Cloud Pro: Azure Databases: Choose, Compare and Launch

What's inside

1. Level 1: The Azure Database Map: Every Service on One PageFree
   Learners group every Azure database service by type (relational, distributed SQL, key-value and document, wide-column, in-memory, graph and time series, migration), note each one's current and former names, and flag which are retiring or closed to new projects, such as Azure Cosmos DB for PostgreSQL and Azure Cache for Redis.
2. Level 2: The Standard Workload ProfileFree
   Learners build a reusable workload profile covering data model, read/write mix, QPS and latency, transactions and consistency, size and growth, scaling and sharding, availability with RPO and RTO, multi-region, engine compatibility and licensing, OLTP versus analytics, team skills and cost model. Every later lesson tests services against it.
3. Level 3: Azure SQL Database: vCore, DTU and Service Tiers
   The nine-part lesson for single Azure SQL Database: the DTU and vCore purchasing models, the General Purpose and Business Critical tiers, the limits that bite, cost levers, the shared responsibility split, and a quick start with the Azure CLI and Bicep that you connect to, query and then delete.
4. Level 4: Azure SQL Hyperscale, Serverless and Elastic Pools
   Learners cover the scale and elasticity options for Azure SQL Database: the Hyperscale architecture and how far it grows, serverless auto-pause and auto-scale, and elastic pools for many databases. Each comes with its limits, cold-start and cost trade-offs, and a quick start.
5. Level 5: Azure SQL Managed Instance
   The nine-part lesson for SQL Managed Instance: near-full SQL Server compatibility (SQL Agent, cross-database queries, CLR, Service Broker), VNet-only deployment, slow provisioning and scaling, instance pools, pricing levers and a quick start with Terraform or Bicep.
6. Level 6: SQL Server on Azure Virtual Machines
   The nine-part lesson for running SQL Server yourself on Azure VMs: full control and full operational load, the SQL IaaS Agent extension, VM and disk sizing for IOPS, licensing options, availability groups, and a quick start from a marketplace image.
7. Level 7: Azure Database for PostgreSQL Flexible Server
   The nine-part lesson for PostgreSQL flexible server: Burstable, General Purpose and Memory Optimized tiers, supported versions and extensions, zone-redundant HA, read replicas, storage and IOPS limits, PgBouncer, pricing levers and a quick start with CLI, Bicep or Terraform and psql.
8. Level 8: Distributed PostgreSQL: Elastic Clusters and What's Closed
   Learners cover scale-out PostgreSQL on Azure: elastic clusters in Azure Database for PostgreSQL, built on the Citus extension, and choosing distribution keys. They also learn why Azure Cosmos DB for PostgreSQL is no longer supported for new projects and what Microsoft recommends instead.
9. Level 9: Azure Database for MySQL Flexible Server
   The nine-part lesson for MySQL flexible server: tiers, supported versions, HA modes, read replicas, storage autogrow and IOPS options, server parameters that matter, pricing levers, and a quick start with CLI and Bicep or Terraform and the mysql client.
10. Level 10: Cosmos DB for NoSQL: RUs, Partitions, Consistency
    Learners cover the core mechanics of Azure Cosmos DB for NoSQL: request units as the currency for every operation, logical and physical partitions, choosing a partition key, hierarchical partition keys, the five consistency levels, and a quick start with the SDK.
11. Level 11: Cosmos DB Cost Levers and Global Distribution
    Learners cover how to pay for Cosmos DB: provisioned throughput, autoscale, serverless and the free tier. They also cover multi-region reads and writes, conflict resolution, limits that bite, a worked cost comparison, and a pros-and-cons verdict for the NoSQL API.
12. Level 12: Cosmos DB's Other APIs and Azure DocumentDB
    Learners check the current names and status of Cosmos DB's other APIs (MongoDB RU, Apache Cassandra, Apache Gremlin and Table) and of Azure DocumentDB, the MongoDB-compatible vCore service formerly called Azure Cosmos DB for MongoDB (vCore), with a quick start for the MongoDB-compatible option.
13. Level 13: Azure Managed Redis and the Cache for Redis Retirement
    The nine-part lesson for Azure Managed Redis, built on Redis Enterprise: its tiers, clustering, active geo-replication and modules. It also covers the retirement of Azure Cache for Redis, with creation blocked for existing customers from 1 October 2026, Enterprise tiers retiring on 31 March 2027 and Basic, Standard and Premium retiring on 30 September 2028.
14. Level 14: Azure Managed Instance for Apache Cassandra
    The nine-part lesson for Managed Instance for Apache Cassandra: real open-source Cassandra on managed VMs, hybrid clusters with on-premises datacentres, what you still tune yourself, pricing by node SKU and disk, and a comparison with the Cosmos DB for Apache Cassandra API.
15. Level 15: Graph and Time-Series Options on Azure
    Learners compare the ways to run graph and time-series workloads on Azure: Cosmos DB for Apache Gremlin, graph extensions on PostgreSQL, Azure Data Explorer and Fabric Real-Time Intelligence for telemetry, and partner-run options. Each comes with its current status, limits and a quick start.
16. Level 16: SQL Database in Microsoft Fabric, in Brief
    A short look at SQL database in Microsoft Fabric: what it is, how it replicates automatically to OneLake for analytics, how Fabric capacity billing works, and when it beats Azure SQL Database or loses to it.
17. Level 17: Oracle Database@Azure
    The nine-part lesson for Oracle Database@Azure: Oracle-run Exadata and Autonomous Database inside Azure datacentres, buying through Azure Marketplace, regional availability, network design, licensing (bring your own licence or licence included), and when it beats rehosting Oracle on VMs or moving to PostgreSQL.
18. Level 18: Azure Database Migration Service
    The nine-part lesson for Azure Database Migration Service: supported source and target pairs, online and offline migrations, the Azure SQL migration extension, PostgreSQL and MySQL migration paths, limits, costs and a quick start that migrates a sample database.
19. Level 19: High Availability, Backup and Disaster Recovery
    Learners compare HA, backup and DR across every service covered: zone redundancy, failover groups, geo-replicas, point-in-time restore, long-term retention and Cosmos DB multi-region. They map each option to measured RPO and RTO and to its cost.
20. Level 20: Security, Encryption and Access Control
    Learners set up a consistent security baseline across Azure databases: Entra ID and managed identity authentication, private endpoints, TLS, encryption at rest with customer-managed keys, Always Encrypted, auditing, and Defender for Databases.
21. Level 21: Performance Tuning Across Azure Databases
    Learn one repeatable tuning loop (measure, find the bottleneck, fix the biggest cost, measure again) and apply it with each service's own tools: Query Store and automatic tuning on Azure SQL, pg_stat_statements and Query Performance Insight on PostgreSQL, the slow query log on MySQL, and request-unit and partition diagnostics on Cosmos DB.
22. Level 22: Fair Benchmarking of Database Options
    Design and run a benchmark that compares candidate databases fairly, using a realistic workload, matched capacity, warm-up and repeated runs, with standard tools such as HammerDB, pgbench, sysbench and YCSB alongside a replay of the real workload.
23. Level 23: A Worked Total Cost of Ownership
    Build a full, dated cost model for one workload on two or three candidate services: compute, storage, I/O, backup retention, replicas and HA, licences (including Azure Hybrid Benefit), reservations, egress, and the hours of operations work each option needs.
24. Level 24: Migration Paths: On-Premises and Other Clouds
    Plan the route from a source database to its Azure target: lift-and-shift versus re-platform versus re-architect, offline versus online cutover, and the assessment, schema conversion, data sync, validation and rollback steps for SQL Server, Oracle, PostgreSQL, MySQL, MongoDB and Cassandra sources.
25. Level 25: Building a Weighted Selection Scorecard
    Turn the standard workload profile into a weighted scorecard: criteria taken from the profile, weights agreed with stakeholders, must-have gates applied before any scoring, and evidence-based scores for each candidate Azure service.
26. Level 26: Scoring Azure Against Another Cloud
    Extend the scorecard to compare Azure's best candidate with the closest equivalent on another cloud (for example AWS or Google Cloud), using dated, sourced evidence for features, limits, SLAs, regions and prices, without favouring either provider.
27. Level 27: Trade-off Calls on Edge Cases
    Practise hard selection decisions where the obvious answer is wrong: multi-region writes with strict consistency, very small or very spiky workloads, regulated data, unusual engine features, vendor lock-in concerns and services that are retiring or closed to new customers.
28. Level 28: Final Challenge: Decision Workshop and Selection Record Exam
    Bring the whole course together in a decision workshop. Profile a realistic workload, shortlist from the full Azure database map, check limits and costs, plan HA, DR, security, benchmarking and migration, score Azure against another cloud, and finish with a one-page selection record you can defend.

Access

The first 2 levels are free with a free account. Every level, the podcast edition and the AI tutor come with All Access at £4.99/month or any Creator plan — see pricing.

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