In this lab you will build a PDF converter web app on Cloud Run, which is a serverless service, that automatically converts files stored in Google Drive into PDFs stored in segregated Google Drive folders.
Objectives
In this lab, you will:
Convert a Go application to a container
Learn how to build containers with Google Cloud Build
Create a Cloud Run service that converts files to PDF files in the cloud.
Understand how to create Service Accounts and add permissions
Use event processing with Cloud Storage
Setup and requirements
Before you click the Start Lab button
Read these instructions. Labs are timed and you cannot pause them. The timer, which starts when you click Start Lab, shows how long Google Cloud resources are made available to you.
This hands-on lab lets you do the lab activities in a real cloud environment, not in a simulation or demo environment. It does so by giving you new, temporary credentials you use to sign in and access Google Cloud for the duration of the lab.
To complete this lab, you need:
Access to a standard internet browser (Chrome browser recommended).
Note: Use an Incognito (recommended) or private browser window to run this lab. This prevents conflicts between your personal account and the student account, which may cause extra charges incurred to your personal account.
Time to complete the lab—remember, once you start, you cannot pause a lab.
Note: Use only the student account for this lab. If you use a different Google Cloud account, you may incur charges to that account.
How to start your lab and sign in to the Google Cloud console
Click the Start Lab button. If you need to pay for the lab, a dialog opens for you to select your payment method.
On the left is the Lab Details pane with the following:
The Open Google Cloud console button
Time remaining
The temporary credentials that you must use for this lab
Other information, if needed, to step through this lab
Click Open Google Cloud console (or right-click and select Open Link in Incognito Window if you are running the Chrome browser).
The lab spins up resources, and then opens another tab that shows the Sign in page.
Tip: Arrange the tabs in separate windows, side-by-side.
Note: If you see the Choose an account dialog, click Use Another Account.
If necessary, copy the Username below and paste it into the Sign in dialog.
{{{user_0.username | "Username"}}}
You can also find the Username in the Lab Details pane.
Click Next.
Copy the Password below and paste it into the Welcome dialog.
{{{user_0.password | "Password"}}}
You can also find the Password in the Lab Details pane.
Click Next.
Important: You must use the credentials the lab provides you. Do not use your Google Cloud account credentials.
Note: Using your own Google Cloud account for this lab may incur extra charges.
Click through the subsequent pages:
Accept the terms and conditions.
Do not add recovery options or two-factor authentication (because this is a temporary account).
Do not sign up for free trials.
After a few moments, the Google Cloud console opens in this tab.
Note: To access Google Cloud products and services, click the Navigation menu or type the service or product name in the Search field.
Activate Cloud Shell
Cloud Shell is a virtual machine that is loaded with development tools. It offers a persistent 5GB home directory and runs on the Google Cloud. Cloud Shell provides command-line access to your Google Cloud resources.
Click Activate Cloud Shell at the top of the Google Cloud console.
Click through the following windows:
Continue through the Cloud Shell information window.
Authorize Cloud Shell to use your credentials to make Google Cloud API calls.
When you are connected, you are already authenticated, and the project is set to your Project_ID, . The output contains a line that declares the Project_ID for this session:
Your Cloud Platform project in this session is set to {{{project_0.project_id | "PROJECT_ID"}}}
gcloud is the command-line tool for Google Cloud. It comes pre-installed on Cloud Shell and supports tab-completion.
(Optional) You can list the active account name with this command:
gcloud auth list
Click Authorize.
Output:
ACTIVE: *
ACCOUNT: {{{user_0.username | "ACCOUNT"}}}
To set the active account, run:
$ gcloud config set account `ACCOUNT`
(Optional) You can list the project ID with this command:
gcloud config list project
Output:
[core]
project = {{{project_0.project_id | "PROJECT_ID"}}}
Note: For full documentation of gcloud, in Google Cloud, refer to the gcloud CLI overview guide.
Architecture
In this lab you will assist the Pet Theory Veterinary practice to automatically convert their invoices into PDFs so that customers can open them reliably.
Using Google APIs
During this lab you will use Google APIs. The following APIs have been enabled for you:
Name
API
Cloud Build
cloudbuild.googleapis.com
Cloud Storage
storage-component.googleapis.com
Cloud Run Admin
run.googleapis.com
Task 1. Get the source code
Get started by downloading the code necessary for this lab.
Activate your lab account:
gcloud auth list --filter=status:ACTIVE --format="value(account)"
Run the following to clone the Pet Theory repository:
In this section you will create a Go application to process requests. As outlined
in the architecture diagram, you will integrate Cloud Storage as part of the
solution.
Click the Open Editor icon and then click Open in a new window.
Navigate to pet-theory > lab03 > server.go
Open the server.go source code and edit it to match the text below:
package main
import (
"fmt"
"log"
"net/http"
"os"
"os/exec"
"regexp"
"strings"
)
func main() {
http.HandleFunc("/", process)
port := os.Getenv("PORT")
if port == "" {
port = "8080"
log.Printf("Defaulting to port %s", port)
}
log.Printf("Listening on port %s", port)
err := http.ListenAndServe(fmt.Sprintf(":%s", port), nil)
log.Fatal(err)
}
func process(w http.ResponseWriter, r *http.Request) {
log.Println("Serving request")
if r.Method == "GET" {
fmt.Fprintln(w, "Ready to process POST requests from Cloud Storage trigger")
return
}
//
// Read request body containing Cloud Storage object metadata
//
gcsInputFile, err1 := readBody(r)
if err1 != nil {
log.Printf("Error reading POST data: %v", err1)
w.WriteHeader(http.StatusBadRequest)
fmt.Fprintf(w, "Problem with POST data: %v \n", err1)
return
}
//
// Working directory (concurrency-safe)
localDir, err := os.MkdirTemp("", "")
if err != nil {
log.Printf("Error creating local temp dir: %v", err)
w.WriteHeader(http.StatusInternalServerError)
fmt.Fprintf(w, "Could not create a temp directory on server. \n")
return
}
defer os.RemoveAll(localDir)
//
// Download input file from Cloud Storage
//
localInputFile, err2 := download(gcsInputFile, localDir)
if err2 != nil {
log.Printf("Error downloading Cloud Storage file [%s] from bucket [%s]: %v",
gcsInputFile.Name, gcsInputFile.Bucket, err2)
w.WriteHeader(http.StatusInternalServerError)
fmt.Fprintf(w, "Error downloading Cloud Storage file [%s] from bucket [%s]",
gcsInputFile.Name, gcsInputFile.Bucket)
return
}
//
// Use LibreOffice to convert local input file to local PDF file.
//
localPDFFilePath, err3 := convertToPDF(localInputFile.Name(), localDir)
if err3 != nil {
log.Printf("Error converting to PDF: %v", err3)
w.WriteHeader(http.StatusInternalServerError)
fmt.Fprintf(w, "Error converting to PDF.")
return
}
//
// Upload the freshly generated PDF to Cloud Storage
//
targetBucket := os.Getenv("PDF_BUCKET")
err4 := upload(localPDFFilePath, targetBucket)
if err4 != nil {
log.Printf("Error uploading PDF file to bucket [%s]: %v", targetBucket, err4)
w.WriteHeader(http.StatusInternalServerError)
fmt.Fprintf(w, "Error downloading Cloud Storage file [%s] from bucket [%s]",
gcsInputFile.Name, gcsInputFile.Bucket)
return
}
//
// Delete the original input file from Cloud Storage.
//
err5 := deleteGCSFile(gcsInputFile.Bucket, gcsInputFile.Name)
if err5 != nil {
log.Printf("Error deleting file [%s] from bucket [%s]: %v", gcsInputFile.Name,
gcsInputFile.Bucket, err5)
// This is not a blocking error.
// The PDF was successfully generated and uploaded.
}
log.Println("Successfully produced PDF")
fmt.Fprintln(w, "Successfully produced PDF")
}
func convertToPDF(localFilePath string, localDir string) (resultFilePath string, err error) {
log.Printf("Converting [%s] to PDF", localFilePath)
cmd := exec.Command("libreoffice", "--headless", "--convert-to", "pdf",
"--outdir", localDir,
localFilePath)
cmd.Stdout, cmd.Stderr = os.Stdout, os.Stderr
log.Println(cmd)
err = cmd.Run()
if err != nil {
return "", err
}
pdfFilePath := regexp.MustCompile(`\.\w+$`).ReplaceAllString(localFilePath, ".pdf")
if !strings.HasSuffix(pdfFilePath, ".pdf") {
pdfFilePath += ".pdf"
}
log.Printf("Converted %s to %s", localFilePath, pdfFilePath)
return pdfFilePath, nil
}
Now run the following to build the application:
go build -o server
The functions called by this top-level code are in source files:
server.go
notification.go
gcs.go
With the application has been successfully built, you can create the
pdf-conversion service.
Task 3. Create a pdf-conversion service
The PDF service will use Cloud Run and Cloud Storage to initiate a process
each time a file is uploaded to the designated storage.
To achieve this you will use a common pattern of event notifications together with
Cloud Pub/Sub. Doing this enables the application to concentrate only on
processing information. Transporting and passing information is performed by
other services, which allows you to keep the
application simple.
Building the invoice module requires the integration of two components:
Adding the LibreOffice package means it can be used in your application.
In the Open editor, Open the existing Dockerfile manifest and update the file as shown below:
FROM amd64/debian
RUN apt-get update -y \
&& apt-get install -y libreoffice \
&& apt-get clean
WORKDIR /usr/src/app
COPY server .
CMD [ "./server" ]
Save the updated Dockerfile.
Initiate a rebuild of the pdf-converter image using Cloud Build:
Click Check my progress to verify that you've performed the above task.
PDF Converter service deployed
The Cloud Run service has now been successfully deployed. However we deployed
an application that requires the correct permissions to access it.
Task 4. Create a Service Account
A Service Account
is a special type of account with access to Google APIs.
In this lab uses a Service Account to access Cloud Run when a Cloud Storage
event is processed. Cloud Storage supports a rich set of notifications that can be used to
trigger events.
Next, update the code to notify the application when a file has been
uploaded.
Click the Navigation menu > Cloud Storage, and verify that two buckets have been created. You should see:
-processed
-upload
Create a Pub/Sub notification to indicate a new file has been uploaded to the docs bucket ("uploaded"). The notifications will be labeled with the topic "new-doc".
Make an anonymous GET request to your new service:
curl -X GET $SERVICE_URL
Expected Output:
<html><head>
<meta http-equiv="content-type" content="text/html;charset=utf-8">
<title>403 Forbidden</title>
</head>
<body text=#000000 bgcolor=#ffffff>
<h1>Error: Forbidden</h1>
<h2>Your client does not have permission to get URL <code>/</code> from this server.</h2>
<h2></h2>
NOTE:
The anonymous GET request will result in an error message:
"Your client does not have permission to get URL".
This is good; you don't want the service to be callable by anonymous users.
Now try invoking the service as an authorized user:
curl -X GET -H "Authorization: Bearer $(gcloud auth print-identity-token)" $SERVICE_URL
Expected Output:
Ready to process POST requests from Cloud Storage trigger
Great work, you have successfully deployed an authenticated Cloud Run service.
Task 6. Cloud Storage trigger
To initiate a notification when new content is uploaded to Cloud Storage,
add a subscription to your existing Pub/Sub Topic.
Note: Cloud Storage notifications will automatically push a message to your Topic queue when new content is uploaded. Using notifications allows you to create powerful applications that respond to events without needing to write additional code.
Create a Pub/Sub subscription so that the PDF converter will be run
whenever a message is published to the topic new-doc:
Created subscription [projects/{{{ project_0.project_id| "PROJECT_ID" }}}/subscriptions/pdf-conv-sub].
Click Check my progress to verify that you've performed the above task.
Confirm Pub/Sub Subscription
Now whenever a file is uploaded the Pub/Sub subscription will interact with your Service
Account. The Service Account will then initiate your PDF Converter Cloud Run service.
Task 7. Testing Cloud Storage notification
To test the Cloud Run service, use the example files available.
In the Cloud Console, click Cloud Storage > Buckets followed by the bucket name whose name ends in "-upload"
Click the Refresh button a few times and see how the files are deleted, one by one, as they are converted to PDFs.
Then click Buckets, followed by the bucket whose name ends in "-processed". It should contain PDF versions of all files.
NOTE:
It can take a few minutes for the processing of the files.
Use the Bucket refresh option to check the processing completion state.
Feel free to open the PDF files to make sure they were properly converted.
Once the upload is done, click Navigation menu > Cloud Run and click on the pdf-converter service.
Select the LOGS tab and add a filter of "Converting" to see the converted files.
Navigate to Navigation menu > Cloud Storage and open the bucket name ending in "-upload" to confirm all files uploaded have been processed.
Excellent work, you have successfully built a new service to create a PDF using files uploaded to Cloud Storage.
Congratulations!
In this lab, you've learned how to convert a Go application into a container, learned how to construct containers utilizing Google Cloud Build, and launched a Cloud Run service.
You've also gained skills in enabling permissions through a Service Account and leveraging Cloud Storage event processing, all of which are integral to the operation of the pdf-converter service that transforms documents into PDFs and stores them in the "processed" bucket.
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Manual Last Updated February 25, 2025
Lab Last Tested February 25, 2025
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Use private browsing to run the lab
Use an Incognito or private browser window to run this lab. This
prevents any conflicts between your personal account and the Student
account, which may cause extra charges incurred to your personal account.
Learn how to develop an application to create PDFs on Google Cloud using Serverless technologies and Go.