Azure Databricks Workspace Architecture
We know that the Azure Databricks workspace is designed in such a way that it allows multiple teams to work together with safety and it also manages the backend services. This makes us easy to focus on your data tasks but the architecture of the workspace can vary according to the user e.g. custom setups (when we deploy Databricks to our own virtual network), the diagram shows the most common structure and data flow for Azure Databricks.
Azure Databricks has two main parts. They are
1. A Control Plane and
2. A Compute Plane
- The control plane is where Azure Databricks manages the backend services in your Databricks account. Things like notebook commands and workspace settings are stored and encrypted here.
- The compute plane is where your data gets processed. For most Databricks computations, the compute resources are in your Azure subscription, called the classic compute plane. This is the network and resources in your Azure subscription. Azure Databricks uses the classic compute plane for your notebooks, jobs, and for certain types of Databricks SQL warehouses.
How To Deploy An Azure Databricks Workspace?
Azure Databricks is an open cloud-based platform that helps organizations to analyze and process large amounts of data, build artificial intelligence (AI) models, and share their work. It is designed in such a way that it can easily handle complex data tasks at a large scale. Databricks helps user to connect with the cloud storage and security settings, so our data remains secure.
It also takes care of setting up and managing the necessary cloud infrastructure automatically. This platform help multiple teams to collaborate and work together in easy steps. Using the Azure Databricks, companies can unlock more brief knowledge about their data and create powerful applications without worrying about technical issues.
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