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Google Cloud Functions

An example integration where a Data Connector forwards events to a Google Cloud Function.

Overview

This example uses a Data Connector to forward the events of all devices in a project to a Google Cloud Function. When receiving the HTTPS POST request, our function will verify both the origin and content of the request using a signature secret, then decode the data.

Prerequisites

The following points are assumed.

Google Cloud Platform

While there are many advantages to using a local environment for development, this guide will be using the browser portal to minimize setup requirements.

Create a Cloud Function

Following this guide, create a new Cloud Function with the following configurations.
Python 3.9
Python API
Node.js 16
Go 1.16

(1) Configuration

Trigger

  • Trigger Type: HTTP
  • Authentication: Allow unauthenticated invocations.
Runtime, build, connections and security settings
Add a new runtime environment variable with the following values.
  • Name: DT_SIGNATURE_SECRET
  • Value: A unique password. We will need it later, so write it down.

(2) Code

  • Runtime: Python 3.9
  • Entry point: dataconnector_endpoint
In the Source Code, edit main.py with the following snippet. The implementation is explained in detail on the Data Connector Advanced Configurations page.
main.py
import os
import hashlib
import jwt # pip install pyjwt==2.3.0
# Fetch environment variables.
SIGNATURE_SECRET = os.environ.get('DT_SIGNATURE_SECRET')
def verify_request(body, token):
"""
Verifies that the request originated from DT, and that the body
hasn't been modified since it was sent. This is done by verifying
that the checksum field of the JWT token matches the checksum of the
request body, and that the JWT is signed with the signature secret.
"""
# Decode the token using signature secret.
try:
payload = jwt.decode(token, SIGNATURE_SECRET, algorithms=["HS256"])
except Exception as err:
print(err)
return False
# Verify the request body checksum.
m = hashlib.sha1()
m.update(body)
checksum = m.digest().hex()
if payload["checksum"] != checksum:
print('Checksum Mismatch')
return False
return True
def dataconnector_endpoint(request):
# Extract the body as a bytestring and the signed JWT.
# We'll use these values to verify the request.
payload = request.get_data()
token = request.headers['x-dt-signature']
# Verify request origin and content integrity.
if not verify_request(payload, token):
return ('Could not verify request.', 400)
# Decode the body as JSON
body = request.get_json()
# First, check if the event type is one of the event
# types we're expecting.
# As an example, we'll check for touch events here.
if body['event']['eventType'] == 'touch':
# Now that we know this is a device event, we can
# check for the device type and device identifier
# in the event metadata.
device_type = body['metadata']['deviceType']
device_id = body['metadata']['deviceId']
print(f"Received touch event from {device_type} sensor with id {device_id}")
return ('OK', 200)
Append the following snippet to requirements.txt.
requirements.txt
pyjwt==2.3.0
For details, read our Python API Documentation.

(1) Configuration

Trigger

  • Trigger Type: HTTP
  • Authentication: Allow unauthenticated invocations.
Runtime, build, connections and security settings
Add a new runtime environment variable with the following values.
  • Name: DT_SIGNATURE_SECRET
  • Value: A unique password. We will need it later, so write it down.

(2) Code

  • Runtime: Python 3.9
  • Entry point: dataconnector_endpoint
In the Source Code, edit main.py with the following snippet.
main.py
import os
from dtintegrations import data_connector, provider
def dataconnector_endpoint(request):
# Validate and decode the incoming request.
payload = data_connector.HttpPush.from_provider(
request=request,
provider=provider.GCLOUD,
secret=os.getenv('DT_SIGNATURE_SECRET'),
)
# Print the payload data.
print(payload)
# If all is well, return 200 response.
return ('OK', 200)
Append the following snippet to requirements.txt.
requirements.txt
dtintegrations==0.5.0

(1) Configuration

Trigger

  • Trigger Type: HTTP
  • Authentication: Allow unauthenticated invocations.
Runtime, build, connections and security settings
Add a new runtime environment variable with the following values.
  • Name: DT_SIGNATURE_SECRET
  • Value: A unique password. We will need it later, so write it down.

(2) Code

  • Runtime: Node.js 16
  • Entry point: dataconnectorEndpoint
In the Source Code, edit index.js with the following snippet. The implementation is explained in detail on the Data Connector Advanced Configurations page.
index.js
const crypto = require('crypto')
const jwt = require('jsonwebtoken') // npm install [email protected]
// Fetch environment variables
const signatureSecret = process.env.DT_SIGNATURE_SECRET
// Verifies that the request originated from DT, and that the body
// hasn't been modified since it was sent. This is done by verifying
// that the checksum field of the JWT token matches the checksum of the
// request body, and that the JWT is signed with the signature secret.
function verifyRequest(body, token) {
// Decode the JWT, and verify that it was
// signed using the signature secret.
let decoded
try {
decoded = jwt.verify(token, signatureSecret)
} catch(err) {
console.log(err)
return false
}
// Verify the request body checksum.
let shasum = crypto.createHash('sha1')
let checksum = shasum.update(body).digest('hex')
if (checksum !== decoded.checksum) {
console.log('Checksum Mismatch')
return false
}
return true
}
exports.dataconnectorEndpoint = (req, res) => {
// Extract the body as a string and the signed JWT.
// We'll use these values to verify the request.
let payload = JSON.stringify(req.body)
let token = req.get('X-Dt-Signature')
// Validate request origin and content integrity.
if (verifyRequest(payload, token) === false) {
res.sendStatus(400)
return
}
// First, check if the event type is one of the event
// types we're expecting.
// As an example, we'll check for touch events here.
switch (req.body.event.eventType) {
case 'touch':
// Now that we know this is a device event, we can
// check for the device type and device identifier
// in the event metadata.
deviceType = req.body.metadata.deviceType
deviceId = req.body.metadata.deviceId
console.log(`Received touch event from ${deviceType} sensor with id ${deviceId}`)
break
default:
break
}
res.sendStatus(200);
};
Edit package.json to contain the following dependencies field.
package.json
{
"dependencies": {
"jsonwebtoken": "^8.5.1"
}
}

(1) Configuration

Trigger

  • Trigger Type: HTTP
  • Authentication: Allow unauthenticated invocations.
Runtime, build, connections and security settings
Add a new runtime environment variable with the following values.
  • Name: DT_SIGNATURE_SECRET
  • Value: A unique password. We will need it later, so write it down.

(2) Code

  • Runtime: Go 1.16
  • Entry point: DataconnectorEndpoint
In the Source Code, edit function.go with the following snippet. The implementation is explained in detail on the Data Connector Advanced Configurations page.
function.go
package main
import (
"crypto/sha1"
"encoding/hex"
"encoding/json"
"fmt"
"io/ioutil"
"net/http"
"os"
jwt "github.com/golang-jwt/jwt/v4" // go get github.com/golang-jwt/jwt/[email protected]
)
// Environment variables.
var signatureSecret = os.Getenv("DT_SIGNATURE_SECRET")
// verifyRequest verifies that the request originated from DT, and that the
// body hasn't been modified since it was sent. This is done by verifying
// that the checksum field of the JWT token matches the checksum of the
// request body, and that the JWT is signed with the signature secret.
func verifyRequest(bodyBytes []byte, tokenString string) error {
// Decode the JWT, and verify that it was signed using the signature secret.
// Also verifies the algorithm used to sign the JWT.
token, err := jwt.Parse(tokenString, func(token *jwt.Token) (interface{}, error) {
// Return out signature secret to verify that it was used to sign the JWT.
return []byte(signatureSecret), nil
}, jwt.WithValidMethods([]string{"HS256"}))
if err != nil {
return err
}
// Verify the request body checksum.
sha1Bytes := sha1.Sum(bodyBytes)
sha1String := hex.EncodeToString(sha1Bytes[:])
claims := token.Claims.(jwt.MapClaims)
if sha1String != claims["checksum"] {
return fmt.Errorf("Checksum mismatch.")
}
return nil
}
// DataConnectorEndpoint receives, validates, and returns a response for the forwarded event.
func DataconnectorEndpoint(w http.ResponseWriter, r *http.Request) {
// Extract the body and the signed JWT.
// We'll use these values to verify the request.
tokenString := r.Header.Get("x-dt-signature")
bodyBytes, err := ioutil.ReadAll(r.Body)
if err != nil {
fmt.Println(err)
http.Error(w, err.Error(), http.StatusBadRequest)
return
}
// Validate request origin and content integrity.
if err := verifyRequest(bodyBytes, tokenString); err != nil {
fmt.Println(err)
http.Error(w, err.Error(), http.StatusBadRequest)
return
}
// We now know the request came from DT Cloud, and the integrity
// of the body has been verify. We can now handle the event safely.
if err := handleEvent(bodyBytes); err != nil {
fmt.Println(err)
http.Error(w, err.Error(), http.StatusBadRequest)
return
}
// Respond with a 200 status code to ack the event,
w.WriteHeader(http.StatusOK)
_, _ = w.Write([]byte("OK"))
}
func handleEvent(payload []byte) error {
// The structure of the events we'll received from a Data Connector.
type Event struct {
Event struct {
EventId string `json:"eventId"`
EventType string `json:"eventType"`
Data json.RawMessage `json:"data"`
Timestamp string `json:"timestamp"`
} `json:"event"`
Labels map[string]string `json:"labels"`
Metadata map[string]string `json:"metadata"`
}
// The structure of the `Event.Data` field for a touch event.
// We'll be using touch events for this example.
type TouchData struct {
Touch struct {
Timestamp string `json:"updateTime"`
} `json:"touch"`
}
// Decode the event
var event Event
if err := json.Unmarshal(payload, &event); err != nil {
return err
}
// First, check if the event type is one of the event
// types we're expecting.
// As an example, we'll check for touch events here.
switch event.Event.EventType {
case "touch":
// Now that we know this is a touch event, we can decode
// the `Event.Data` field.
var touchData TouchData
if err := json.Unmarshal(event.Event.Data, &touchData); err != nil {
return err
}
// Also, since we now know this is a device event, we can
// check for the device type and device identifier
// in the event metadata.
deviceType := event.Metadata["deviceType"]
deviceId := event.Metadata["deviceId"]
timestamp := touchData.Touch.Timestamp
fmt.Printf("Received touch event at %s from %s sensor with id %s\n",
timestamp,
deviceType,
deviceId,
)
}
return nil
}
Replace the content of go.mod with the following snippet.
module example.com/cloudfunction
go 1.16
require github.com/golang-jwt/jwt/v4 v4.2.0
When configured, deploy your function.

Post Deployment

Your function is now ready to receive requests, but we need to know the target URL. In your function, locate the TRIGGER tab and copy the Trigger URL. Save this for later.

Create a Data Connector

To continuously forward the data to our newly created Cloud Function, a Data Connector with almost all default settings is sufficient. If you are unfamiliar with how Data Connectors can be created, refer to our Creating a Data Connector guide using the following configurations.
  • Endpoint URL: The Trigger URL found in the previous step.
  • Signature Secret: The value of the DT_SIGNATURE_SECRET environment variable.
Depending on your integration, it can also be smart to disable the event types you are not interested in. For instance, the networkStatus event is sent every periodic heartbeat and will by default be forwarded by the Data Connector if not explicitly unticked.

Test the Integration

If the integration was correctly implemented, the Success counter for your Data Connector should increment for each new event forwarded. This happens each periodic heartbeat or by touching a sensor to force a new event.
If instead the Error counter increments, a response containing a non-2xx status code is returned.
  • Verify that the Data Connector endpoint URL is correct.
  • Google provides a host of tools that monitor Cloud Functions. Check the logs for any tracebacks that could explain why an error is returned.

Next steps

Your sensor data is now in the Google Cloud environment, and you can start using it in their various services. Fortunately, Google has some well-documented guides to get you started.

PostgreSQL Database

A database should be tailored to each specific use case. However, if you're uncertain, PostgreSQL (Postgres) is a good place to get started. The following guides will show you how to create a new Postgres database, then connect your Cloud Function to execute queries.

DataStudio

Once your Database has been set up, the following guide shows you how to connect it to DataStudio for continuous data visualization and analytics.
Last modified 10mo ago