This tutorial shows how to build a custom Cloud Run service
that transforms a graph description input parameter into a diagram in the PNG
image format. It uses Graphviz and
is installed as a system package in the service's container environment.
Graphviz is used via command-line utilities to serve requests.
Objectives
- Write and build a custom container with a Dockerfile
- Write, build, and deploy a Cloud Run service
- Use Graphviz dot utility to generate diagrams
- Test the service by posting a DOT syntax diagram from the collection or your own creation
Costs
In this document, you use the following billable components of Google Cloud:
To generate a cost estimate based on your projected usage,
use the pricing calculator.
Before you begin
- Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.
-
In the Google Cloud console, on the project selector page, select or create a Google Cloud project.
-
Make sure that billing is enabled for your Google Cloud project.
-
In the Google Cloud console, on the project selector page, select or create a Google Cloud project.
-
Make sure that billing is enabled for your Google Cloud project.
- Enable the Cloud Run Admin API
- Install and initialize the gcloud CLI.
- Update components:
gcloud components update
Required roles
To get the permissions that you need to complete the tutorial, ask your administrator to grant you the following IAM roles on your project:
-
Cloud Build Editor (
roles/cloudbuild.builds.editor
) -
Cloud Run Admin (
roles/run.admin
) -
Create Service Accounts (
roles/iam.serviceAccountCreator
) -
Service Account User (
roles/iam.serviceAccountUser
) -
Service Usage Consumer (
roles/serviceusage.serviceUsageConsumer
) -
Storage Admin (
roles/storage.admin
)
For more information about granting roles, see Manage access to projects, folders, and organizations.
You might also be able to get the required permissions through custom roles or other predefined roles.
Setting up gcloud defaults
To configure gcloud with defaults for your Cloud Run service:
Set your default project:
gcloud config set project PROJECT_ID
Replace PROJECT_ID with the name of the project you created for this tutorial.
Configure gcloud for your chosen region:
gcloud config set run/region REGION
Replace REGION with the supported Cloud Run region of your choice.
Cloud Run locations
Cloud Run is regional, which means the infrastructure that
runs your Cloud Run services is located in a specific region and is
managed by Google to be redundantly available across
all the zones within that region.
Meeting your latency, availability, or durability requirements are primary
factors for selecting the region where your Cloud Run services are run.
You can generally select the region nearest to your users but you should consider
the location of the other Google Cloud
products that are used by your Cloud Run service.
Using Google Cloud products together across multiple locations can affect
your service's latency as well as cost.
Cloud Run is available in the following regions:
Subject to Tier 1 pricing
asia-east1
(Taiwan)asia-northeast1
(Tokyo)asia-northeast2
(Osaka)europe-north1
(Finland) Low CO2europe-southwest1
(Madrid) Low CO2europe-west1
(Belgium) Low CO2europe-west4
(Netherlands) Low CO2europe-west8
(Milan)europe-west9
(Paris) Low CO2me-west1
(Tel Aviv)us-central1
(Iowa) Low CO2us-east1
(South Carolina)us-east4
(Northern Virginia)us-east5
(Columbus)us-south1
(Dallas) Low CO2us-west1
(Oregon) Low CO2
Subject to Tier 2 pricing
africa-south1
(Johannesburg)asia-east2
(Hong Kong)asia-northeast3
(Seoul, South Korea)asia-southeast1
(Singapore)asia-southeast2
(Jakarta)asia-south1
(Mumbai, India)asia-south2
(Delhi, India)australia-southeast1
(Sydney)australia-southeast2
(Melbourne)europe-central2
(Warsaw, Poland)europe-west10
(Berlin) Low CO2europe-west12
(Turin)europe-west2
(London, UK) Low CO2europe-west3
(Frankfurt, Germany) Low CO2europe-west6
(Zurich, Switzerland) Low CO2me-central1
(Doha)me-central2
(Dammam)northamerica-northeast1
(Montreal) Low CO2northamerica-northeast2
(Toronto) Low CO2southamerica-east1
(Sao Paulo, Brazil) Low CO2southamerica-west1
(Santiago, Chile) Low CO2us-west2
(Los Angeles)us-west3
(Salt Lake City)us-west4
(Las Vegas)
If you already created a Cloud Run service, you can view the region in the Cloud Run dashboard in the Google Cloud console.
Retrieving the code sample
To retrieve the code sample for use:
Clone the sample app repository to your local machine:
Node.js
git clone https://github.com/GoogleCloudPlatform/nodejs-docs-samples.git
Alternatively, you can download the sample as a zip file and extract it.
Python
git clone https://github.com/GoogleCloudPlatform/python-docs-samples.git
Alternatively, you can download the sample as a zip file and extract it.
Go
git clone https://github.com/GoogleCloudPlatform/golang-samples.git
Alternatively, you can download the sample as a zip file and extract it.
Java
git clone https://github.com/GoogleCloudPlatform/java-docs-samples.git
Alternatively, you can download the sample as a zip file and extract it.
Change to the directory that contains the Cloud Run sample code:
Node.js
cd nodejs-docs-samples/run/system-package/
Python
cd python-docs-samples/run/system-package/
Go
cd golang-samples/run/system_package/
Java
cd java-docs-samples/run/system-package/
Visualizing the architecture
The basic architecture looks like this:
The user makes an HTTP request to the Cloud Run service which executes a Graphviz utility to transform the request into an image. That image is delivered to the user as the HTTP response.
Understanding the code
Defining your environment configuration with the Dockerfile
Your Dockerfile
is specific to the language and base operating environment,
such as Ubuntu, that your service will use.
The Build and Deploy Quickstart
shows various Dockerfiles
that can be used as a starting point to build a
Dockerfile
for other services.
This service requires one or more additional system packages not available by default.
Open the
Dockerfile
in an editor.Look for a
Dockerfile
RUN
statement. This statement allows running arbitrary shell commands to modify the environment. If theDockerfile
has multiple stages, identified by finding multipleFROM
statements, it will be found in the last stage.The specific packages required and the mechanism to install them varies by the operating system declared inside the container.
To get instructions for your operating system or base image, click the appropriate tab.
Debian/Ubuntu Alpine Alpine requires a second package for font support.To determine the operating system of your container image, check the name in the
FROM
statement or a README associated with your base image. For example, if you extend fromnode
, you can find documentation and the parentDockerfile
on Docker Hub.Test your customization by building the image, using
docker build
locally or Cloud Build.
Handling incoming requests
The sample service uses parameters from the incoming HTTP request to invoke a
system call that executes the appropriate dot
utility command.
In the HTTP handler below, a graph description input parameter is extracted from
the dot
querystring variable.
Graph descriptions can include characters which must be URL encoded for use in a querystring.
Node.js
Python
Go
Java
You'll need to differentiate between internal server errors and invalid user
input. This sample service returns an Internal Server Error for all dot
command-line errors unless the error message contains the string syntax
, which
indicates a user input problem.
Generating a diagram
The core logic of diagram generation uses the dot command-line tool to process the graph description input parameter into a diagram in the PNG image format.
Node.js
Python
Go
Java
Designing a secure service
Any vulnerabilities in the dot
tool are potential vulnerabilities of
the web service. You can mitigate this by using up-to-date versions of the
graphviz
package through re-building the container image on a regular basis.
If you extend the current sample to accept user input as command-line parameters, you should protect against command-injection attacks. Some of the ways to prevent injection attacks include:
- Mapping inputs to a dictionary of supported parameters
- Validating inputs match a range of known-safe values, perhaps using regular expressions
- Escaping inputs to ensure shell syntax is not evaluated
You can further mitigate potential vulnerabilities by deploying the service with a service account that has not been granted any permissions to use Google Cloud services, rather than using the default account, which has commonly used permissions. For that reason, the steps in this tutorial create and use a new service account.
Shipping the code
To ship your code, you build with Cloud Build, and upload to Artifact Registry, and deploy to Cloud Run:
Create an Artifact Registry:
gcloud artifacts repositories create REPOSITORY \ --repository-format docker \ --location REGION
Replace:
- REPOSITORY with a unique name for the repository. For each repository location in a project, repository names must be unique.
- REGION with the Google Cloud region to be used for the Artifact Registry repository.
Run the following command to build your container and publish on Artifact Registry.
Node.js
gcloud builds submit --tag REGION-docker.pkg.dev/PROJECT_ID/REPOSITORY/graphviz
Where PROJECT_ID is your Google Cloud project ID, and
graphviz
is the name you want to give your service.Upon success, you will see a SUCCESS message containing the ID, creation time, and image name. The image is stored in Artifact Registry and can be re-used if desired.
Python
gcloud builds submit --tag REGION-docker.pkg.dev/PROJECT_ID/REPOSITORY/graphviz
Where PROJECT_ID is your Google Cloud project ID, and
graphviz
is the name you want to give your service.Upon success, you will see a SUCCESS message containing the ID, creation time, and image name. The image is stored in Artifact Registry and can be reused if desired.
Go
gcloud builds submit --tag REGION-docker.pkg.dev/PROJECT_ID/REPOSITORY/graphviz
Where PROJECT_ID is your Google Cloud project ID, and
graphviz
is the name you want to give your service.Upon success, you will see a SUCCESS message containing the ID, creation time, and image name. The image is stored in Artifact Registry and can be reused if desired.
Java
This sample uses Jib to build Docker images using common Java tools. Jib optimizes container builds without the need for a Dockerfile or having Docker installed. Learn more about building Java containers with Jib.Using the Dockerfile, configure and build a base image with the system packages installed to override Jib's default base image:
gcloud builds submit --tag REGION-docker.pkg.dev/PROJECT_ID/REPOSITORY/graphviz-base
Where PROJECT_ID is your Google Cloud project ID.
Use the gcloud credential helper to authorize Docker to push to your Artifact Registry.
gcloud auth configure-docker
Build your final container with Jib and publish on Artifact Registry:
mvn compile jib:build \ -Dimage=REGION-docker.pkg.dev/PROJECT_ID/REPOSITORY/graphviz \ -Djib.from.image=REGION-docker.pkg.dev/PROJECT_ID/REPOSITORY/graphviz-base
Where PROJECT_ID is your Google Cloud project ID.
Deploy using the following:
gcloud
- Create a new service account. Your code, including any system packages
it uses, can use only those
Google Cloud services that have been granted to this service account.
gcloud iam service-accounts create SA_NAME
Where SA_NAME is a name you give this service account. If there is an error or a vulnerability in your code, your code will not be able to access any of your other Google Cloud project resources. - Deploy the code, specifying the service account.
gcloud run deploy graphviz-web --service-account SA_NAME@PROJECT_ID.iam.gserviceaccount.com --image REGION-docker.pkg.dev/PROJECT_ID/REPOSITORY/graphviz
Where PROJECT_ID is your Google Cloud project ID, SA_NAME is the name of the service account you created, andgraphviz
is the name of the container from above andgraphviz-web
is the name of the service. RespondY
to the "allow unauthenticated" prompt. See Managing access for more details on IAM-based authentication. - Wait for the deployment to finish. This can take about half a minute. On success, the command line displays the service URL.
Terraform
To learn how to apply or remove a Terraform configuration, see Basic Terraform commands.
The following Terraform code creates a Cloud Run service.
Replace IMAGE_URL with a reference to the container image, for example,
us-docker.pkg.dev/cloudrun/container/hello:latest
. If you use Artifact Registry, the repository REPO_NAME must already be created. The URL has the shapeLOCATION-docker.pkg.dev/PROJECT_ID/REPO_NAME/PATH:TAG
.The following Terraform code makes your Cloud Run service public.
- Create a new service account. Your code, including any system packages
it uses, can use only those
Google Cloud services that have been granted to this service account.
If you want to deploy a code update to the service, repeat the previous steps. Each deployment to a service creates a new revision and automatically starts serving traffic when ready.
Try it out
Try out your service by sending HTTP POST
requests with DOT syntax
descriptions in the request payload.
Send an HTTP request to your service.
Copy the URL into your browser URL bar and update
[SERVICE_DOMAIN]
:https://SERVICE_DOMAIN/diagram.png?dot=digraph Run { rankdir=LR Code -> Build -> Deploy -> Run }
You can embed the diagram in a web page:
<img src="https://SERVICE_DOMAIN/diagram.png?dot=digraph Run { rankdir=LR Code -> Build -> Deploy -> Run }" />
Open the resulting
diagram.png
file in any application that supportsPNG
files, such as Chrome.It should look like this:
You can explore a small collection of ready-made diagram descriptions.
- Copy the contents of the selected
.dot
file Send an HTTP request to your service.
Copy the URL into your browser URL bar
https://SERVICE_DOMAIN/diagram.png?dot=SELECTED DOTFILE CONTENTS
Clean up
If you created a new project for this tutorial, delete the project. If you used an existing project and wish to keep it without the changes added in this tutorial, delete resources created for the tutorial.
Deleting the project
The easiest way to eliminate billing is to delete the project that you created for the tutorial.
To delete the project:
- In the Google Cloud console, go to the Manage resources page.
- In the project list, select the project that you want to delete, and then click Delete.
- In the dialog, type the project ID, and then click Shut down to delete the project.
Deleting tutorial resources
Delete the Cloud Run service you deployed in this tutorial:
gcloud run services delete SERVICE-NAME
Where SERVICE-NAME is your chosen service name.
You can also delete Cloud Run services from the Google Cloud console.
Remove the gcloud default region configuration you added during tutorial setup:
gcloud config unset run/region
Remove the project configuration:
gcloud config unset project
Delete other Google Cloud resources created in this tutorial:
Delete the container image named
REGION-docker.pkg.dev/PROJECT_ID/REPOSITORY/graphviz
from Artifact Registry.Delete the service account SA_NAME.
gcloud iam service-accounts delete SA_NAME@PROJECT_ID.iam.gserviceaccount.com
What's next
- Experiment with your graphviz app:
- Add support for other graphviz utilities which apply different algorithms to diagram generation.
- Save diagrams to Cloud Storage. Do you want to save the image or the DOT syntax?
- Implement content abuse protection with Cloud Natural Language API.
- See another example of a system package in the Image Processing with Cloud Run tutorial.
- Explore reference architectures, diagrams, and best practices about Google Cloud. Take a look at our Cloud Architecture Center.