GCP Onboarding

Learn how to integrate your GCP account with North.Cloud

Based on your billing account's data volume, Google Cloud can take up to 5 days to fully migrate your data during billing export. If possible, start the billing export before you start onboarding. This speeds up the process. You can resume onboarding at any time. More from the official GCP documentation.

Prerequisites:

• If you do not have an account, we recommend that you create a free account first at app.north.cloud
• Make sure you have the minimum role BigQuery Data Owner within the billing account. This role lets you create and share billing datasets.

1

Go to the Billing Export

Select the billing account you want to add and click Edit Settings.

2

Enable billing export for all

You will repeat the step 3 below for all billing reports.

• Standard usage cost
• Detailed usage cost
• Pricing

3

Select a project and billing dataset

Selecting a project does not prevent other projects under your billing account from being included in your dataset. The project only serves as a storage location for the data. You can create a new project and dataset, or use an existing one.

Choose the project where your data will be hosted. All projects under your billing account remain available. You can set the dataset name to any convention you prefer. You can also use our recommended name, north_billing_dataset.

This dataset holds your standard usage cost, detailed usage cost, and pricing exports. Note the name. You need it in the last two steps.

4

Set up the CUD export

The Committed Use Discount (CUD) metadata export gives North.Cloud the data it needs to calculate commitment coverage and utilization.

• On the same Billing Export settings page from the previous step, enable Enable committed use discounts (CUD) metadata export.
• Use the same project as before.

Google Cloud writes the CUD export into its own dataset. It does not write it into your billing dataset. We recommend that you name this dataset north_cud_dataset so it is easy to identify later. Note the name you choose. You need it in the last two steps.

5

Enable the recommender

When you enable the recommender, GCP sends you a permission request. This request is the Recommender service asking for access to your other GCP services. It needs that access to provide accurate recommendations.

If you see an error like BigQuery Data Transfer is not enabled for <project_id>, enable the BigQuery Data Transfer API for that project and try again. If it still fails, you may need to grant permission to the transfer service agent directly. See GCP's troubleshooting guide.

North.Cloud uses Google Cloud Platform (GCP) recommendations. We integrate them with our internal machine learning and AI services.

• Choose the same project and billing dataset used earlier.
• Configure the transfer. This sets how often recommendations can be generated. We generally recommend the following:

  • Name: north_config
  • Schedule option: Daily ( Day, 1 )
  • Start: 00:00
  • Destination settings: the dataset you created or selected earlier

6

Share your datasets with North.Cloud

North.Cloud reads your exports with a read-only principal. Share every dataset that holds an export. This means your billing dataset and your CUD dataset.

For each dataset:

1. Open the dataset in BigQuery. Select Sharing, then Permissions.
2. Select Add Principal. Paste the Principal ID shown during onboarding.
3. Assign both roles: BigQuery Data Viewer and BigQuery Metadata Viewer.
4. Save.

Then add your project ID and billing dataset name to North.Cloud.

A dataset that is not shared is the most common reason a table dropdown is empty in the next step. North.Cloud tells you when this happens, and it gives you the sharing steps in place.

7

Select the corresponding tables in North.Cloud

North.Cloud lists five billing exports. Each one has a table and a dataset.

Row in North.Cloud	GCP billing export
Billing Header	Standard usage cost
Billing Detail	Detailed usage cost
Pricing	Pricing
CUD	Committed use discounts (CUD) metadata
Recommender	Recommender export

For each row, select the table from the dropdown. The Dataset field beside it shows which dataset North.Cloud reads that table from.

Four of the rows read from your billing dataset. CUD is the exception, because Google Cloud writes that export into its own dataset. The CUD row defaults to north_cud_dataset. If you named your CUD dataset something else, type that name into the Dataset field. North.Cloud re-checks the dataset when you leave the field, then loads the tables it finds.

Select Use recommended to accept the table North.Cloud detected for one row. Select Use all recommended to accept every detected table at once.

Select a table for every row before you continue. See Troubleshooting below if a table you expect is missing.

If a dropdown has no options, North.Cloud shows a warning under that row. The warning states the reason and offers Check again. If North.Cloud cannot read the dataset, the warning also offers How to fix, which gives the sharing steps for that dataset. See Troubleshooting below for what each message means.

8

Start saving

Once North.Cloud completes your savings and data analysis, we will send you a confirmation email. You will then have access to all our AI-powered optimization features, the same tools that help leading companies achieve top 1% cloud efficiency.

Troubleshooting

A table dropdown is empty in North.Cloud

North.Cloud shows a warning under the row. The message tells you which of three things happened.

Message	What it means	What to do
Dataset not accessible	North.Cloud cannot read the dataset.	Select How to fix for the sharing steps. Grant both roles. Then select Check again.
No tables in dataset	North.Cloud read the dataset and found no tables.	Check the dataset name. If the export does not exist yet, create it in BigQuery.
Not checked yet	North.Cloud has not read this dataset.	Select Check again.

A new export can take a few hours to generate its first table. If the dataset is correct and shared, wait and select Check again.

BigQuery Data Transfer is not enabled for <project_id> when enabling the Recommender

Enable the BigQuery Data Transfer API for that project. If the error continues, you may need to grant permission to the transfer service agent directly. See GCP's authorization troubleshooting guide.

A cloud_pricing_export_* or CUD table is not showing up in the dropdown

If a table does not appear, the export is probably not enabled yet. Go back to the Billing Export settings page and enable it. A new export can take a few hours to write its first table.

If you already enabled the export, check that the row points at the correct dataset. Google Cloud writes the CUD export into its own dataset. Your pricing export stays in your billing dataset.