I just finished teaching my Azure Master Class for Cloud Solution Architects and wanted to provide a quick recap:
The motivation for organizing this class was three-fold:
- Like many companies, AIS has many open CSA (Cloud Solution Architect) positions that we are unable to fill. So the only solution is to take folks with a strong background in non-cloud environments (on any development stack for that matter) and “rewire” their brains for cloud computing 😊
Note – Please refer to Gartner’s cautionary note  about Azure (the only note of caution in what is otherwise a very positive report on Azure). Gartner claims that that lack of deep technical expertise is impacting adoption.
- An effective CSA needs an understanding of a broad array of key concepts. Even though new features are being added to the Azure platform every day, the key concepts of availability sets, fault and upgrade domains and managed identity don’t change that often. My goal was to discuss each of these concepts in depth along with practical tips, guidance, and pitfalls.
Note – Please refer to the list of key concepts  that I covered during this class.
- Engender a “Cloud Thinking” mindset. Cloud thinking is a mindset that goes beyond moving an existing application to the cloud (lift-n-shift) or starting out using a cloud-native service like Functions. Cloud thinking is a solution-focused approach to building cloud applications that maximizes the benefits that the cloud has to offer, including considerations like monitoring, cost, governance, HA and of course, compliance and security.
- The class spanned three intense days.
- No hands-on lab – I expected the attendees to fork the repo and work through the samples on their own time. I also encouraged attendees to review Azure Essentials before attending the class.
- I focused on building a conceptual understanding of key Azure topics. I relied on concept slides combined with focused demos.
This class would not have been possible without help from several folks:
- MK and Joe Darko for their constant support.
- Thomas Lewis (via Jeff Sandquist) offered advice to improve the class.
- Local Microsoft team in the DC area including Ashish Jaiman, Javier Vasquez, Mehul Shah and David McDonald for their valuable support.
Some Gartner clients with larger-scale implementations have reported significant challenges with Azure adoption; smaller customers may experience the same challenges, but with less severe impact. This is most often because Microsoft’s sales, field solutions architects and professional service teams did not have an adequate technical understanding of Azure. Technical support personnel may also lack adequate expertise.
Many traditional Microsoft partners are trying to transition to Azure support, but many do not do so well. Customers should be wary of solicitations from inexperienced partners.
 Key concepts
|IaaS, PaaS, SaaS
Hybrid / Appliance
Comparing Commercial Clouds / Azure Differentiators
Role of the CSA
It’s all about “Time to Value”
|Identity Essentials||Azure AD – BB, B2C, ADDS, BYO
Hybrid Identity (Pass-through, Federation, Sync)
Tenant, Management Groups and Subscriptions
Subscription Governance – Naming Conventions, Tagging,
Policies, Resource Locks
Third party – OKTA / auth0
Service Principal / Managed Identity
|Automation Essentials||Azure CLI/ Cloud Shell / Azure automation / PS
ARM fundamentals – Resource Provider / Control and Data
Plane / Templates/ Policy
Quick Start / Blueprints
|Storage Essentials||Tiering (hot, cool, archive)
Disks (Managed Disks Premium Disks
Data Transfer (Export/import, appliance), Data Box
|Networking Essentials||VNET/ Subnet
Load Balancers (Traffic Manager Application Gateway, ILB)
Traffic Filtering (NSG, NVA)
Gateway, peering (public/ private)
Network Service Endpoints
|Compute Essentials||Topology of a VM
VM Scale Set
|PaaS Essentials||Cloud Services
Serverless / Functions
Containers and Orchestration / ACI/ AKS
|Data Essentials||Cosmos DB
Azure SQL Database
Big Data / Data Bricks
ML / Cognitive APIs
|High Availability Essentials||Defensive Programming
Resilience Modeling and Analysis