ClickHouse/clickhouse-docs-embeddings huggingface dataset:
GCP Marketplace Committed Contract

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Get started with ClickHouse Cloud on the [GCP Marketplace](https://console.cloud.google.com/marketplace) via a committed contract. A committed contract, also known as a a Private Offer, allows customers to commit to spending a certain amount on ClickHouse Cloud over a period of time.

## Prerequisites[​](#prerequisites "Direct link to Prerequisites")

- A Private Offer from ClickHouse based on specific contract terms.

## Steps to sign up[​](#steps-to-sign-up "Direct link to Steps to sign up")

1. You should have received an email with a link to review and accept your private offer.

  
  

2. Click on the **Review Offer** link in the email. This should take you to your GCP Marketplace page with the private offer details.

  
  
  

3. Review the private offer details and if everything is correct, click **Accept**.

  
  

4. Click on **Go to product page**.

  
  

5. Click on **Manage on provider**.

  
  

It is critical to redirect to ClickHouse Cloud at this point and sign up or sign in. Without completing this step, we won't be able to link your GCP Marketplace subscription to ClickHouse Cloud.

  
  

6. Once you redirect to ClickHouse Cloud, you can either login with an existing account, or register with a new account.

  
  

If you're a new ClickHouse Cloud user, click **Register** at the bottom of the page. You will be prompted to create a new user and verify the email. After verifying your email, you can leave the ClickHouse Cloud login page and login using the new username at the <https://console.clickhouse.cloud>.

  
  

Note that if you're a new user, you will also need to provide some basic information about your business. See the screenshots below.

  
  
  

If you're an existing ClickHouse Cloud user, simply log in using your credentials.

7. After successfully logging in, a new ClickHouse Cloud organization will be created. This organization will be connected to your GCP billing account and all usage will be billed via your GCP account.
8. Once you login, you can confirm that your billing is in fact tied to the GCP Marketplace and start setting up your ClickHouse Cloud resources.

  
  
  

9. You should receive an email confirming the sign up:

  
  
  
  

If you run into any issues, please don't hesitate to contact [our support team](https://clickhouse.com/support/program).

- [Prerequisites](#prerequisites)- [Steps to sign up](#steps-to-sign-up)

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GCP Marketplace PAYG

[Edit this page](https://github.com/ClickHouse/clickhouse-docs/blob/main/docs/cloud/reference/03_billing/02_marketplace/gcp-marketplace-payg.md)

Get started with ClickHouse Cloud on the [GCP Marketplace](https://console.cloud.google.com/marketplace) via a PAYG (Pay-as-you-go) Public Offer.

## Prerequisites[​](#prerequisites "Direct link to Prerequisites")

- A GCP project that is enabled with purchasing rights by your billing administrator.
- To subscribe to ClickHouse Cloud on the GCP Marketplace, you must be logged in with an account that has purchasing rights and choose the appropriate project.

## Steps to sign up[​](#steps-to-sign-up "Direct link to Steps to sign up")

1. Go to the [GCP Marketplace](https://cloud.google.com/marketplace) and search for ClickHouse Cloud. Make sure you have the correct project chosen.

2. Click on the [listing](https://console.cloud.google.com/marketplace/product/clickhouse-public/clickhouse-cloud) and then on **Subscribe**.

3. On the next screen, configure the subscription:

- The plan will default to "ClickHouse Cloud"
- Subscription time frame is "Monthly"
- Choose the appropriate billing account
- Accept the terms and click **Subscribe**

  
  

4. Once you click **Subscribe**, you will see a modal **Sign up with ClickHouse**.

  
  

5. Note that at this point, the setup isn't complete yet. You will need to redirect to ClickHouse Cloud by clicking on **Set up your account** and signing up on ClickHouse Cloud.
6. Once you redirect to ClickHouse Cloud, you can either login with an existing account, or register with a new account. This step is very important so we can bind your ClickHouse Cloud organization to the GCP Marketplace billing.

  
  

If you're a new ClickHouse Cloud user, click **Register** at the bottom of the page. You will be prompted to create a new user and verify the email. After verifying your email, you can leave the ClickHouse Cloud login page and login using the new username at the <https://console.clickhouse.cloud>.

  
  

Note that if you're a new user, you will also need to provide some basic information about your business. See the screenshots below.

  
  
  

If you're an existing ClickHouse Cloud user, simply log in using your credentials.

7. After successfully logging in, a new ClickHouse Cloud organization will be created. This organization will be connected to your GCP billing account and all usage will be billed via your GCP account.
8. Once you login, you can confirm that your billing is in fact tied to the GCP Marketplace and start setting up your ClickHouse Cloud resources.

  
  
  

9. You should receive an email confirming the sign up:

  
  
  
  

If you run into any issues, please don't hesitate to contact [our support team](https://clickhouse.com/support/program).

- [Prerequisites](#prerequisites)- [Steps to sign up](#steps-to-sign-up)

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Accessing S3 data securely

## Advanced action control[​](#advanced-action-control "Direct link to Advanced action control")

For stricter access control, it's possible to restrict the bucket policy to only accept requests that originate from ClickHouse Cloud's VPC endpoints using the [`aws:SourceVpce` condition](https://docs.aws.amazon.com/AmazonS3/latest/userguide/example-bucket-policies-vpc-endpoint.html#example-bucket-policies-restrict-accesss-vpc-endpoint). To obtain the VPC endpoints for your ClickHouse Cloud region, open a terminal and run:

```
# Replace <your-region> with your ClickHouse Cloud region
curl -s https://api.clickhouse.cloud/static-ips.json | jq -r '.aws[] | select(.region == "<your-region>") | .s3_endpoints[]'
```

Then, add a deny rule to the IAM policy with the returned endpoints:

```
{
        "Version": "2012-10-17",
        "Statement": [
            {
                "Sid": "VisualEditor0",
                "Effect": "Allow",
                "Action": [
                    "s3:List*",
                    "s3:Get*"
                ],
                "Resource": [
                    "arn:aws:s3:::{BUCKET_NAME}",
                    "arn:aws:s3:::{BUCKET_NAME}/*"
                ]
            },
            {
                "Sid": "VisualEditor3",
                "Effect": "Deny",
                "Action": [
                    "s3:GetObject"
                ],
                "Resource": "*",
                "Condition": {
                    "StringNotEquals": {
                        "aws:SourceVpce": [
                            "{ClickHouse VPC ID from your S3 region}",
                            "{ClickHouse VPC ID from your S3 region}",
                            "{ClickHouse VPC ID from your S3 region}"
                        ]
                    }
                }
            }
        ]
}
```

For more details on accessing endpoints for ClickHouse Cloud services, see [Cloud IP Addresses](/docs/manage/data-sources/cloud-endpoints-api).

- [Obtain the IAM role ARN of your ClickHouse service](#obtaining-the-clickhouse-service-iam-role-arn)- [Set up IAM assume role](#setting-up-iam-assume-role)
    - [Deploying with CloudFormation stack](#option-1-deploying-with-cloudformation-stack)- [Manually create IAM role](#option-2-manually-create-iam-role)- [Access your S3 bucket with the ClickHouseAccess role](#access-your-s3-bucket-with-the-clickhouseaccess-role)- [Advanced action control](#advanced-action-control)

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Query API endpoints

[Edit this page](https://github.com/ClickHouse/clickhouse-docs/blob/main/docs/cloud/features/03_sql_console_features/03_query-endpoints.md)

Building interactive data-driven applications requires not only a fast database, well-structured data, and optimized queries.
Your front-end and microservices also need an easy way to consume the data returned by those queries, preferably via well-structured APIs.

The **Query API Endpoints** feature allows you to create an API endpoint directly from any saved SQL query in the ClickHouse Cloud console.
You'll be able to access API endpoints via HTTP to execute your saved queries without needing to connect to your ClickHouse Cloud service via a native driver.

## IP Access Control[​](#ip-access-control "Direct link to IP Access Control")

Query API endpoints respect API key-level IP whitelisting. Similar to the SQL Console, Query API endpoints proxy requests from within ClickHouse's infrastructure, so service-level IP whitelist settings don't apply.

To restrict which clients can call your Query API endpoints:

Open API key settings

#### Open API key settings[​](#open-settings "Direct link to Open API key settings")

1. Go to ClickHouse Cloud Console → **Organization** → **API Keys**

2. Click **Edit** next to the API key used for Query API endpoints

Add allowed IP addresses

#### Add allowed IP addresses[​](#add-ips "Direct link to Add allowed IP addresses")

1. In the **Allow access to this API Key** section, select **Specific locations**
2. Enter IP addresses or CIDR ranges (e.g., `203.0.113.1` or `203.0.113.0/24`)
3. Add multiple entries as needed

Creating Query API endpoints requires an Admin Console Role and an API key with appropriate permissions.

Guide

See the [Query API endpoints guide](/docs/cloud/get-started/query-endpoints) for instructions on how to set up
query API endpoints in a few easy steps

- [IP Access Control](#ip-access-control)

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title_wip

[Edit this page](https://github.com/ClickHouse/clickhouse-docs/blob/main/docs/cloud/onboard/index.md)

New to ClickHouse Cloud and not sure where to begin? In this section of the docs,
we'll walk you through everything you need to get up and running quickly. We've
arranged this getting started section into three subsections to help guide
you through each step of the process as you explore ClickHouse Cloud.

Discover ClickHouse Cloud

## Discover ClickHouse Cloud[​](#discover-clickhouse-cloud "Direct link to Discover ClickHouse Cloud")

- [Learn](/docs/cloud/overview) about what ClickHouse Cloud is, and how it differs from the open-source version
- [Discover](/docs/cloud/get-started/cloud/use-cases/overview) the main use-cases of ClickHouse Cloud

Get set up with ClickHouse Cloud

## Get set up with ClickHouse Cloud[​](#get-set-up-with-clickhouse-cloud "Direct link to Get set up with ClickHouse Cloud")

Now that you know what ClickHouse Cloud is, we'll walk you through the process
of getting your data into ClickHouse Cloud, show you the main features available
and point you towards some general best practices you should know.

Topics include:

- [Migration guides](/docs/integrations/migration/overview) from various platforms

Tune your ClickHouse Cloud deployment

## Tune your ClickHouse Cloud deployment[​](#evaluate-clickhouse-cloud "Direct link to Tune your ClickHouse Cloud deployment")

Now that your data is in ClickHouse Cloud, we'll walk you through some more advanced
topics to help you get the most out of your ClickHouse Cloud experience and explore
what the platform has to offer.

Topics include:

- [Query performance and optimization](/docs/cloud/get-started/cloud/resource-tour#query-optimization)
- [Monitoring](/docs/cloud/get-started/cloud/resource-tour#monitoring)
- [Security considerations](/docs/cloud/get-started/cloud/resource-tour#security)
- [Troubleshooting tips](/docs/troubleshooting)

- [Discover ClickHouse Cloud](#discover-clickhouse-cloud)- [Get set up with ClickHouse Cloud](#get-set-up-with-clickhouse-cloud)- [Tune your ClickHouse Cloud deployment](#evaluate-clickhouse-cloud)

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Machine learning

On the other hand, it could be managed in the data layer itself. ClickHouse [User Defined Functions (UDFs)](/docs/sql-reference/functions/udf), give users the ability to invoke a model directly from ClickHouse at insert or query time.
This provides the ability to pass incoming data to a model, receive the output, and store these results along with the ingested data automatically - all without having to spin up other processes or jobs.
This also provides a single interface, SQL, by which to manage this step.

### Vector store[​](#vector-store "Direct link to Vector store")

A vector store is a specific type of database that is optimized for storing and retrieving vectors, typically embeddings of a piece of data (such as text or images) that numerically capture their underlying meaning.
Vectors are at the core of today’s generative AI wave and are used in countless applications.

The primary operation in a vector database is a “similarity search” to find the vectors that are “closest” to one another according to a mathematical measure.
Vector databases have become popular because they employ specific tactics intended to make this examination - vector comparisons - as fast as possible.
These techniques generally mean that they approximate the vector comparisons, instead of comparing the input vector to every vector stored.

The issue with this new class of tools is that many general-purpose databases, including ClickHouse, provide vector support out-of-the-box, and also often have implementations of those approximate approaches built-in.
ClickHouse, in particular, is designed for high-performance large-scale analytics - allowing you to perform non-approximate vector comparisons very effectively.
This means that you can achieve precise results, rather than having to rely on approximations, all without sacrificing speed.

### Observability[​](#observability "Direct link to Observability")

Once your machine learning application is live, it will generate data, including logs and tracing data, that offer valuable insights into model behavior, performance, and potential areas for improvement.

SQL-based observability is another key use case for ClickHouse, where ClickHouse has been found to be 10-100x more cost-effective than alternatives.
In fact, many observability products are themselves built with ClickHouse under-the-hood.
With best-in-class ingestion rates and compression ratios, ClickHouse provides cost-efficiency and blazing speed to power machine learning observability at any scale.

- [The machine learning data layer](#machine-learning-data-layer)
  - [Data exploration](#data-exploration)- [Data preparation and feature extraction](#data-preparation-and-feature-extraction)- [Training and evaluation](#training-and-evaluation)- [Inference](#inference)- [Vector store](#vector-store)- [Observability](#observability)

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From the database perspective, we can expect a potentially unlimited number of
AI agents, concurrently running a large number of queries on behalf of users,
or in autonomy, to perform investigations, refine iterative research and insights,
and execute tasks.

Over the years, real-time databases have had the time to adapt to human
interactive users, directly connected to the system or via a middleware
application layer. Classic personas examples include database administrators,
business analysts, data scientists, or software developers building applications
on top of the database. The industry has progressively learned their usage
patterns and requirements and organically, provided the interfaces, the operators,
the UIs, the formats, the clients, and the performance to satisfy their various
use cases.

The question now becomes, are we ready to accommodate the AI agent's workloads?
What specific features do we need to re-think or create from scratch for these
usage patterns?

ClickHouse is rapidly providing answers to some of these questions through a host
of features aimed at providing a feature-complete AI experience.

## ClickHouse.ai[​](#clickhouse-ai "Direct link to ClickHouse.ai")

For more information about features coming soon to ClickHouse Cloud, see [ClickHouse.ai](https://clickhouse.com/clickhouse-ai/).

- [Agent-facing analytics concepts](#agent-facing-analytics)
  - [What are "agents"?](#agents)- [AI agents superpowers: “Tools”](#tools)- [Reasoning models](#reasoning-models)- [Real-time analytics for AI agents](#real-time-analytics-for-ai-agents)- [AI agents as an emerging user persona](#ai-agents-as-an-emerging-user-persona)- [ClickHouse.ai](#clickhouse-ai)

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Query Insights

[Edit this page](https://github.com/ClickHouse/clickhouse-docs/blob/main/docs/cloud/features/03_sql_console_features/02_query-insights.md)

The **Query Insights** feature makes ClickHouse's built-in query log easier to use through visualizations and tables. ClickHouse's `system.query_log` table is a key source of information for query optimization, debugging, and monitoring overall cluster health and performance.

## Query overview[​](#query-overview "Direct link to Query overview")

After selecting a service, the **Monitoring** navigation item in the left sidebar should expand to reveal a new **Query insights** sub-item. Clicking on this option opens the new Query insights page:

## Top-level metrics[​](#top-level-metrics "Direct link to Top-level metrics")

The stat boxes at the top represent some basic top-level query metrics over the selected period of time. Beneath it, we've exposed three time-series charts representing query volume, latency, and error rate broken down by query kind (select, insert, other) over a selected time window. The latency chart can be further adjusted to display p50, p90, and p99 latencies:

## Recent queries[​](#recent-queries "Direct link to Recent queries")

Beneath the top-level metrics, a table displays query log entries (grouped by normalized query hash and user) over the selected time window:

Recent queries can be filtered and sorted by any available field. The table can also be configured to display or hide additional fields such as tables, p90, and p99 latencies.

## Query drill-down[​](#query-drill-down "Direct link to Query drill-down")

Selecting a query from the recent queries table will open a flyout containing metrics and information specific to the selected query:

As we can see from the flyout, this particular query has been run more than 3000 times in the last 24 hours. All metrics in the **Query info** tab are aggregated metrics, but we can also view metrics from individual runs by selecting the **Query history** tab:

  

From this pane, the `Settings` and `Profile Events` items for each query run can be expanded to reveal additional information.

- [Query overview](#query-overview)- [Top-level metrics](#top-level-metrics)- [Recent queries](#recent-queries)- [Query drill-down](#query-drill-down)

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title_wip

[Edit this page](https://github.com/ClickHouse/clickhouse-docs/blob/main/docs/cloud/guides/data_sources/index.md)

## Cloud integrations[​](#cloud-integrations "Direct link to Cloud integrations")

This section contains guides and references for integrating ClickHouse Cloud with external data sources that require additional configuration.

|  |  |  |  |  |  |  |  |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Page Description|  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | | [Cloud IP addresses](/docs/manage/data-sources/cloud-endpoints-api) Networking information needed for some table functions and connections|  |  |  |  | | --- | --- | --- | --- | | [Accessing S3 data securely](/docs/cloud/data-sources/secure-s3) Access external data sources in AWS S3 using role based access|  |  | | --- | --- | | [Accessing GCS data securely](/docs/cloud/data-sources/secure-gcs) Access external data sources in GCS securely using HMAC keys | | | | | | | |

## Additional connections for external data sources[​](#additional-connections-for-external-data-sources "Direct link to Additional connections for external data sources")

### ClickPipes for data ingestion[​](#clickpipes-for-data-ingestion "Direct link to ClickPipes for data ingestion")

ClickPipes allow customers to easily integrate streaming data from a number of sources. Refer to [ClickPipes](/docs/integrations/clickpipes) in our Integrations documentation for additional information.

### Table functions as external data sources[​](#table-functions-as-external-data-sources "Direct link to Table functions as external data sources")

ClickHouse supports a number of table functions to access external data sources. For more information, refer to [table functions](/docs/sql-reference/table-functions) in the SQL reference section.

- [Cloud integrations](#cloud-integrations)- [Additional connections for external data sources](#additional-connections-for-external-data-sources)
    - [ClickPipes for data ingestion](#clickpipes-for-data-ingestion)- [Table functions as external data sources](#table-functions-as-external-data-sources)

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ClickHouse Cloud Production Readiness Guide

### Production support integration[​](#production-support "Direct link to Production support integration")

Understand your current support tier's SLA expectations and escalation procedures. Create internal runbooks defining when to engage ClickHouse support and integrate these procedures with your existing incident management processes.

Learn more about [ClickHouse Cloud backup and recovery](/docs/cloud/manage/backups/overview) and [support services](/docs/about-us/support).

## Next steps[​](#next-steps "Direct link to Next steps")

After implementing the integrations and procedures in this guide, visit the [Cloud resource tour](/docs/cloud/get-started/cloud/resource-tour) for guides on [monitoring](/docs/cloud/get-started/cloud/resource-tour#monitoring), [security](/docs/cloud/get-started/cloud/resource-tour#security), and [cost optimization](/docs/cloud/get-started/cloud/resource-tour#cost-optimization).

When current [service tier limitations](/docs/cloud/manage/cloud-tiers) impact your production operations, consider upgrade paths for enhanced capabilities such as [private networking](/docs/cloud/security/connectivity/private-networking), [TDE/CMEK](/docs/cloud/security/cmek) (Transparent Data Encryption with Customer-Managed Encryption Keys), or [advanced backup options](/docs/cloud/manage/backups/configurable-backups).

- [Introduction](#introduction)- [Environment strategy](#environment-strategy)- [Private networking](#private-networking)- [Enterprise authentication and user management](#enterprise-authentication)
        - [SSO and social authentication](#sso-authentication)- [Access control design](#access-control-design)- [User lifecycle management limitations](#user-lifecycle-management)- [Infrastructure as code and automation](#infrastructure-as-code)
          - [Terraform Provider](#terraform-provider)- [Cloud API integration](#cloud-api-integration)- [Monitoring and operational integration](#monitoring-integration)
            - [Built-in monitoring](#built-in-monitoring)- [Production alerting setup](#production-alerting)- [Business continuity and support integration](#business-continuity)
              - [Backup strategy assessment](#backup-strategy)- [Validate and test recovery procedures](#validate-test-recovery)- [Disaster recovery planning](#disaster-recovery-planning)- [Production support integration](#production-support)- [Next steps](#next-steps)

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