Below we have outlined the most important topics to consider when getting started with GoodData Cloud Native. These will aid you in building of your analytic solution.
Installation & Deployment
During the evaluation of GD.CN, you were most likely able to install and deploy GD.CN (or its Community Edition) in an environment of your choice. If that is not the case, you might want to take a look at the process that accompanies this.
There are several helpful pages in our documentation to guide you through. They are available at https://www.gooddata.com/developers/cloud-native/doc/2.3/deploy-and-install/cloud-native. Here you will find resources concerning requirements, different types of environments you can use, as well as guidelines for deployment with Helm Chart.
Another valuable resource are the Deployment Considerations, which go over the major steps when deploying GD.CN:
These topics refer to key processes to take into consideration when deploying GD.CN, such as handling certificates, DNS and TLS configurations. We strongly recommend reviewing these.
As GD.CN is deployable on premises and in various cloud environments that we cover below, there are hardware and software requirements that need to be met. You can learn more about these on this help page:
We have prepared reference examples for Postgres and Redis while deploying GD.CN on Amazon AWS, Google Cloud, Microsoft Azure and on-premise. These can be found here:
Helm Chart Installation
The most straightforward way to install and deploy GD.CN into your environment is to install it via Helm Chart. The following article guides you through every step:
Once you have deployed your GD.CN platform and are ready to go, the next step is to set up one (or more) organizations. Here, an organization is a basic unit of isolation of data sources, workspaces, and users. In other words, it is analogical to an analytical application from the point of its user. You can create any number of such applications for your tenants. These help pages go into more detail about creating and managing your organizations:
As you progress through creating your first organization, it is necessary to ensure that people are able to login and start building, consuming or managing your analytics. GD.CN utilizes OpenID Connect (OIDC), a simple identity layer on top of the OAuth 2.0 protocol to manage user authentication in the platform.
You have the option to use your own external OIDC provider, which we highly recommend. It is also possible to leverage Dex, the built-in provider that is included in GD.CN.
Please consult the following help pages to guide you through authentication setup:
Building Your Data Application
After completing the above steps, you are ready to build your analytics. Before you dive in, it might be worthwhile to familiarize yourself with some of the concepts of GD.CN. We recommend to start with learning about the Logical Data Model and take it from there:
Embedding with GoodData.UI
You can also use GD.CN inside your web application. GoodData.UI is a collection of libraries that helps you build custom data applications on top of GD.CN. You can learn more about it in the following articles:
There are GoodData Python libraries that allow you to work with GD.CN API in a programmatic and convenient way. They facilitate automatization of various workflows, such as provisioning or implementing data pipelines. You can learn more about these here:
GoodData Pandas library is built on top of GoodData Python SDK and itself is a lightweight layer that allows you to build Pandas series or dataframes on top of GoodData. All information can be found here: