Using system packages tutorial

Setting up gcloud defaults

To configure gcloud with defaults for your Cloud Run service:

1. Set your default project:

   gcloud config set project PROJECT_ID

   Replace PROJECT_ID with the name of the project you created for this tutorial.

2. Configure gcloud for your chosen region:

   gcloud config set run/region REGION

   Replace REGION with the supported Cloud Run region of your choice.

Retrieving the code sample

To retrieve the code sample for use:

1. 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.

2. 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.

1. Open the Dockerfile in an editor.

2. Look for a Dockerfile RUN statement. This statement allows running arbitrary shell commands to modify the environment. If the Dockerfile has multiple stages, identified by finding multiple FROM 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

   RUN apt-get update -y && apt-get install -y \
     graphviz \
     && apt-get clean

   Alpine

   Alpine requires a second package for font support.

   RUN apk --no-cache add graphviz ttf-ubuntu-font-family

   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 from node, you can find documentation and the parent Dockerfile on Docker Hub.

3. 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.

app.get('/diagram.png', (req, res) => {
  try {
    const image = createDiagram(req.query.dot);
    res.setHeader('Content-Type', 'image/png');
    res.setHeader('Content-Length', image.length);
    res.setHeader('Cache-Control', 'public, max-age=86400');
    res.send(image);
  } catch (err) {
    console.error(`error: ${err.message}`);
    const errDetails = (err.stderr || err.message).toString();
    if (errDetails.includes('syntax')) {
      res.status(400).send(`Bad Request: ${err.message}`);
    } else {
      res.status(500).send('Internal Server Error');
    }
  }
});

@app.route("/diagram.png", methods=["GET"])
def index():
    """Takes an HTTP GET request with query param dot and
    returns a png with the rendered DOT diagram in a HTTP response.
    """
    try:
        image = create_diagram(request.args.get("dot"))
        response = make_response(image)
        response.headers.set("Content-Type", "image/png")
        return response

    except Exception as e:
        print(f"error: {e}")

        # If no graphviz definition or bad graphviz def, return 400
        if "syntax" in str(e):
            return f"Bad Request: {e}", 400

        return "Internal Server Error", 500

// diagramHandler renders a diagram using HTTP request parameters and the dot command.
func diagramHandler(w http.ResponseWriter, r *http.Request) {
	if r.Method != http.MethodGet {
		log.Printf("method not allowed: %s", r.Method)
		http.Error(w, fmt.Sprintf("HTTP Method %s Not Allowed", r.Method), http.StatusMethodNotAllowed)
		return
	}

	q := r.URL.Query()
	dot := q.Get("dot")
	if dot == "" {
		log.Print("no graphviz definition provided")
		http.Error(w, "Bad Request", http.StatusBadRequest)
		return
	}

	// Cache header must be set before writing a response.
	w.Header().Set("Cache-Control", "public, max-age=86400")

	input := strings.NewReader(dot)
	if err := createDiagram(w, input); err != nil {
		log.Printf("createDiagram: %v", err)
		// Do not cache error responses.
		w.Header().Del("Cache-Control")
		if strings.Contains(err.Error(), "syntax") {
			http.Error(w, "Bad Request: DOT syntax error", http.StatusBadRequest)
		} else {
			http.Error(w, "Internal Server Error", http.StatusInternalServerError)
		}
	}
}

get(
    "/diagram.png",
    (req, res) -> {
      InputStream image = null;
      try {
        String dot = req.queryParams("dot");
        image = createDiagram(dot);
        res.header("Content-Type", "image/png");
        res.header("Content-Length", Integer.toString(image.available()));
        res.header("Cache-Control", "public, max-age=86400");
      } catch (Exception e) {
        if (e.getMessage().contains("syntax")) {
          res.status(400);
          return String.format("Bad Request: %s", e.getMessage());
        } else {
          res.status(500);
          return "Internal Server Error";
        }
      }
      return image;
    });

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.

// Generate a diagram based on a graphviz DOT diagram description.
const createDiagram = dot => {
  if (!dot) {
    throw new Error('syntax: no graphviz definition provided');
  }

  // Adds a watermark to the dot graphic.
  const dotFlags = [
    '-Glabel="Made on Cloud Run"',
    '-Gfontsize=10',
    '-Glabeljust=right',
    '-Glabelloc=bottom',
    '-Gfontcolor=gray',
  ].join(' ');

  const image = execSync(`/usr/bin/dot ${dotFlags} -Tpng`, {
    input: dot,
  });
  return image;
};

def create_diagram(dot):
    """Generates a diagram based on a graphviz DOT diagram description.

    Args:
        dot: diagram description in graphviz DOT syntax

    Returns:
        A diagram in the PNG image format.
    """
    if not dot:
        raise Exception("syntax: no graphviz definition provided")

    dot_args = [  # These args add a watermark to the dot graphic.
        "-Glabel=Made on Cloud Run",
        "-Gfontsize=10",
        "-Glabeljust=right",
        "-Glabelloc=bottom",
        "-Gfontcolor=gray",
        "-Tpng",
    ]

    # Uses local `dot` binary from Graphviz:
    # https://graphviz.gitlab.io
    image = subprocess.run(
        ["dot"] + dot_args, input=dot.encode("utf-8"), stdout=subprocess.PIPE
    ).stdout

    if not image:
        raise Exception("syntax: bad graphviz definition provided")
    return image

// createDiagram generates a diagram image from the provided io.Reader written to the io.Writer.
func createDiagram(w io.Writer, r io.Reader) error {
	stderr := new(bytes.Buffer)
	args := []string{
		"-Glabel=Made on Cloud Run",
		"-Gfontsize=10",
		"-Glabeljust=right",
		"-Glabelloc=bottom",
		"-Gfontcolor=gray",
		"-Tpng",
	}
	cmd := exec.Command("/usr/bin/dot", args...)
	cmd.Stdin = r
	cmd.Stdout = w
	cmd.Stderr = stderr

	if err := cmd.Run(); err != nil {
		return fmt.Errorf("exec(%s) failed (%w): %s", cmd.Path, err, stderr.String())
	}

	return nil
}

// Generate a diagram based on a graphviz DOT diagram description.
public static InputStream createDiagram(String dot) {
  if (dot == null || dot.isEmpty()) {
    throw new NullPointerException("syntax: no graphviz definition provided");
  }
  // Adds a watermark to the dot graphic.
  List<String> args = new ArrayList<>();
  args.add("/usr/bin/dot");
  args.add("-Glabel=\"Made on Cloud Run\"");
  args.add("-Gfontsize=10");
  args.add("-Glabeljust=right");
  args.add("-Glabelloc=bottom");
  args.add("-Gfontcolor=gray");
  args.add("-Tpng");

  StringBuilder output = new StringBuilder();
  InputStream stdout = null;
  try {
    ProcessBuilder pb = new ProcessBuilder(args);
    Process process = pb.start();
    OutputStream stdin = process.getOutputStream();
    stdout = process.getInputStream();
    // The Graphviz dot program reads from stdin.
    Writer writer = new OutputStreamWriter(stdin, "UTF-8");
    writer.write(dot);
    writer.close();
    process.waitFor();
  } catch (Exception e) {
    System.out.println(e);
  }
  return stdout;
}

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:

1. 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.

2. 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.

   1. Using the Dockerfile, configure and build a base image with the system packages installed to override Jib's default base image:

      # Use the Official eclipse-temurin image for a lean production stage of our multi-stage build.
      # https://hub.docker.com/_/eclipse-temurin/
      FROM eclipse-temurin:17.0.12_7-jre
      
      RUN apt-get update -y && apt-get install -y \
        graphviz \
        && apt-get clean

      gcloud builds submit --tag REGION-docker.pkg.dev/PROJECT_ID/REPOSITORY/graphviz-base

      Where PROJECT_ID is your Google Cloud project ID.

   2. Use the gcloud credential helper to authorize Docker to push to your Artifact Registry.

      gcloud auth configure-docker

   3. Build your final container with Jib and publish on Artifact Registry:

      <plugin>
        <groupId>com.google.cloud.tools</groupId>
        <artifactId>jib-maven-plugin</artifactId>
        <version>3.4.0</version>
        <configuration>
          <from>
            <image>gcr.io/PROJECT_ID/graphviz-base</image>
          </from>
          <to>
            <image>gcr.io/PROJECT_ID/graphviz</image>
          </to>
        </configuration>
      </plugin>

      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.

3. Deploy using the following:

   gcloud

   1. 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.
   2. 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, and graphviz is the name of the container from above and graphviz-web is the name of the service. Respond Y to the "allow unauthenticated" prompt. See Managing access for more details on IAM-based authentication.
   3. 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.

   resource "google_service_account" "graphviz" {
     account_id   = "graphviz"
     display_name = "GraphViz Tutorial Service Account"
   }
   
   resource "google_cloud_run_v2_service" "default" {
     name     = "graphviz-example"
     location = "us-central1"
   
     deletion_protection = false # set to "true" in production
   
     template {
       containers {
         # Replace with the URL of your graphviz image
         #   gcr.io/<YOUR_GCP_PROJECT_ID>/graphviz
         image = "us-docker.pkg.dev/cloudrun/container/hello"
       }
   
       service_account = google_service_account.graphviz.email
     }
   }

   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 shape LOCATION-docker.pkg.dev/PROJECT_ID/REPO_NAME/PATH:TAG .

   The following Terraform code makes your Cloud Run service public.

   # Make Cloud Run service publicly accessible
   resource "google_cloud_run_service_iam_member" "allow_unauthenticated" {
     service  = google_cloud_run_v2_service.default.name
     location = google_cloud_run_v2_service.default.location
     role     = "roles/run.invoker"
     member   = "allUsers"
   }

4. 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.

1. 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 }" />

2. Open the resulting diagram.png file in any application that supports PNG files, such as Chrome.

   It should look like this:

   

You can explore a small collection of ready-made diagram descriptions.

1. Copy the contents of the selected .dot file

2. Send an HTTP request to your service.

   Copy the URL into your browser URL bar

   https://SERVICE_DOMAIN/diagram.png?dot=SELECTED DOTFILE CONTENTS