Google Cloud Landing Zone Series – Part 4: Naming Conventions

Table of Contents:


Naming Conventions

In the last blog post, we talked a lot about resource hierarchies. Resource hierarchies help to group projects into a folder structure and help with issues like governance, automation, access control, billing and cost management and other things.

Advantages of naming conventions

Another important issue for building up a scalable landing zone are naming conventions. Naming conventions bring up advantages for your environment, let’s shortly name some of them:

Clarity and Readability: Good naming conventions help in clearly identifying resources, their purpose, and their relationships. This enhances readability and understanding for anyone who interacts with the cloud environment, from developers to system administrators.

Consistency: Consistent naming makes it easier to manage resources across your different teams and projects. It reduces confusion and helps in setting standard practices for operations within the cloud environment.

Automation and Tooling Compatibility: Automated tools and scripts often rely on naming patterns to select and manage resources. Consistent naming conventions ensure that these tools can function correctly and efficiently, whether they are used for monitoring, provisioning, or management.

Security: Proper naming can aid in implementing security policies. For instance, names can indicate the sensitivity level of data stored in a resource, or whether a resource is in a production or development environment, helping in applying appropriate security controls.

Cost Management: Naming conventions can also aid in tracking and managing costs. By identifying resources clearly, organizations can monitor usage and costs more effectively, making it easier to optimize resource allocation and reduce wastage.

Examples of naming conventions

So there are clearly a lot of advantages of naming conventions, so let’s continue with that and provide some examples.

For projects you might want to embed some information within the project name. Common components might be:

  • The stage of the project, e.g. Test, QA or Prod
  • If you have a CMDB in your place, you might reuse some kind of service numbers or project numbers and embed them in the project name.
  • The purpose of the project, for example a network project, a project for storing audit information

In Google, it is also important to remember that project ids cannot be changed, but project names can be changed. So if a project number or something changes over time, changing the project name is possible, but changing the project id is not. That’s why it might be better to use a surrogate as the project id, and a descriptive name for the project name.

Another thing to consider is that resource ids might not be re-used – at least not immediately. For example, if you delete a project it will be first be in the trash for something like a month until it is eventually deleted. In this time, the name for the resource cannot be resued. Luckily, you can easily deal with the problem by appending some random suffix on your ressource.

Another important thing is to clearly adhere to the naming standard – even in edge cases. For example, if you separate your components in your project name by means of “-“, you can run into problems if your descriptive name also use “-“.  Here is a small example:

Good: p-1234557-landingzone-ab123

Bad: p-1234566-landing-zone-ab123

The latter example might break your automation processes later, because you cannot clearly figure out the purpose of the project anymore.

Also important, while naming conventions are important, you do not need naming conventions for everything. Cloud providers and Google is no exception here have hundreds of services and components and if you come up with a naming convention, you would only be busy with setting up and enforcing naming conventions.


Beside naming conventions, cloud providers also allow the use of labels to store metadata information. Here are some examples of labels you might encounter or use in a cloud setting:



Project or Application


Owner or Team


Cost Center or Budget


Automation Support

To demonstrate the how you can use automation for working with projects, let’s take a look at a Python snippet. In Google, you use the Resource Manager API for working with projects. Luckily, like for all APIs, there is a comprehensive library to be imported:

from import resource_manager
def list_projects():
    client = resource_manager.Client()
    projects = client.list_projects()
    project_ids = [project.project_id for project in projects]
    # For debugging or direct response, convert list to string
    return str(project_ids)

As you can see, automation in the Google Cloud is really easy. For many use cases, the best way to deploy such scripts, is to use a Cloud Function and trigger it manually, with a schedule or based on some event.


Dr. Guido Söldner


Guido Söldner ist Geschäftsführer und Principal Consultant bei Söldner Consult. Sein Themenfeld umfasst Cloud Infrastruktur, Automatisierung und DevOps, Kubernetes, Machine Learning und Enterprise Programmierung mit Spring.