Sync data from Kubernetes to Databricks

CloudQuery is the simple, fast data integration platform that can fetch your data from Kubernetes APIs and load it into Databricks

Trusted by

Self-hosted

Start locally, then deploy to a Virtual Machine, Kubernetes, or anywhere else. Full instructions on CLI setup are available in our documentation.

Step-by-step Instructions

Cloud-hosted

Start syncing in a few clicks. No need to deploy your own infrastructure.

Coming soon for Kubernetes to Databricks

Fast and reliable

CloudQuery’s efficient design means our syncs are fast and a sync from Kubernetes to Databricks can be completed in a fraction of the time compared to other tools.

Easy to use, easy to maintain

Kubernetes syncing using CloudQuery is easy to set up and maintain thanks to its simple YAML configuration. Once synced, you can use normal SQL queries to work with your data.

A huge library of supported destinations

Databricks isn’t the only place we can sync your Kubernetes data to. Whatever you need to do with your Kubernetes data, CloudQuery can make it happen. We support a huge range of destinations, customizable transformations for ETL, and we regularly release new plugins.

Extensible and Open Source SDK

Write your own connectors in any language by utilizing the CloudQuery open source SDK powered by Apache Arrow. Get out-of-the-box scheduling, rate-limiting, transformation, documentation and much more.

Step by step guide for how to export data from Kubernetes to Databricks

MacOS Windows Linux

MacOS Setup

Step 1: Install CloudQuery

To install CloudQuery, run the following command in your terminal:

brew install cloudquery/tap/cloudquery

Step 2: Create a Configuration File

Next, run the following command to initialize a sync configuration file for Kubernetes to Databricks:

cloudquery init --source=k8s --destination=databricks

This will generate a config file named k8s_to_databricks.yaml. Follow the instructions to fill out the necessary fields to authenticate against your own environment.

Next, log in to the CloudQuery CLI. If you have't already, you can sign up for a free account as part of this step:

cloudquery login

Step 4: Run a Sync

cloudquery sync k8s_to_databricks.yaml

This will start syncing data from the Kubernetes API to your Databricks database! 🚀

See the CloudQuery documentation portal for more deployment guides, options and further tips.

FAQs

What is CloudQuery?

CloudQuery is an open-source tool that helps you extract, transform, and load cloud asset data from various sources into databases for security, compliance, and visibility.

Why does CloudQuery require login?

Logging in allows CloudQuery to authenticate your access to the CloudQuery Hub and monitor usage for billing purposes. Data synced with CloudQuery remains private to your environment and is not shared with our servers or any third parties.

What data does CloudQuery have access to?

CloudQuery accesses only the metadata and configurations of your cloud resources that you specify without touching sensitive data or workloads.

How is CloudQuery priced?

CloudQuery offers flexible pricing based on the number of cloud accounts and usage. Visit our pricing page for detailed plans.

Is there a free version of CloudQuery?

Yes, CloudQuery offers a free plan that includes basic features, perfect for smaller teams or personal use. More details can be found on our pricing page.

What authentication information is required to run the sync from Kubernetes to Databricks?

CloudQuery works on a similar basis to kubectl, the Kubernetes command line tool and will use information contained in a Kubernetes configuration file (also known as a kubeconfig file) to authenticate the sync. By default, CloudQuery will look for a file located at ~/.kube/config. If you want to use a different file, you can specify this by setting the KUBECONFIG environment variable to your chosen path.

How can I specify which Kubernetes contexts to connect to?

By default, CloudQuery will use the contexts specificed in your Kubernetes configuration file. If you want to connect to different contexts, you can specify this by setting the contexts variable. This variable supports wildcard use, so if you want to connect to all available contexts, simply set the variable to *.