TechOps Examples

Hey — It's Govardhana MK 👋

Welcome to another technical edition.

Every Tuesday – You’ll receive a free edition with a byte-size use case, remote job opportunities, top news, tools, and articles.

Every Thursday and Saturday – You’ll receive a special edition with a deep dive use case, remote job opportunities, and articles.

Top engineers at Anthropic and OpenAI say AI now writes 100% of their code.

If you're not using AI, you're spending 40 hours doing what they do in 4.

These 100+ Claude Code hacks fix that and help you ship 10x faster.

Sign up for The Code and get:

Powered by: Jobsurface.com

Browse 691 Worldwide Jobs Here →

Looking to promote your company, product, service, or event to 48,000+ Cloud Native Professionals? Let's work together. Advertise With Us

Every product that succeeds on Azure goes through the same uncomfortable journey. What worked at a hundred users starts showing cracks at ten thousand. What held together at ten thousand collapses at a hundred thousand. The engineers who navigate this well are not the ones who built for a million users on day one. They are the ones who understood which bottleneck to solve at each stage and resisted the urge to over engineer before the problem existed.

This edition walks through the exact architectural evolution from a single VM to a system that handles one million users on Azure, with the services that make each transition possible and the reasoning behind each decision.

Every Azure deployment starts here. One virtual machine running your application and database together. It is the fastest path to production and completely appropriate when you have no users yet.

The problems are familiar. The application and database fight over the same CPU and memory. A traffic spike that exhausts CPU takes down both your app and your data layer simultaneously. There is no redundancy anywhere. When the VM restarts for a patch, your service is down.

The first fix is not scaling out. It is separating concerns.

Before adding more VMs, extract the database onto a managed service. Azure SQL Database gives you automatic backups, built-in high availability, read replicas, and automatic tuning without you managing any database infrastructure.

Azure SQL Database Business Critical tier maintains a cluster of SQL Server instances internally, providing automatic failover in under 30 seconds without any configuration. The read replica (Active Geo replication) lets you offload reporting queries and read heavy endpoints without touching the primary. This single architectural change, separating the database, is the most impactful move in the early scaling journey.

When one VM is no longer enough, the answer is not a larger VM. It is more VMs behind a load balancer. This is the transition from vertical to horizontal scaling, and Azure Load Balancer plus Virtual Machine Scale Sets is how you implement it on Azure.

VMSS spans three Availability Zones within the Azure region. A zone failure takes out at most one third of your instances. The remaining instances absorb the load and the scale set provisions replacements in the healthy zones automatically. Azure Load Balancer Standard tier distributes traffic across all healthy instances with health probe-based routing.

Your application must be stateless for this to work. Any user session data, file uploads, or in-memory state that must survive across requests needs to move out of the VM. Sessions go into Azure Cache for Redis. File uploads go into Blob Storage. The VM instances become disposable.

🔴 Get my DevOps & Kubernetes ebooks! (free for Premium Club and Personal Tier newsletter subscribers)