Azure Cloud Platform and Services
Microsoft Azure is a comprehensive cloud platform providing infrastructure, platform, and software services for building modern applications. This collection covers Azure services, deployment patterns, cost optimization, and practical cloud architecture decisions for organizations adopting Azure.
Azure Services and Strategic Use
Azure encompasses hundreds of services spanning compute, storage, networking, databases, AI/ML, integration, and analytics. Effective cloud architects understand not just what services exist, but when to use them and when alternatives are more appropriate.
Compute Services range from virtual machines for lift-and-shift migrations, to App Service for web applications, to container services and serverless options. The choice depends on workload characteristics, team expertise, and operational requirements.
Data Services include relational databases, NoSQL options, data warehousing, and analytics platforms. Each makes specific trade-offs about consistency, scalability, query patterns, and operational complexity.
Integration and Messaging services connect applications, enable asynchronous workflows, and support event-driven architectures.
Cloud Adoption and Operations
Articles in this section cover Azure service selection, infrastructure as code with Bicep and Terraform, cost management strategies, security and compliance, and operational patterns for production Azure workloads. Topics include migration strategies, hybrid scenarios, and designing for Azure’s specific capabilities.
The emphasis remains practical: understanding Azure options, making informed architectural choices, and avoiding vendor lock-in decisions made without deliberation.
Green Dashboard, Dead Application
Your application just crashed in production. Azure App Service kept routing traffic to the failing instance for ninety seconds. Users saw timeouts. Your monitoring dashboard stayed green because the web server responded with HTTP 200 while the database connection pool was exhausted.
I’ve watched this exact scenario play out at three different organizations in the past year. Each time, the post-mortem revealed the same root cause: health checks that verified the process was breathing without checking whether it could actually do its job. ISO/IEC 27001 Control A.17.2.1 exists precisely for this reason—availability is a security control, not an operational afterthought.
Your Azure SQL Backups Won't Save You (Here's Why)
“We have backups” is the IT equivalent of “thoughts and prayers.” Comforting words that mean nothing when disaster strikes. I’ve watched teams discover their Azure SQL Database backups expired just before an audit, or worse, during an actual outage. The default seven-day retention feels generous until you need data from day eight.
Compliance standards demand information backup in cloud environments, but no standard can enforce what most teams ignore: actually testing those backups. The gap between “we configured backups” and “we can restore our data” has ended careers and companies. This isn’t about checking compliance boxes. It’s about whether your business survives the next outage.
AKS Disaster Recovery: Why Your Untested Backup Will Fail
Your cluster will fail. The question is not if, but when, and whether you can recover before customers notice. Most organizations discover their backup strategy does not work during an actual outage, when recovery time matters most and manual heroics cannot save you.
If you run Azure Kubernetes Service (AKS) in production, you need a recovery plan that engineers can execute half asleep at 2 AM. We will go through what to back up, how Velero works in day-to-day operations, when Azure Backup for AKS is enough, and how to design realistic failover with measurable Recovery Time Objective (RTO) and Recovery Point Objective (RPO).
The goal is simple: repeatable recovery procedures you have already tested, not a document that looks good in Confluence but fails during an incident.
Nobody Runs Your Cleanup Script (And Regulators Know It)
“Storage is cheap” — until your data retention strategy becomes evidence in a GDPR lawsuit.
After 15+ years in enterprise software, I’ve seen this pattern in project after project: elaborate wiki documentation, a cleanup script nobody runs, and production databases growing exponentially with personal data that should have been deleted years ago. The compliance checkbox is marked, but the actual deletion never happens.
When regulators investigate, they don’t want your policy documents. They want execution logs proving deletion actually happened. Azure Storage lifecycle policies, Cosmos DB TTL, and scheduled Functions give you exactly that — automated retention that runs without human intervention, with full audit trails.