# Google Cloud

## Pre-requisites

This tutorial assumes that you have a Billing Account for your Google Cloud Projects in place. In the event this is not the case please follow the steps in [this tutorial](https://cloud.google.com/billing/docs/how-to/manage-billing-account) before proceeding.

## Setting up BigQuery

Exivity will leverage on the GCP BigQuery service. This will enable the export of detailed Google Cloud billing data to a BigQuery dataset, giving Exivity the capability to query the billing data in a more granular manner than with the standard file export (which is going to be [deprecated](https://cloud.google.com/billing/docs/how-to/export-data-bigquery) by Google).

{% hint style="info" %}
Before proceeding further, make sure sure your user has the **Billing Account Administrator** and the **BigQuery User** roles associated
{% endhint %}

First and foremost, Exivity will create a dataset containing the billing table which will be periodically queried. Please follow these instructions:

1. Go to the [BigQuery ](https://console.cloud.google.com/bigquery)service page.
2. Select the project that will contain your dataset in the project drop down.
3. Click **CREATE DATASET**.
   1. Enter a **Dataset ID**
   2. Select **Data location** (region)
   3. Set **Default table expiration** to *Never*
   4. Set **Encryption** to *Google-managed key*
4. Finally, click **Create dataset**
5. Note the *Project*, *BigQueryProject* and *Table*, these parameters will be used by Exivity on a later stage.

Once you have the dataset created in BigQuery you need to enable Cloud Billing export to BigQuery:

1. Sign in to the [Cloud Billing Console](https://console.cloud.google.com/billing), select *Organization* and main *Billing Account*.
2. Go to the **Billling Export** tab.
3. Click **Edit Settings** to enable the export.
   1. Select the project where you previously created the BigQuery dataset.
   2. Select the specific dataset from the **Billing export dataset** list.
   3. Click **Save**.

## Creating Exivity Service Account

Exivity requires a GCP *Service Account* with the **BigQuery User** role asscociated in order to retrieve the billing data. Please follow [this manual](https://cloud.google.com/iam/docs/creating-managing-service-accounts) to create a Service Account, [this manual](https://cloud.google.com/iam/docs/creating-managing-service-account-keys) to associate a Private Key with the service account, and finally [this manual](https://cloud.google.com/iam/docs/granting-changing-revoking-access) to associate the role with the service account.

{% hint style="warning" %}
Make sure to write down the *Mail address / service account* and its associated *Private Key*, as these parameters will be required for the Exivity Data Extractor
{% endhint %}

## Configuring the Extractor

To create the Extractor in Exivity, browse to **Data Sources > Extractors** and click the *Create Extractor* button. This will try to connect to the Exivity Github account to obtain a list of available templates. For Google Cloud, please click *Google\_Cloud* from the list. Provide a name for the Extractor in the name field, and click the **Create** button.

Once you have created the Extractor, go to **Variables** tab and fill the parameters:

* **Hostname**:  Default endpoint for Google BigQuery with version
* **Private**: Provide the RSA private key PEM format 

{% hint style="danger" %}
**IMPORTANT** make sure to replace **\n** with **${NEWLINE}** in the **RSA Private key** using a text editor, before pasting the key in the Exivity Extractor field
{% endhint %}

* **Email**: Mail address / service account associated with the private key, obtained in the *Creating Exivity Service Account section.*
* **Project**: Main GCP Project name.
* **BigQuery project**: GCP BigQuery Billing Project, obtained in the *Setting up BigQuery section.*
* **BigQuery table**: GCP BigQuery Billing Table, obtained in the *Setting up BigQuery section.*

Finally, click on **Update**.

![Example of GCP Extractor Variables](https://3540922554-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-LHEKskLK6aXinV75Knl%2Fsync%2F425eff5c97c7578bca277e33278ab3e4353f8f56.png?generation=1616416803517971\&alt=media)

Once you have filled in all details, go to the **Run** tab to execute the Extractor for a single day:

![](https://3540922554-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-LHEKskLK6aXinV75Knl%2F-Lz1ckLhuu2xubIn-UpI%2F-Lz1fv-tCTdyxOhUHEcr%2Fimage.png?alt=media\&token=9a703a2f-d7d3-49f6-baed-96466c18a0c2)

The Extractor requires two parameters in *yyyMMdd* format:

* **from\_date** is the date for which you wish to start collecting consumption data.
* **to\_date** is the end date for which you wish to collect consumption data.

When you click the **Run Now** button, you should get a successful result.

## Configure a Transformer

Once you have successfully run your Google Cloud Extractor, you should be able to create a Transformer template via **Data Sources > Transformers** and click the **Create Transformer** button.

Select the Google Cloud Transformer that you just created, go to the **Run Tab** and run it for a single day as a test. Make sure that it is the same day as for which you extracted consumption data in the previous step.

![](https://3540922554-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-LHEKskLK6aXinV75Knl%2F-Lz1ckLhuu2xubIn-UpI%2F-Lz1gpMQbLnBGyUGcmIv%2Fimage.png?alt=media\&token=7b0a42ec-5b21-462f-9fb7-828705190cb1)

When you click the **Run Now** button, you should get a successful result.

## Create your Report

Once you have run both your Extractor and Transformer successfully create a Report Definition via the menu option **Report Definition** via the menu **Reports > Definitions**:

![](https://3540922554-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-LHEKskLK6aXinV75Knl%2F-Lz1ckLhuu2xubIn-UpI%2F-Lz1hS4CXZJAquvjKzyk%2Fimage.png?alt=media\&token=1efdf63a-48be-453d-a0a9-22b06d064cdc)

Select the column(s) by which you would like to break down the costs (you can start with only *project\_name* as a test). Once you have created the report, you should then click the **Prepare Report** button after first making sure you have selected a valid date selector shown when preparing the report.![](https://blobscdn.gitbook.com/v0/b/gitbook-28427.appspot.com/o/assets%2F-LHEKskLK6aXinV75Knl%2F-LMg6h46PYa2zRIM4aIw%2F-LMgS-sUs8uBd0jk5bFC%2FManual13.jpg?alt=media\&token=3fd1f372-60bc-48f3-a339-bbcc0f0d0086)

Once this is done you should be able to run any of **Accounts**, **Instances**, **Services** or **Invoices** report types located under the *Report* menu for the date range you prepared the report for.


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://olddocs.exivity.io/3.4.3/getting-started/tutorials/google-cloud.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.