![]() ![]() In this guide you will learn about the Master server, cluster nodes, and the Kubernetes Control Plane. Together, these servers form a cluster and are controlled by the services that make up the Control Plane. These servers can be Linodes, VMs, or physical servers. If you are unsure whether your account is on the E2 platform, contact your Databricks representative.This is the second guide in the Beginner’s Guide to Kubernetes series that explains the major parts and concepts of Kubernetes.Īt the highest level of Kubernetes, there exist two kinds of servers, a Master and a Node. ![]() Most existing accounts have been migrated. New accounts-except for select custom accounts-are created on the E2 platform. Secure cluster connectivity: Also known as “No Public IPs,” secure cluster connectivity lets you launch clusters in which all nodes have only private IP addresses, providing enhanced security.Ĭustomer-managed keys for managed services: Provide KMS keys to encrypt notebook and secret data in the Databricks-managed control plane.Īlong with features like token management, IP access lists, cluster policies, and IAM credential passthrough, the E2 architecture makes the Databricks platform on AWS more secure, more scalable, and simpler to manage. Multi-workspace accounts: Create multiple workspaces per account using the Account API 2.0.Ĭustomer-managed VPCs: Create Databricks workspaces in your own VPC rather than using the default architecture in which clusters are created in a single AWS VPC that Databricks creates and configures in your AWS account. In September 2020, Databricks released the E2 version of the platform, which provides: Note that some metadata about results, such as chart column names, continues to be stored in the control plane. If you want interactive notebook results stored only in your cloud account storage, you can ask your Databricks representative to enable interactive notebook results in the customer account for your workspace. Interactive notebook results are stored in a combination of the control plane (partial results for presentation in the UI) and your AWS storage. Job results reside in storage in your account. Your data lake is stored at rest in your own AWS account. You can also ingest data from external streaming data sources, such as events data, streaming data, IoT data, and more. ![]() Use Databricks connectors to connect clusters to external data sources outside of your AWS account to ingest data or for storage. The compute resources for notebooks, jobs, and pro and classic Databricks SQL warehouses still live in the Classic data plane in the customer account. If you enable serverless compute for Databricks SQL, the compute resources for Databricks SQL are in a shared Serverless data plane. This is the type of data plane Databricks uses for notebooks, jobs, and for pro and classic Databricks SQL warehouses. The data plane is where your data is processed.įor most Databricks computation, the compute resources are in your AWS account in what is called the Classic data plane. Notebook commands and many other workspace configurations are stored in the control plane and encrypted at rest. The control plane includes the backend services that Databricks manages in its own AWS account. ![]()
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