From 97466e3ee0eed962c1fa828e1a04c02634950d8a Mon Sep 17 00:00:00 2001 From: Rachel House Date: Fri, 20 Sep 2024 12:40:50 -0500 Subject: [PATCH] [DOCS] DSB-1116: Reorganize and update GX Cloud deployment and architecture patterns into GX Cloud overview (#10345) --- .../docs/application_integration_support.md | 16 +- docs/docusaurus/docs/cloud/_try_gx_cloud.md | 4 +- docs/docusaurus/docs/cloud/about_gx.md | 122 ---- ...rchitecture_and_deployment_diagrams.drawio | 634 ------------------ .../gx_cloud_architecture_components.png | Bin 56277 -> 0 bytes .../orchestrated_deployment.png | Bin 49275 -> 0 bytes .../org_hosted_deployment.png | Bin 116206 -> 0 bytes .../self_hosted_deployment.png | Bin 121064 -> 0 bytes .../cloud/connect/connect_databrickssql.md | 2 +- .../docs/cloud/connect/connect_postgresql.md | 2 +- .../docs/cloud/connect/connect_snowflake.md | 2 +- .../cloud/{ => deploy}/deploy_gx_agent.md | 53 +- .../docusaurus/docs/cloud/deploy/deploy_lp.md | 21 + .../agent_enabled_deployment.png | Bin 0 -> 47056 bytes .../deployment_diagrams.drawio | 208 ++++++ .../fully_hosted_deployment.png | Bin 0 -> 41654 bytes .../read_only_deployment.png | Bin 0 -> 48577 bytes .../docs/cloud/deploy/deployment_patterns.md | 44 ++ docs/docusaurus/docs/cloud/gx_cloud_lp.md | 7 +- .../docs/cloud/overview/gx_cloud_overview.md | 68 ++ .../overview_images/gx_cloud_architecture.png | Bin 0 -> 109906 bytes .../gx_cloud_overview_images.drawio | 255 +++++++ .../overview_images/gx_cloud_workflow.png | Bin 0 -> 32381 bytes .../gx_cloud_workflow_enhanced.png | Bin 0 -> 70447 bytes .../docs/cloud/users/manage_users.md | 10 + docs/docusaurus/docs/cloud/why_gx_cloud.mdx | 80 --- .../docs/core/introduction/introduction.mdx | 2 + docs/docusaurus/docs/gx_welcome.md | 10 +- .../data_quality_use_cases/missingness.md | 2 +- docs/docusaurus/docs/resources/get_support.md | 2 +- docs/docusaurus/docusaurus.config.js | 6 +- docs/docusaurus/sidebars.js | 43 +- docs/docusaurus/static/img/checklist_icon.svg | 38 ++ docs/docusaurus/static/img/database_icon.svg | 14 + docs/docusaurus/static/img/gear_icon.svg | 47 ++ .../static/img/magnify_data_icon.svg | 7 + docs/docusaurus/static/img/python_logo.svg | 19 + docs/docusaurus/static/img/table_icon.svg | 7 + 38 files changed, 815 insertions(+), 910 deletions(-) delete mode 100644 docs/docusaurus/docs/cloud/about_gx.md delete mode 100644 docs/docusaurus/docs/cloud/architecture_deployment_images/gx_cloud_architecture_and_deployment_diagrams.drawio delete mode 100644 docs/docusaurus/docs/cloud/architecture_deployment_images/gx_cloud_architecture_components.png delete mode 100644 docs/docusaurus/docs/cloud/architecture_deployment_images/orchestrated_deployment.png delete mode 100644 docs/docusaurus/docs/cloud/architecture_deployment_images/org_hosted_deployment.png delete mode 100644 docs/docusaurus/docs/cloud/architecture_deployment_images/self_hosted_deployment.png rename docs/docusaurus/docs/cloud/{ => deploy}/deploy_gx_agent.md (78%) create mode 100644 docs/docusaurus/docs/cloud/deploy/deploy_lp.md create mode 100644 docs/docusaurus/docs/cloud/deploy/deployment_images/agent_enabled_deployment.png create mode 100644 docs/docusaurus/docs/cloud/deploy/deployment_images/deployment_diagrams.drawio create mode 100644 docs/docusaurus/docs/cloud/deploy/deployment_images/fully_hosted_deployment.png create mode 100644 docs/docusaurus/docs/cloud/deploy/deployment_images/read_only_deployment.png create mode 100644 docs/docusaurus/docs/cloud/deploy/deployment_patterns.md create mode 100644 docs/docusaurus/docs/cloud/overview/gx_cloud_overview.md create mode 100644 docs/docusaurus/docs/cloud/overview/overview_images/gx_cloud_architecture.png create mode 100644 docs/docusaurus/docs/cloud/overview/overview_images/gx_cloud_overview_images.drawio create mode 100644 docs/docusaurus/docs/cloud/overview/overview_images/gx_cloud_workflow.png create mode 100644 docs/docusaurus/docs/cloud/overview/overview_images/gx_cloud_workflow_enhanced.png delete mode 100644 docs/docusaurus/docs/cloud/why_gx_cloud.mdx create mode 100644 docs/docusaurus/static/img/checklist_icon.svg create mode 100644 docs/docusaurus/static/img/database_icon.svg create mode 100644 docs/docusaurus/static/img/gear_icon.svg create mode 100644 docs/docusaurus/static/img/magnify_data_icon.svg create mode 100644 docs/docusaurus/static/img/python_logo.svg create mode 100644 docs/docusaurus/static/img/table_icon.svg diff --git a/docs/docusaurus/docs/application_integration_support.md b/docs/docusaurus/docs/application_integration_support.md index eb986b925d03..8d300cd819a1 100644 --- a/docs/docusaurus/docs/application_integration_support.md +++ b/docs/docusaurus/docs/application_integration_support.md @@ -29,7 +29,7 @@ The following table defines the GX Cloud, GX Core, and Community Supported integ | Credential Stores | Environment variables | Environment variables
YAML4 | None | | Orchestrator | Airflow 5 6 | Airflow 5 6 | None | -1 We've also seen GX work with the following data sources in the past but we can't guarentee ongoing compatibility. These data sources include Clickhouse, Vertica, Dremio, Teradata, Athena, EMR Spark, AWS Glue, Microsoft Fabric, Trino, Pandas on (S3, GCS, Azure), Databricks (Spark), and Spark on (S3, GCS, Azure).
+1 We've also seen GX work with the following data sources in the past but we can't guarantee ongoing compatibility. These data sources include Clickhouse, Vertica, Dremio, Teradata, Athena, EMR Spark, AWS Glue, Microsoft Fabric, Trino, Pandas on (S3, GCS, Azure), Databricks (Spark), and Spark on (S3, GCS, Azure).
2 Support for BigQuery in GX Cloud will be available in a future release.
3 This includes configuration storage for Expectations, Checkpoints, Validation Definitions, and Validation Result
4 config_variables.yml
@@ -53,7 +53,7 @@ The following table defines the operating systems supported by GX Cloud and GX C | ---------------------- | --------- | --------- | | Mac/Linux 1 | Mac/Linux | Mac/Linux | -1 GX does not currently support Windows. However, we've seen users successfuly deploying GX on Windows. +1 GX does not currently support Windows. However, we've seen users successfully deploying GX on Windows. ### Python versions @@ -70,3 +70,15 @@ The following table defines the GX versions supported by GX Cloud and GX Core. | GX Cloud | GX Core | Community | | -------- | ------- | --------- | | ≥1.0 | ≥1.0 | ≥1.0 | + +### Web browsers + +The following web browsers are supported by GX Cloud. + +- [Google Chrome](https://www.google.com/chrome/) — the latest version is fully supported + +- [Mozilla Firefox](https://www.mozilla.org/en-US/firefox/) — the latest version is fully supported + +- [Apple Safari](https://www.apple.com/safari/) — the latest version is fully supported + +- [Microsoft Edge](https://www.microsoft.com/en-us/edge?ep=82&form=MA13KI&es=24) — the latest version is fully supported \ No newline at end of file diff --git a/docs/docusaurus/docs/cloud/_try_gx_cloud.md b/docs/docusaurus/docs/cloud/_try_gx_cloud.md index fe2386b88023..b196678f06d4 100644 --- a/docs/docusaurus/docs/cloud/_try_gx_cloud.md +++ b/docs/docusaurus/docs/cloud/_try_gx_cloud.md @@ -24,7 +24,7 @@ If you've tested GX Cloud features and functionality and discovered it's a great ## Self-hosted deployment -To try GX Cloud, you use a [self-hosted deployment](./about_gx#self-hosted-deployment-pattern) to run the GX Agent with Docker, connect the GX Agent to your target Data Sources, and use the GX Cloud web UI to define your Data Assets, create Expectations, and run Validations. A self-hosted deployment is recommended when you want to test GX Cloud features and functionality and it differs from the recommended [org-hosted deployment](./about_gx.md#org-hosted-deployment-pattern), in which the GX Agent runs in your organization's deployment environment. +To try GX Cloud, you use a [self-hosted deployment](/cloud/deploy/deployment_patterns.md) to run the GX Agent with Docker, connect the GX Agent to your target Data Sources, and use the GX Cloud web UI to define your Data Assets, create Expectations, and run Validations. A self-hosted deployment is recommended when you want to test GX Cloud features and functionality and it differs from the recommended [org-hosted deployment](/cloud/deploy/deployment_patterns.md), in which the GX Agent runs in your organization's deployment environment. ## Get your user access token and copy your organization ID @@ -48,7 +48,7 @@ You'll need your user access token and organization ID to set your environment v ## Set the environment variables and deploy the GX Agent -Environment variables securely store your GX Cloud access credentials. The GX Agent runs open source GX code in GX Cloud, and it allows you to securely access your data without connecting to it or interacting with it directly. To learn more about the GX Agent and deployment patterns, see [About GX Cloud](./about_gx.md). +Environment variables securely store your GX Cloud access credentials. The GX Agent runs open source GX code in GX Cloud, and it allows you to securely access your data without connecting to it or interacting with it directly. To learn more about the GX Agent and deployment patterns, see [GX Cloud deployment patterns](/cloud/deploy/deployment_patterns.md). 1. Start the Docker Engine. diff --git a/docs/docusaurus/docs/cloud/about_gx.md b/docs/docusaurus/docs/cloud/about_gx.md deleted file mode 100644 index 6fb0aaca9d66..000000000000 --- a/docs/docusaurus/docs/cloud/about_gx.md +++ /dev/null @@ -1,122 +0,0 @@ ---- -sidebar_label: 'GX Cloud deployment patterns and architecture' -title: 'GX Cloud deployment patterns and architecture' -description: Learn more about GX Cloud deployment patterns and architecture. -toc_min_heading_level: 2 -toc_max_heading_level: 2 ---- - -GX Cloud simplifies data quality management and monitoring. Its easy-to-use web interface lets you quickly validate your data without provisioning and maintaining complex infrastructure. With GX Cloud, you can work collaboratively with your teammates to define and test reusable data queries that alert you to changes in your data. - -GX Cloud includes the following features and functionality: - -- An intuitive web-based interface makes it easier and faster to set up your Expectations and run your Validations. - -- Data Asset metrics give you a head-start on understanding your data and creating Expectations. - -- Validation run history shows you how your data has changed over time, and makes troubleshooting failed Expectations simple. - -- Scheduling your Validations in GX Cloud helps you get set up with production data quailty checks within minutes. - -- As a fully managed solution, GX Cloud makes connecting to your data straightforward and secure. - -## GX Cloud architecture - -The following diagram provides an overview of the key GX Cloud architecture components: - -![GX Cloud Architecture and Components](./architecture_deployment_images/gx_cloud_architecture_components.png) - -### GX Cloud components - -- **GX Cloud data storage** - Stores your organization's Data Source, Data Asset, Expectation Suite, and Checkpoint configurations and your organization's Validation run histories and Data Asset descriptive metrics. - -- **GX Cloud web UI** - A web interface that allows you to manage and validate your organization's data quality without running Python code and enables shared visibility into your organization's Validation Results and Checkpoint run history. It's browser- and platform-independent. - -- **GX Cloud API** - Provides a REST API to programmatically access and manage GX Cloud data and configurations. Both the GX Core Python library and the GX Agent use the GX Cloud API to query data from and send data to GX Cloud. - - -## GX Cloud deployment options - -GX Cloud deployments can be tailored to meet your specific business requirements. How your data is accessed and how you want your users to interact with GX Cloud determine which deployment pattern and GX architectural components are suitable for your organization. - -| Deployment pattern | Description | When to use | -|----------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------| -| [Fully hosted](#fully-hosted) | You connect your data to GX Cloud entirely through its web interface, in a fully hosted GX-managed environment. Connections to your data are read-only, using secure, encrypted methods. | You want to get started quickly and securely with GX Cloud using direct cloud-to-cloud Data Source connection. | -| [Org-hosted GX Agent](#org-hosted-gx-agent) | You connect your data to GX Cloud using a utility that runs in your organization's deployment environment. While running, the GX Agent can receive tasks generated from the GX Cloud web UI, such as running a Validation or fetching Metrics, and execute these tasks against your Data Assets. | You want to connect to Data Sources using your organization's cloud infrastructure, for enhanced control and security. | -| [Self-hosted GX Agent](#self-hosted-gx-agent) | You connect your data to GX Cloud using a utility that runs on your local machine. While running, the GX Agent can receive tasks generated from the GX Cloud web UI, such as running a Validation or fetching Metrics, and execute these tasks against your Data Assets. | You want to test the Agent setup on your own machine, before moving to a shared production Agent deployment. | -| [API-only](#api-only) | You integrate with GX Cloud using Python scripts, the GX Core Python library, and an orchestrator. The GX Cloud web UI is used primarily to view results; all tasks are executed in your own environment. | You want to use GX Cloud as a data store for Expectations and Validation results only. | - -### Fully hosted -In a fully hosted deployment, you get started with GX Cloud by connecting directly to your organization's cloud data stores via the GX Cloud UI. This is the fastest path to setup. - -If you are using this option please ensure that the GX Cloud IPs are in your organizations allow list for ingress traffic. -- 44.209.54.123 -- 54.235.167.60 -- 34.194.243.19 - -### Org-hosted GX Agent - -In an org-hosted deployment, you run the GX Agent in your organization's deployment environment. The GX Agent is an intermediary between GX Cloud and your organization's deployment environment data stores. Organization users can interact with GX Cloud using the web UI, the GX Core client, or both. - -![GX Cloud org-hosted deployment](./architecture_deployment_images/org_hosted_deployment.png) - -### Self-hosted GX Agent - -In a self-hosted deployment, you use Docker to run the GX Agent in your local environment. The GX Agent is an intermediary between GX Cloud and your local data stores. You can interact with GX Cloud using the web UI, the GX Core Python library, or both. - -![GX Cloud self-hosted deployment](./architecture_deployment_images/self_hosted_deployment.png) - -### API-only - -Use Python scripts and an orchestrator to integrate GX Cloud into your existing data pipeline. The GX Core Python library can be used to access your organization's data stores and to store job results in GX Cloud. Users can interact with GX Cloud using the web UI, the GX Core Python library, or both. - -![GX Cloud orchestrated deployment](./architecture_deployment_images/orchestrated_deployment.png) - -### Custom deployment patterns - -The deployment patterns described previously are not an exhaustive collection of the ways you can deploy GX Cloud. Instead, these patterns are meant to illustrate the building blocks of a GX Cloud deployment and how your organization can configure and connect those blocks to form a functioning data quality ecosystem. - -For example, you might opt to run and interact with the GX Core Python library locally to define your Data Sources, Data Assets, Expectation Suites, and Checkpoints, run the Python scripts utilizing the GX Core library in your Airflow pipeline to execute Checkpoints on a regular schedule, run the GX Agent in your production environment to fetch Data Asset metrics from the GX Cloud web UI, and access the GX Cloud web UI to view Validation and Checkpoint run histories. - -GX provides flexible, robust products that allow your organization to quickly deploy GX Cloud or GX Core to fit your unique requirements. - -## GX Cloud workflow - -The GX Cloud workflow is a sequence of tasks you complete to perform Data Validations. - -You connect GX Cloud to a Data Asset stored on your Data Source, you define and create an Expectation, and then you run a Validation on the data defined in the Expectation. Knowing that your data meets your Expectations helps you ensure your data is accurate and reliable and alerts you to issues before they become problematic. - -The following table lists the sequence of tasks that you complete in a typical GX Cloud workflow. A brief description of the task and links to the relevant topics are provided. - -| Task | Description | -|------------------------------------------|--------------------------------------------------------------------| -| [Create a Data Asset](./data_assets/manage_data_assets.md#create-a-data-asset) | The Data Asset contains the data you want to examine and validate, and the Data Source is where the Data Asset is located. | -| [Invite users](./users/manage_users.md#invite-a-user) | Invite users to your GX Cloud organization. | -| [Create an Expectation](./expectations/manage_expectations.md) | Define verifiable assertions about your data. | -| [Run Validations](./validations/manage_validations.md) | Run a Validation to determine if your data meets the assertions in the Expectation. | - -## Roles and responsibilities - -How you interact with GX Cloud is dependent on the role you're assigned by your Admin. The following table lists GX Cloud roles and responsibilities. - -| Role | Responsibilities | -|---------------|---------------------------------------------------| -| Viewer | View Validation Results | -| Editor | Create Data Assets
Create and edit Expectations
Create access tokens | -| Admin | Full access
Perform all GX Cloud administrative functions including user and role assignment | - -## Supported browsers - -The following browsers are supported by GX Cloud: - -- [Google Chrome](https://www.google.com/chrome/) — the latest version is fully supported - -- [Mozilla Firefox](https://www.mozilla.org/en-US/firefox/) — the latest version is fully supported - -- [Apple Safari](https://www.apple.com/safari/) — the latest version is fully supported - -- [Microsoft Edge](https://www.microsoft.com/en-us/edge?ep=82&form=MA13KI&es=24) — the latest version is fully supported - -### Browser session duration - -A session is the period of time that you’re signed in to your GX Cloud account from a browser. If you close the browser, your session ends, and you're signed out. 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[Admin or Editor permissions](/cloud/users/manage_users.md#roles-and-responsibilities). - You have a Databricks SQL catalog, schema, and table. diff --git a/docs/docusaurus/docs/cloud/connect/connect_postgresql.md b/docs/docusaurus/docs/cloud/connect/connect_postgresql.md index c98b3f2c3772..a4db9a2f321e 100644 --- a/docs/docusaurus/docs/cloud/connect/connect_postgresql.md +++ b/docs/docusaurus/docs/cloud/connect/connect_postgresql.md @@ -9,7 +9,7 @@ import Tabs from '@theme/Tabs'; ## Prerequisites -- You have a [GX Cloud account](https://greatexpectations.io/cloud) with [Admin or Editor permissions](../about_gx.md#roles-and-responsibilities). +- You have a [GX Cloud account](https://greatexpectations.io/cloud) with [Admin or Editor permissions](/cloud/users/manage_users.md#roles-and-responsibilities). - You have a PostgreSQL database, schema, and table. diff --git a/docs/docusaurus/docs/cloud/connect/connect_snowflake.md b/docs/docusaurus/docs/cloud/connect/connect_snowflake.md index a8a6835893eb..a792300c0208 100644 --- a/docs/docusaurus/docs/cloud/connect/connect_snowflake.md +++ b/docs/docusaurus/docs/cloud/connect/connect_snowflake.md @@ -9,7 +9,7 @@ import Tabs from '@theme/Tabs'; ## Prerequisites -- You have a [GX Cloud account](https://greatexpectations.io/cloud) with [Admin or Editor permissions](../about_gx.md#roles-and-responsibilities). +- You have a [GX Cloud account](https://greatexpectations.io/cloud) with [Admin or Editor permissions](/cloud/users/manage_users.md#roles-and-responsibilities). - You have a Snowflake database, schema, and table. diff --git a/docs/docusaurus/docs/cloud/deploy_gx_agent.md b/docs/docusaurus/docs/cloud/deploy/deploy_gx_agent.md similarity index 78% rename from docs/docusaurus/docs/cloud/deploy_gx_agent.md rename to docs/docusaurus/docs/cloud/deploy/deploy_gx_agent.md index f5410e2cc016..bb00fdbddaf4 100644 --- a/docs/docusaurus/docs/cloud/deploy_gx_agent.md +++ b/docs/docusaurus/docs/cloud/deploy/deploy_gx_agent.md @@ -9,26 +9,25 @@ toc_max_heading_level: 2 import TabItem from '@theme/TabItem'; import Tabs from '@theme/Tabs'; -:::info -For access to the GX Agent, reach out to Support at support@greatexpectations.io. +The GX Agent is used to run an [agent-enabled deployment](/cloud/deploy/deployment_patterns.md#agent-enabled-deployment) of GX Cloud. If you are running a fully hosted or read-only deployment, you do not need to deploy the GX Agent. -::: +:::info Enable the GX Agent -GX Cloud is a fully hosted data quality solution and you do not need to deploy the GX Agent to make use of its full suite of features. However, you can optionally deploy the GX Agent to exert additional control over how users access GX Cloud and how data is accessed by GX Cloud processes. +The GX Agent, and agent-enabled deployments, are not available by default in GX Cloud. To enable the GX Agent for your GX Cloud organization, reach out to GX Support at support@greatexpectations.io. -The GX Agent is an intermediary between GX Cloud and your organization's data stores. GX Cloud does not connect directly to your data with this deployment option, and all data access occurs within the GX Agent. GX Cloud sends jobs to the GX Agent, the GX Agent executes these jobs against your data, and then sends the job results to GX Cloud. +::: -A local deployment of the GX Agent will allow you to test GX Cloud setup or processes from a single machine before moving to a shared production deployment. Alternatively, you can deploy the GX Agent to your development environment and leverage GX Cloud while connecting to Data Sources using your organization's cloud infrastructure, for enhanced control and security. +The GX Agent serves as an intermediary between GX Cloud and your organization's data stores. GX Cloud does not connect directly to your data in an agent-enabled deployment, and all data access occurs within the GX Agent. GX Cloud sends jobs to the GX Agent, the GX Agent executes these jobs against your data, and then sends the job results to GX Cloud. +A local deployment of the GX Agent will allow you to test GX Cloud setup or processes from a single machine before moving to a shared production deployment. Alternatively, you can run the GX Agent in your deployment environment and leverage GX Cloud while connecting to Data Sources using your organization's environment and infrastructure, for enhanced control and security. -### GX Agent versioning -GX uses a date-based versioning format for its weekly GX Agent Docker image releases: `YYYYMMMDD.#` for stable releases and `YYYYMMDD.#.dev#` for pre-releases. GX uses the `stable` and `dev` Docker image tags to identify the release type. The `stable` tag indicates the image is fully tested and ready for use. The `dev` tag indicates a pre-release image. This documentation assumes you're using the latest `stable` GX Agent Docker image. ## Prerequisites - You have a [GX Cloud account](https://greatexpectations.io/cloud). -- You have reached out to Support at support@greatexpectations.io to request a GX Agent deployment. +- You have reached out to GX Support at support@greatexpectations.io to request a GX Agent deployment. +- You have a [Docker instance](https://docs.docker.com/get-docker/) or [kubectl](https://kubernetes.io/docs/tasks/tools/). ## Get your access token and organization ID @@ -81,20 +80,15 @@ Use the information provided here to view your organization ID or create a new a ## Deploy the GX Agent -The GX Agent allows you to securely access your data without connecting to it or interacting with it directly. To learn more about the GX Agent and deployment patterns, see [About GX Cloud](./about_gx.md). - -### Prerequisites - -- You have a GX Cloud access token and organization ID. See [Get your access token and organization ID](#get-your-access-token-and-organization-id). - -- You have a [Docker instance](https://docs.docker.com/get-docker/) or [kubectl](https://kubernetes.io/docs/tasks/tools/). +The GX Agent allows you to securely access your data without connecting to it or interacting with it directly. @@ -132,12 +126,9 @@ You can deploy the GX Agent in any environment in which you create Kubernetes cl 2. After configuring your cloud service to run Docker containers, run the following Docker command to start the GX Agent: ```bash title="Terminal input" - docker run -it \ - -e GX_CLOUD_ACCESS_TOKEN= YOUR_ACCESS_TOKEN \ - -e GX_CLOUD_ORGANIZATION_ID= YOUR_ORGANIZATION_ID \ - greatexpectations/agent:stable + docker run -it -e GX_CLOUD_ACCESS_TOKEN="" -e GX_CLOUD_ORGANIZATION_ID="" greatexpectations/agent:stable ``` - Replace `YOUR_ACCESS_TOKEN` and `YOUR_ORGANIZATION_ID` with the values you copied previously. + Replace `` and `` with the [access token and organization ID](#get-your-access-token-and-organization-id) values that you copied previously. 3. Optional. If you created a temporary file to record your user access token and Organization ID, delete it. @@ -166,7 +157,7 @@ You can deploy the GX Agent in any environment in which you create Kubernetes cl --from-literal=GX_CLOUD_ORGANIZATION_ID=YOUR_ORGANIZATION_ID \ --from-literal=GX_CLOUD_ACCESS_TOKEN=YOUR_ACCESS_TOKEN \ ``` - Replace `YOUR_ORGANIZATION_ID` and `YOUR_ACCESS_TOKEN` with the values you copied previously. + Replace `YOUR_ORGANIZATION_ID` and `YOUR_ACCESS_TOKEN` with the [organization ID and access token](#get-your-access-token-and-organization-id) values that you copied previously. 3. Optional. If you created a temporary file to record your user access token and Organization ID, delete it. @@ -226,7 +217,7 @@ You can deploy the GX Agent in any environment in which you create Kubernetes cl ```bash title="Terminal input" docker run --rm --pull=always -e GX_CLOUD_ACCESS_TOKEN="" -e GX_CLOUD_ORGANIZATION_ID="" greatexpectations/agent ``` - Replace `user_access_token` and `organization_id` with the values you copied previously. + Replace `` and `` with the [access token and organization ID](#get-your-access-token-and-organization-id) values that you copied previously. 3. In GX Cloud, confirm the GX Agent status is **Active Agent** and the icon is green. This indicates the GX Agent is active. If it isn't, repeat step 2 and confirm the `user_access_token` and `organization_id` values are correct. @@ -253,13 +244,5 @@ If you encounter an issue deploying the GX Agent or performing a GX Cloud task, 3. Optional. Click **Hide log** to close the log details view. - -## Next steps - -Want to continue testing GX Cloud features and functionality? - -- [Create a Data Asset](./data_assets/manage_data_assets.md#create-a-data-asset) - -Ready to connect GX Cloud to your deployment environment? - -- [Connect GX Cloud](./connect/connect_lp.md) +## GX Agent versioning +GX uses a date-based versioning format for its weekly GX Agent Docker image releases: `YYYYMMMDD.#` for stable releases and `YYYYMMDD.#.dev#` for pre-releases. GX uses the `stable` and `dev` Docker image tags to identify the release type. The `stable` tag indicates the image is fully tested and ready for use. The `dev` tag indicates a pre-release image. \ No newline at end of file diff --git a/docs/docusaurus/docs/cloud/deploy/deploy_lp.md b/docs/docusaurus/docs/cloud/deploy/deploy_lp.md new file mode 100644 index 000000000000..782ca75f0b98 --- /dev/null +++ b/docs/docusaurus/docs/cloud/deploy/deploy_lp.md @@ -0,0 +1,21 @@ +--- +sidebar_label: 'Deploy GX Cloud' +title: 'Deploy GX Cloud' +hide_title: true +description: Deploy GX Cloud in your environment. +hide_feedback_survey: true +--- + +import LinkCardGrid from '@site/src/components/LinkCardGrid'; +import LinkCard from '@site/src/components/LinkCard'; +import OverviewCard from '@site/src/components/OverviewCard'; + + + Deploy GX Cloud in your environment. + + + + + + + \ No newline at end of file diff --git a/docs/docusaurus/docs/cloud/deploy/deployment_images/agent_enabled_deployment.png b/docs/docusaurus/docs/cloud/deploy/deployment_images/agent_enabled_deployment.png new file mode 100644 index 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zZ)@HBdJ^(YQu=U3^fTe>cUWZ9UrINX#-M0>8e^Q(zEd;4Z6zb2{tIK(tqVG-XTH$J zw?0$@C#(}vq8eO;40ux@eOTCm)X1Y@NJ5m4v>BCL<@i5}TBYcRhNQCLQ7*L}z%EG& zNo~*4pPupBH=a)Uc4#>T$vnkyC%#`y%vU_6yFJAR6Y}6kO8i|O;D%^H99WIL?+KAA zVcX7Moa3v>O_j$uJmW-6?oMM17`%jx7_o5P0M3ZI7UiaQu~JwXh+tzJABZI^i;g+f zHt%KYrpZ59VSIDyjr}L){>jq*U61nPkG4W`uyvgOj)D3=@Z+}$z}Lxz6aM$*AdWHo z=XU=tMGGngVZXG#h~R&o - - + + + + + ### Manage diff --git a/docs/docusaurus/docs/cloud/overview/gx_cloud_overview.md b/docs/docusaurus/docs/cloud/overview/gx_cloud_overview.md new file mode 100644 index 000000000000..846bd2622b80 --- /dev/null +++ b/docs/docusaurus/docs/cloud/overview/gx_cloud_overview.md @@ -0,0 +1,68 @@ +--- +title: 'GX Cloud overview' +id: gx_cloud_overview +description: Explore GX Cloud components, workflows, and architecture. +toc_min_heading_level: 2 +toc_max_heading_level: 2 +--- + +GX Cloud is a fully managed SaaS platform that simplifies data quality management and monitoring. With GX Cloud, you and your organization can work collaboratively to define and maintain shared understanding of your data. + +## GX Cloud concepts + +The key GX Cloud concepts described below provide a data validation vocabulary that represents your data, your data validation criteria, and the results of data validation. Within GX Cloud, these concepts are applied to define components and implement data validation workflows. + +| | | +| :--: | :--- | +| Data Source | **Data Source**
A Data Source is the GX representation of a database or data store. | +| Data Asset | **Data Asset**
A Data Asset is a collection of records within a Data Source. | +| Expectation | **Expectation**
An Expectation is a declarative, verifiable assumption about your data. Expectations serve as unit tests for your data. | +| Validation | **Validation**
A Validation runs selected Expectations against a Data Asset to validate the data defined by that Data Asset. | +| Validation Result | **Validation Result**
A Validation Result captures the outcome of a Validation and related metadata that describes passing and failing data. | + +## GX Cloud workflow + +GX Cloud data validation workflows are created using GX Cloud components, entities that represent GX Cloud data validation concepts. + +### Standard data validation workflow + +A GX Cloud data validation workflow can be implemented using a short, clear set of steps: + +![Standard GX Cloud workflow](./overview_images/gx_cloud_workflow.png) + +1. Connect to your data. +2. Create a Data Asset. +3. Define Expectations. +4. Validate your data. +5. Review and share your Validation Results with your organization. + + +### Additional workflow features +There are a variety of GX Cloud features that support additional enhancements to your GX Cloud data validation workflow. + +![GX Cloud workflow enhanced with product features](./overview_images/gx_cloud_workflow_enhanced.png) + +* **GX Cloud user management.** GX Cloud functions as a shared portal to manage and monitor your organization's data quality. Users can be invited to your GX Cloud organization and assigned a role that governs their ability to view and edit components and workflows in GX Cloud. See [Manage users and access tokens](/cloud/users/manage_users.md) for more details. + +* **Data Asset profiling.** GX Cloud introspects your data schema by default on Data Asset creation, and also offers one-click fetching of additional descriptive metrics including column type and statistical summaries. Data profiling results are used to suggest parameters for Expectations that you create. + +* **Schedule Validations.** GX Cloud enables you to schedule validations, so that you can test and assess your data on a regular cadence and monitor data quality over time. See [Manage schedules](/cloud/schedules/manage_schedules.md) for more detail. + +* **Alerting.** GX Cloud provides the ability send alerts when validations fail, enabling your organization to remain proactively aware of the health of your Data Assets. See [Manage alerts](/cloud/alerts/manage_alerts.md) for more detail. + + + + +## GX Cloud architecture + +GX Cloud architecture comprises a frontend web UI, storage for entity configuration and metadata, a backend application, and a Python client. + +![GX Cloud architecture](./overview_images/gx_cloud_architecture.png) + +* **GX Cloud frontend web UI**. Enables you to manage and validate your organization's data quality without running code and provides shared visibility into your organization's Validation Results history. The GX Cloud web UI is browser- and platform-independent. + +* **GX Cloud data storage**. Stores the configurations for your organization's Data Sources, Data Assets, Expectations, and Validations alongside your organization's Validation Result histories and Data Asset descriptive metrics. + +* **GX Cloud backend application**. Contains the necessary logic and compute to connect to data and run queries. The specifics of how the GX Cloud backend connects to your data is described in [GX Cloud deployment pattern](/cloud/deploy/deployment_patterns.md). + +* **GX Core Python client**. Enables you to interact programmatically with the GX Cloud backend application. 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w8K%Fly!>|wL7-u`Qf2<#HLw1U&TSS}4V5a#Pq{mS0sh^WSCji7^C0m50T}%rG5`Po literal 0 HcmV?d00001 diff --git a/docs/docusaurus/docs/cloud/users/manage_users.md b/docs/docusaurus/docs/cloud/users/manage_users.md index 893189ec359d..e9cd304d3bbc 100644 --- a/docs/docusaurus/docs/cloud/users/manage_users.md +++ b/docs/docusaurus/docs/cloud/users/manage_users.md @@ -6,6 +6,16 @@ description: Manage GX Cloud users and access tokens. With Admin permissions, you can add users, edit organization roles, and delete users. You can also manage user and organization access tokens. +## Roles and responsibilities + +The following table lists GX Cloud roles and responsibilities. + +| Role | Responsibilities | +|---------------|---------------------------------------------------| +| Viewer | View Validation Results | +| Editor | Create Data Assets
Create and edit Expectations
Create access tokens | +| Admin | Full access
Perform all GX Cloud administrative functions including user and role assignment | + ## Invite a user 1. In GX Cloud, click **Settings** > **Users**. diff --git a/docs/docusaurus/docs/cloud/why_gx_cloud.mdx b/docs/docusaurus/docs/cloud/why_gx_cloud.mdx deleted file mode 100644 index a27185a220dd..000000000000 --- a/docs/docusaurus/docs/cloud/why_gx_cloud.mdx +++ /dev/null @@ -1,80 +0,0 @@ ---- -sidebar_label: 'Why GX Cloud' -title: 'Why GX Cloud' -description: Why GX Cloud. ---- - -If you’ve made it this far, you know that you need a data quality framework—it’s time to think about how to make it happen. GX Cloud is the data quality solution for when you need: - -- A fast, easy way to set up comprehensive test coverage. -- Collaborative input from other teams and stakeholders. -- Shared understanding through results that are accessible to everyone. - -Proactive data quality lets you catch issues before they can become problems downstream. And with GX Cloud, you can have your first proactive data quality tests in place today. - -## Expect great things - -An Expectation is a simple, verifiable assertion about the way your data should be. - -Expectations offer deeper insights than schema validations, and they’re more resilient to changes in business and technical requirements. With Expectations, you can intuitively create data quality tests with unparalleled flexibility and control and make them accessible to technical and nontechnical users alike. - - - -Plus, Expectations are reusable and [create their own documentation](/cloud/validations/manage_validations.md#view-validation-run-history), making it easy to deploy them across large numbers of datasets and then keep everyone on the same page about what they’re doing. - -Expectations in GX Cloud tell you exactly what they’re for **using plain language, start to finish**. Self-explanatory names and results expressed in full sentences mean anyone can understand an Expectation and Expectation Suite on first look. - -## Collaboration upgrades - -To build a culture of organizational trust in your data, you need the experience, insights, and buy-in of other technical teams in your organization, plus that of your nontechnical stakeholders. - -Technical teams will find the control and flexibility they're looking for with GX Cloud. Built on GX Core, GX Cloud’s rich API allows data engineers to interact with it using tools they're already comfortable with, like Python and Jupyter notebooks. - -And its ability to connect to a wide range of data sources and interoperability with orchestrators means [GX Cloud can fit into your data pipelines exactly where you need it](/cloud/about_gx.md#gx-cloud-deployment-patterns). - -No matter how many datasets you're working with, GX Cloud unifies your data quality testing in one place. It’s easy to find team members’ tests, and—since everyone is using the same language and approach—easier to understand what they’re doing. - -On top of that, GX Cloud’s familiar SaaS approach and friendly user interface makes nontechnical stakeholders feel included and competent from the start. - -GX Cloud’s business-friendly visualizations of test results lets stakeholders absorb and learn from data quality results using their existing competencies, no technical hand-holding needed. They can navigate and contribute to GX Cloud [without having to read or write a single line of code](/cloud/about_gx.md#workflow-optimization)—independently and on their own schedule. - -Because GX Cloud **empowers stakeholders to contribute and understand independently**, stakeholders finally feel like the data quality process is backed by a transparency that fosters maximum trust. - -## Clear, central communication - -Building a shared understanding of your data quality is hard enough already without misunderstandings or lost-in-translation moments cropping up. GX Cloud makes it easy for everyone to stay on the same page: - -- Tests and results are in clear, plain language that can speak for itself. -- A shared UI organically fosters standardized processes. - -GX Cloud’s clear user interface means you can spend your time with new users working productively, instead of trying to explain what they’re seeing. - -Whether you prefer to see **results as numbers or visualizations**, GX Cloud provides. Get the gist of a Validation Result by scanning its straightforward visual indicators, or inspect its detailed result tables instead. - -Historical results are displayed with **trend visualizations** accessible to technical and nontechnical teams alike. - - - -Effective communication is easier when everyone shares a single source of reliable information. GX Cloud’s **clear visual UI organically fosters standardized processes**. Your team members will naturally build similar perspectives even before they directly interact—making communication smoother from the start. - - -## Sustainable growth - -A cornerstone of growing an effective data quality framework is to **embrace iteration**. GX Cloud is built to support that. - - - -There’s nowhere the need for iteration is more constant than when it comes to creating and configuring your data quality tests: as you uncover more nuances of your data, your operational needs change, or your data stack evolves, you’ll need to continue updating your Expectations. - -Your testing feedback loop stays short and responsive in GX Cloud. Its visual GUI for Expectation editing makes it [a snap to create and edit them for nontechnical teams, while data engineers can use the power of GX Cloud’s API](/cloud/expectations/manage_expectations.md#add-an-expectation). - -And you can make those changes with confidence that you won’t disrupt your view of your historical results: **GX Cloud captures every change to an Expectation** within your test result’s historical charts and visualizations, so you can see your Validation Results in context with your evolving understanding of your data. - -## Don't take our word for it - -GX Cloud’s free tier has plenty of power. Give it a try and see for yourself how GX Cloud can help you build a proactive, collaboration-ready data quality framework. - -## Next steps - -- [Try GX Cloud](https://greatexpectations.io/cloud) -- [Request a demo](https://greatexpectations.io/demo) diff --git a/docs/docusaurus/docs/core/introduction/introduction.mdx b/docs/docusaurus/docs/core/introduction/introduction.mdx index 268d9fbfbfeb..af33ac341ac0 100644 --- a/docs/docusaurus/docs/core/introduction/introduction.mdx +++ b/docs/docusaurus/docs/core/introduction/introduction.mdx @@ -3,6 +3,8 @@ title: Introduction to GX Core description: Learn about GX Core components and workflows and try out the GX Core Python library. hide_feedback_survey: true hide_title: true +pagination_next: null +pagination_prev: null --- import GxData from '../_core_components/_data.jsx' diff --git a/docs/docusaurus/docs/gx_welcome.md b/docs/docusaurus/docs/gx_welcome.md index 50ac63d04e43..38f753558a17 100644 --- a/docs/docusaurus/docs/gx_welcome.md +++ b/docs/docusaurus/docs/gx_welcome.md @@ -24,8 +24,12 @@ import GXCard from '@site/src/components/GXCard'; ## What do you want to do today? - + + - - + + + + + diff --git a/docs/docusaurus/docs/reference/learn/data_quality_use_cases/missingness.md b/docs/docusaurus/docs/reference/learn/data_quality_use_cases/missingness.md index 8e1d13e30ea9..0283eefa6f67 100644 --- a/docs/docusaurus/docs/reference/learn/data_quality_use_cases/missingness.md +++ b/docs/docusaurus/docs/reference/learn/data_quality_use_cases/missingness.md @@ -64,7 +64,7 @@ Ensures that values within a specific column are not `NULL`. The examples given in this section provide insight into how and when to apply missingness Expectations to identify different varieties of missing data. The focus of this guidance is on the specifics of the Expectations, rather than the overall workflow, which can be implemented using either GX Cloud or GX Core. -[GX Cloud](/cloud/about_gx.md#gx-cloud-workflow) provides a visual interface to create and run workflows for managing missing data. The GX Cloud workflow to handle data missingness is intuitive and straightforward: create a Data Asset, define Expectations for missing values, run a Validation, and review Validation Results. +[GX Cloud](/cloud/overview/gx_cloud_overview.md) provides a visual interface to create and run workflows for managing missing data. The GX Cloud workflow to handle data missingness is intuitive and straightforward: create a Data Asset, define Expectations for missing values, run a Validation, and review Validation Results. ![Validate missingness Expectations in GX Cloud](./missingness_resources/gx_cloud_missingness_expectations_validate.gif) diff --git a/docs/docusaurus/docs/resources/get_support.md b/docs/docusaurus/docs/resources/get_support.md index 935b695266c3..90ec6d5101fc 100644 --- a/docs/docusaurus/docs/resources/get_support.md +++ b/docs/docusaurus/docs/resources/get_support.md @@ -36,7 +36,7 @@ The following are some recommendations for resolving issues on your own. Resolvi Search the docs you're using currently for an answer to your issue or question. -If you're new to GX Cloud, review [About GX Cloud](/cloud/about_gx.md). +If you're new to GX Cloud, review the [GX Cloud overview](/cloud/overview/gx_cloud_overview.md). If you're new to GX Core, see the [Introduction to GX Core](/core/introduction/introduction.mdx). diff --git a/docs/docusaurus/docusaurus.config.js b/docs/docusaurus/docusaurus.config.js index 28901de84138..c0835c882592 100644 --- a/docs/docusaurus/docusaurus.config.js +++ b/docs/docusaurus/docusaurus.config.js @@ -59,8 +59,8 @@ module.exports = { href: 'https://greatexpectations.io/cloud', }, secondary: { - label: 'Why GX Cloud?', - href: 'https://docs.greatexpectations.io/docs/cloud/why_gx_cloud', + label: 'GX Cloud overview', + href: '/docs/cloud/overview/gx_cloud_overview', }, }, }, @@ -152,7 +152,7 @@ module.exports = { }, { label: 'GX Cloud', - to: 'docs/cloud', + to: 'docs/cloud/overview/gx_cloud_overview', position: 'right', className: 'non-versioned-section', }, diff --git a/docs/docusaurus/sidebars.js b/docs/docusaurus/sidebars.js index 1f6a1a709386..fd436788c3c5 100644 --- a/docs/docusaurus/sidebars.js +++ b/docs/docusaurus/sidebars.js @@ -146,43 +146,37 @@ module.exports = { } ], gx_cloud: [ - {type: 'doc', id: 'cloud/why_gx_cloud'}, { type: 'category', - label: 'GX Cloud deployment patterns and architecture', - link: { type: 'doc', id: 'cloud/about_gx' }, + label: 'GX Cloud overview', + link: { type: 'doc', id: 'cloud/overview/gx_cloud_overview' }, items: [ { type: 'link', - label: 'GX Cloud architecture', - href: '/docs/cloud/about_gx#gx-cloud-architecture', - }, - { - type: 'link', - label: 'GX Cloud deployment options', - href: '/docs/cloud/about_gx#gx-cloud-deployment-options', + label: 'GX Cloud concepts', + href: '/docs/cloud/overview/gx_cloud_overview#gx-cloud-concepts', }, { type: 'link', label: 'GX Cloud workflow', - href: '/docs/cloud/about_gx#gx-cloud-workflow', - }, - { - type: 'link', - label: 'Roles and responsibilities', - href: '/docs/cloud/about_gx#roles-and-responsibilities', + href: '/docs/cloud/overview/gx_cloud_overview#gx-cloud-workflow', }, { type: 'link', - label: 'Supported browsers', - href: '/docs/cloud/about_gx#supported-browsers', - }, - { - type: 'doc', - id: 'cloud/deploy_gx_agent' + label: 'GX Cloud architecture', + href: '/docs/cloud/overview/gx_cloud_overview#gx-cloud-architecture', }, ] }, + { + type: 'category', + label: 'Deploy GX Cloud', + link: { type: 'doc', id: 'cloud/deploy/deploy_lp' }, + items: [ + 'cloud/deploy/deployment_patterns', + 'cloud/deploy/deploy_gx_agent', + ] + }, { type: 'category', label: 'Connect GX Cloud', @@ -367,6 +361,11 @@ module.exports = { label: 'Manage users and access tokens', link: { type: 'doc', id: 'cloud/users/manage_users' }, items: [ + { + type: 'link', + label: 'Roles and responsibilities', + href: '/docs/cloud/users/manage_users#roles-and-responsibilities', + }, { type: 'link', label: 'Invite a user', diff --git a/docs/docusaurus/static/img/checklist_icon.svg b/docs/docusaurus/static/img/checklist_icon.svg new file mode 100644 index 000000000000..b782f01858bb --- /dev/null +++ b/docs/docusaurus/static/img/checklist_icon.svg @@ -0,0 +1,38 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/docusaurus/static/img/database_icon.svg b/docs/docusaurus/static/img/database_icon.svg new file mode 100644 index 000000000000..dcc1f5441e50 --- /dev/null +++ b/docs/docusaurus/static/img/database_icon.svg @@ -0,0 +1,14 @@ + + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/docusaurus/static/img/gear_icon.svg b/docs/docusaurus/static/img/gear_icon.svg new file mode 100644 index 000000000000..a78418dd9b83 --- /dev/null +++ b/docs/docusaurus/static/img/gear_icon.svg @@ -0,0 +1,47 @@ + + + + + + + + + + \ No newline at end of file diff --git a/docs/docusaurus/static/img/magnify_data_icon.svg b/docs/docusaurus/static/img/magnify_data_icon.svg new file mode 100644 index 000000000000..866cc00bc181 --- /dev/null +++ b/docs/docusaurus/static/img/magnify_data_icon.svg @@ -0,0 +1,7 @@ + + + + + + + \ No newline at end of file diff --git a/docs/docusaurus/static/img/python_logo.svg b/docs/docusaurus/static/img/python_logo.svg new file mode 100644 index 000000000000..1fc8c883bb82 --- /dev/null +++ b/docs/docusaurus/static/img/python_logo.svg @@ -0,0 +1,19 @@ + + + + + python [#127] + Created with Sketch. + + + + + + + + + + + + + \ No newline at end of file diff --git a/docs/docusaurus/static/img/table_icon.svg b/docs/docusaurus/static/img/table_icon.svg new file mode 100644 index 000000000000..91ac5caeb87c --- /dev/null +++ b/docs/docusaurus/static/img/table_icon.svg @@ -0,0 +1,7 @@ + + + + + + + \ No newline at end of file