event-filters="type=google.cloud.audit.log.v1.written" \
    --event-filters="serviceName=storage.googleapis.com" \
    --event-filters="methodName=storage.objects.create" \
    --event-filters=${PROJECT_NO}-compute@developer.gserviceaccount.com
    gcloud - AuditLog
    

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48. Proprietary + Confidential
    Create a trigger for Pub/Sub messages → Cloud Run
    gcloud eventarc triggers create trigger-pubsub \
    --destination-run-service=${SERVICE_NAME} \
    --destination-run-region=${REGION}
    --event-filters="type=google.cloud.pubsub.topic.v1.messagePublished"
    --transport-topic=projects/${PROJECT_ID}/topics/${TOPIC_ID}
    gcloud - Pub/Sub
    

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49. Proprietary + Confidential
    Cloud Console - Trigger section of Cloud Run
    

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50. POST / HTTP/1.1
    Content-Type: application/json; charset=utf-8
    Content-Length: 33
    ce-specversion: 1.0
    ce-type: google.cloud.pubsub.topic.publish
    ce-time: 2020-09-05T03:56:24Z
    ce-id: 1234-1234-1234
    ce-source: mycontext/subcontext
    custom-attr: 42
    {
    "message": "Hello Cloud Next!"
    }
    CloudEvents
    cloudevents.io
    "Data"
    "Context"
    

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51. Cloud Run Service
    CloudEvent SDK
    HTTP request → CloudEvent in your language
    cloudevents.io
    Google Events Library
    Type library for CloudEvent#data
    Event parsing libraries
    HTTP POST
    to Cloud Run URL
    HTTP body is a
    CloudEvent with
    event data
    ("binary" CloudEvent V1)
    (optional)
    (optional)
    github.com/googleapis/google-cloudevents
    

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52. Proprietary + Confidential
    const { HTTP } = require("cloudevents");
    const {toLogEntryData} = require('@google/events/cloud/audit/v1/LogEntryData')
    app.post('/', async (req, res) => {
    // Read CloudEvent using CloudEvents SDK
    const cloudEvent = HTTP.toEvent({ headers: req.headers, body: req.body });
    // Read AuditLog using Google.Events library for Node.js
    const logEntryData = toLogEntryData(cloudEvent.data);
    // Extract bucket and objectName
    const tokens = logEntryData.protoPayload.resourceName.split('/');
    const bucket = tokens[3];
    const objectName = tokens[5];
    

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53. Proprietary + Confidential
    using CloudNative.CloudEvents;
    using Google.Events;
    using Google.Events.Protobuf.Cloud.PubSub.V1;
    public async Task Read(HttpContext context) {
    // Read CloudEvent using CloudEvents SDK
    var cloudEvent = await context.Request.ReadCloudEventAsync();
    // Read Pub/Sub message using Google.Events library for .NET
    var messagePublishedData =
    CloudEventConverters.ConvertCloudEventData(cloudEvent);
    // Extract the Pub/Sub message
    var pubSubMessage = messagePublishedData.Message;
    

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54. Codelabs
    Lab 5 — Cleanup after image deletion
    Cloud Storage delete notifications sent to
    Eventarc via Audit Logs
    Triggering a Cloud Run instance via Eventarc
    Cloud Run service deletes image thumbnails and
    metadata
    Lab 6 — Orchestration with Workflows
    Creating a workflow of our “business process”
    Reworking the services for an orchestrated
    architecture
    Triggering a Workflows from a Cloud Function
    g.co/codelabs/serverless-workshop
    

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55. 07
    Workflows
    From a loosely-coupled
    event-driven choreography,
    towards an orchestrated
    architecture
    

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56. Choreography: Pros and Cons
    Pros
    ➕ Services are loosely coupled,
    ➕ Services can be changed
    independently
    ➕ Services can be scaled
    independently
    ➕ No single point of failure
    ➕ Events are useful to extend the
    system beyond the current domain
    Cons
    ➖ Difficult to monitor the whole system
    ➖ Errors / retries / timeouts are problematic
    ➖ The business flow is not captured explicitly
    ➖ Who ensures the whole transaction is
    successful?
    

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57. Orchestration: Pros and Cons
    Pros
    ➕ Business flow captured centrally and
    source controlled
    ➕ Each step can be monitored
    ➕ Errors / retries / timeouts are
    centralized
    ➕ Use simple REST, no need for events
    ➕ Services are still independent
    Cons
    ➖ A new orchestrator service to worry about
    ➖ Orchestrator could be a single point of
    failure
    ➖ Reliance on REST means more
    tight-coupling
    

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58. Serverless
    Compute
    External
    API’s
    Google
    API’s
    etc...
    Workflows - orchestrate & integrate
    SaaS
    API’s
    Private
    API’s
    Other
    Clouds
    

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59. - processPayment:
    params: [paymentDetails]
    call: http.post
    args:
    url: https://payment-processor.run.app/...
    body:
    input: ${paymentDetails}
    result: processResult
    - shipItems:
    call: http.post
    args:
    url: https://.../cloudfunctions.net/ship
    body:
    input: ${processResult.body}
    result: shipResult
    - notifyUser:
    call: http.post
    ...
    Payment Processor
    Cloud Run
    Authorize & charge CC
    Notifier
    Cloud Run
    Notify user
    Shipper
    Cloud Functions
    Prepare & ship items
    YAML or JSON syntax
    

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60. Payment Processor
    Cloud Run
    Authorize & charge CC
    Notifier
    Cloud Run
    Notify user
    Shipper
    Cloud Functions
    Prepare & ship items
    Payment Processor
    Cloud Run
    Authorize & charge CC
    Notifier
    Cloud Run
    Notify user
    Shipper
    Cloud Functions
    Prepare & ship items
    WAIT
    Payment Processor
    Cloud Run
    Authorize & charge CC
    Notifier
    Cloud Run
    Notify user
    Shipper
    Cloud Functions
    Prepare & ship items
    shipmentDetails
    userDetails
    Step Sequencing Serverless Pause
    Variable passing
    JSON Parsing
    Steps
    

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61. Payment Processor
    Cloud Run
    Authorize & charge CC
    Notifier
    Cloud Run
    Notify user
    Shipper
    Cloud Functions
    Prepare & ship items
    MAX: 5 times
    BACKOFF
    Payment Processor
    Cloud Run
    Authorize & charge CC
    Notifier
    Cloud Run
    Notify user
    Shipper
    Cloud Functions
    Prepare & ship items
    Pager
    Cloud Run
    Escalate to support
    SUCCESS ERROR
    Configurable retries Configurable exception handling
    Errors and retries
    

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62. Notifier
    Cloud Run
    Notify user
    Shipper
    Cloud Functions
    Prepare & ship items
    Pager
    Cloud Run
    Escalate to support
    SUCCESS
    ERROR
    Out of
    Stock?
    No
    Request from the
    supplier
    Yes
    Read inventory
    Inventory DB
    Update inventory
    Inventory DB
    Supplier API
    Conditionals and 3rd party calls
    

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63. Subworkflows
    to encapsulate common reusable flows
    Connectors ßeta
    to connect to other Google Cloud services & APIs
    Other useful features
    

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64. # Deploy a workflow
    gcloud workflows deploy my-workflow --source=workflow.yaml
    # Execute a workflow
    gcloud workflows execute my-workflow
    # See the result
    gcloud workflows executions
    describe
    --workflow my-workflow
    Deploy, execute, manage workflows
    

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66. An orchestration of microservices
    

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67. Codelabs
    Lab 5 — Cleanup after image deletion
    Cloud Storage delete notifications sent to
    Eventarc via Audit Logs
    Triggering a Cloud Run instance via Eventarc
    Cloud Run service deletes image thumbnails and
    metadata
    Lab 6 — Orchestration with Workflows
    Creating a workflow of our “business process”
    Reworking the services for an orchestrated
    architecture
    Triggering a Workflows from a Cloud Function
    g.co/codelabs/serverless-workshop
    

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68. Proprietary + Confidential
    Guillaume Laforge — @glaforge
    Mete Atamel — @meteatamel
    

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