databricks-cloud-arch

Designing a Databricks cloud architecture involves mapping out networking, security, IaC, storage, and governance to enable scalable lakehouse deployments. This includes defining VPC/VNet structures, PrivateLink patterns, and Hub-Spoke topologies for your workspaces.

Setting up Databricks network security requires a Hub-Spoke topology with PrivateLink patterns to secure connectivity. This approach isolates traffic and provides managed network boundaries for PoC to production environments across AWS and Azure.

Structuring Terraform modules for Databricks involves separating IaC for networking, workspaces, Unity Catalog, and security controls. This enables automated CI/CD pipelines and remote state management across Dev, STG, and PRD environments.

Yes, you can use Unity Catalog for multi-workspace governance across AWS and Azure. It provides a centralized metastore strategy and environment separation to manage compliance and access controls effectively.

Yes, this approach supports disaster recovery and cost optimization through dedicated failover planning and replication strategies. It also leverages Serverless compute options and specific storage cost patterns to optimize lakehouse operations.

Compliance and security controls for a regulated Databricks environment require IAM/Entra ID integration, customer-managed key (CMK) encryption, and specific compliance profiles. These guardrails ensure your infrastructure meets stringent audit requirements.