Azure Databricks Storage Architecture
Budget: $15 – $25 USD
I need to finalise an Azure architecture that keeps structured data safe, fast to query, and easy to grow. The heart of the design will be Azure Databricks—Delta Lake tables sitting on ADLS Gen2—but I still want a clear picture of how this storage layer should be organised, secured, and automated from day one.
The key decisions I’m wrestling with include:
• landing zones for raw, curated, and serving layers
• cluster configuration and autoscaling rules suited to my data volumes
• versioning and governance for Delta tables
• when (or if) to off-load specific marts to Azure SQL Database for BI tools
What I expect from you is an architecture blueprint I can hand to my team and build with confidence. That means a concise document or diagram set outlining the data flow, recommended Azure resources, security boundaries (RBAC, service principals, network), cost-optimised storage tiers, and a step-by-step implementation plan. If you can add sample notebooks or IaC templates (ARM/Bicep or Terraform) to jump-start the build, even better.
I’m ready to move quickly, review early drafts together, and sign off once the design meets best-practice guidelines for scalability, performance, and governance in Databricks on Azure.
The key decisions I’m wrestling with include:
• landing zones for raw, curated, and serving layers
• cluster configuration and autoscaling rules suited to my data volumes
• versioning and governance for Delta tables
• when (or if) to off-load specific marts to Azure SQL Database for BI tools
What I expect from you is an architecture blueprint I can hand to my team and build with confidence. That means a concise document or diagram set outlining the data flow, recommended Azure resources, security boundaries (RBAC, service principals, network), cost-optimised storage tiers, and a step-by-step implementation plan. If you can add sample notebooks or IaC templates (ARM/Bicep or Terraform) to jump-start the build, even better.
I’m ready to move quickly, review early drafts together, and sign off once the design meets best-practice guidelines for scalability, performance, and governance in Databricks on Azure.