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The Cost Optimisation pillar of the Azure Well-Architected Framework focuses on maximising the value of your cloud spend. It is not about spending as little as possible — it is about ensuring that every pound or dollar you spend delivers business value. Over-provisioning wastes money; under-provisioning degrades performance. The goal is to find the right balance.
Before deploying any workload, estimate its cost using the Azure Pricing Calculator. Understand the pricing model for every service you plan to use. Many teams are surprised by their first Azure bill because they did not account for data transfer, storage transactions, or log ingestion costs.
Cost optimisation is not a one-time exercise. Cloud costs change as your workload evolves, as Azure introduces new pricing models, and as usage patterns shift. Implement continuous monitoring and review processes.
Cloud resources that sit idle are wasted money. Right-size your resources, shut down what you do not need, and use autoscaling to match capacity to demand.
Azure offers multiple pricing models for the same services. Choosing the right one can save 40-90% compared to pay-as-you-go pricing.
Azure costs typically fall into several categories:
| Component | Description | Example |
|---|---|---|
| Compute | VMs, App Service, Functions, Containers | VM running 24/7 |
| Storage | Blob, Disk, File, Database storage | 1 TB of Blob Storage |
| Networking | Data transfer, Load Balancer, VPN Gateway | Egress data leaving Azure |
| PaaS Services | Managed databases, AI, analytics | Azure SQL Database DTUs |
| Licences | Windows Server, SQL Server | Included or bring your own |
Right-sizing means using the smallest resource tier that meets your performance requirements. Azure Advisor analyses your resource utilisation and recommends smaller sizes when resources are underutilised.
Example: If a Standard_D4s_v5 VM (4 vCPUs, 16 GB RAM) consistently uses less than 20% CPU and 4 GB RAM, downsize to a Standard_D2s_v5 (2 vCPUs, 8 GB RAM) and cut your compute cost in half.
Development and testing environments often run 24/7 but are only used during business hours. Use auto-shutdown schedules or Azure DevTest Labs to stop resources outside working hours:
For production workloads with predictable, steady usage:
| Commitment | Typical Savings | Best For |
|---|---|---|
| 1-year Reserved Instance | Up to 40% | Stable production VMs and databases |
| 3-year Reserved Instance | Up to 72% | Long-term, predictable workloads |
| Savings Plan | Up to 65% | Mixed compute usage across services |
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