Workload and data fit
Assess relational or non-relational needs, data volume, growth, consistency, transactions, reporting, and application dependencies.
Azure technical area · Rollitech
Azure Data Platforms
Select and operate Azure data services with attention to workload fit, identity, connectivity, protection, and cost.
Understand the service
What are Azure data platforms?
Azure offers managed relational databases, NoSQL options, object storage, and analytics services. Choosing a data platform starts with workload requirements—data shape, consistency, transaction patterns, performance, retention, and integration—not with a product name. The design must also define identity, network access, backup and recovery, monitoring, data movement, and who is responsible for the data throughout its lifecycle.
Technical design
Data-platform design areas
The architecture depends on workloads, identity, connectivity, and the operating model; there is no single design for every organization.
Azure SQL and managed databases
Review database service options, availability needs, performance characteristics, migration constraints, and maintenance responsibilities.
Storage and data movement
Plan storage account organization, access tiers, lifecycle rules, ingestion paths, integration, and data transfer controls.
Identity and network access
Use managed identity where supported, define database roles, restrict network paths, and consider private connectivity.
Protection and recovery
Set backup, retention, restore testing, and recovery expectations according to data importance and service capabilities.
Monitoring and cost
Track performance, capacity, data movement, storage growth, and consumption with clear ownership and review thresholds.
From design to operations
How Rollitech helps shape data services
We clarify scope, assumptions, and ownership before configuration, then validate the result and hand over usable operating guidance.
Understand data and workload needs
Review schemas, access patterns, transaction behavior, integrations, data sensitivity, and expected growth.
Compare suitable service patterns
Identify platform options and document trade-offs for performance, resilience, operations, and consumption.
Plan migration or implementation
Map dependencies, data transfer, security, validation, cutover, rollback, and application changes.
Prepare operations and ownership
Define monitoring, backups, access reviews, capacity checks, and operational responsibilities.
Before implementation
Data decisions that affect the platform
- What consistency, latency, transaction, and availability behavior does the application actually require?
- Which data must stay private, how is it classified, and which identities may access it?
- What restore point, retention, performance, and consumption expectations should be validated?
Choose Azure data services based on workload needs.
Discuss data shape, integrations, protection requirements, and operational ownership with Rollitech.