Plan your Azure environment for cost estimation

This article defines how to create accurate cost estimates for your Azure environment by documenting architectural decisions and service selections. A well-defined architecture is essential to create accurate cost estimates for your Azure environment. This clarity ensures that cost models reflect the actual scope of services, platform dependencies, and operational requirements. Without this foundation, estimates lack the specificity needed for effective planning and governance.

Plan your Azure architecture

An architecture plan provides the context required to estimate the total cost of ownership (TCO) in Azure. You must define both platform and workload architectures to align technical and financial planning.

1. Align architecture with business and technical requirements. Document constraints, performance expectations, and compliance needs. This alignment ensures that selected Azure services meet business goals and avoids costly rework after deployment.

2. Plan your Azure landing zone architecture. A landing zone provides the shared services and governance foundation for all workloads. This architecture enables accurate estimation of platform-level costs and operational readiness.

   • Use an Azure landing zone as the foundation for your platform architecture. Azure landing zones provide a scalable and secure foundation for enterprise environments. They include critical components such as identity, network, and governance controls. Use the guidance in What is an Azure landing zone?.

   • Start small for early-stage startups. Startups or cloud-native businesses can begin without implementing shared services, hybrid or multicloud connectivity, or on-premises identity management. Instead, implement a resource hierarchy to organize and govern resources. As your environment scales, incrementally adopt Azure landing zone components to support growth and governance.

3. Plan your workload (application) architecture. A workload architecture defines the Azure services, regions, and configurations required to meet business and technical requirements. Identify the Azure services, regions, and configurations needed to meet business and technical goals. Include dependencies, performance needs, and compliance requirements. Use the Azure Architecture Center to get ideas.

Select the appropriate Azure services

1. Define and enforce service selection standards. The services you choose directly affect both the initial deployment and long-term operational costs of your cloud environment. You must evaluate and select Azure services that best support your workload, architecture, and financial goals. Establish documented guidelines for selecting services based on common workload patterns. These standards reduce support complexity, enable volume purchasing benefits, and simplify policy enforcement. For guidance, see CAF Govern.

2. Use Azure decision guides to evaluate service options. Azure provides structured decision guides to help you navigate its extensive service catalog. These guides help you compare services based on technical fit, cost, and operational complexity. Use the Azure technology decision guides to identify the most appropriate services for your solution. This step reduces the risk of overprovisioning or selecting services that don't meet your workload needs.

3. Select managed services for cloud-native workloads. Platform as a service (PaaS) offerings reduce operational overhead by abstracting infrastructure management. These services improve scalability, security, and reliability while minimizing administrative effort. Choose managed services for new or modernized workloads unless infrastructure-level control is required for compliance, performance, or compatibility. For guidance on cloud-native design, see CAF Cloud-native for cloud-native guidance.

4. Align service selection with your migration strategy. Your migration approach determines the most suitable Azure services. For rehosting scenarios, select services that mirror your current components. For replatforming or rearchitecting, prioritize PaaS solutions that support modernization goals. If migrating from another cloud provider, use Amazon Web Services (AWS) to Azure service mapping or Google Cloud Platform (GCP) to Azure service mapping to find the right services.

Select the appropriate service tier

1. Understand service tiers. Each Azure service offers multiple service tiers (also known as SKUs) that provide different levels of performance, scalability, availability, and available features. The right tier is essential to meet workload-specific requirements with all the features needed and avoid over- or under-provisioning. There are certain features available only on specific SKUs so even if your performance data applies to lower SKU you might need some feature that is available on higher SKU. You must use your workload requirements to determine the most appropriate service tier.

2. Migrated workloads should use assessment data to select SKUs. Assessment data includes performance baselines, usage patterns, and architecture dependencies. This data maps existing workload characteristics to equivalent Azure SKUs. This mapping ensures continuity and minimizes performance regressions after migration.

   • Review the architecture component requirements gathered during the assessment phase.
   • Match CPU, memory, storage, and IOPS needs to available SKUs.
   • Identify any required features that are only available in higher-tier SKUs, even if performance needs suggest a lower tier.

3. Cloud-native workloads should use performance targets and usage estimates. Cloud-native workloads lack historical performance data. You must define expected usage patterns and performance targets to select an appropriate starting SKU.

   • Estimate user concurrency, transaction volumes, and latency requirements.
   • Select a SKU that meets these targets and validate it through performance testing.
   • Adjust the SKU based on test results for optimized cost and performance.

4. Select high-availability SKUs for critical workloads. Mission-critical and business-critical workloads require high availability and fault tolerance. You must select service tiers that support Availability Zones or zone-redundant configurations.

   • Review the service’s availability options and SLAs.
   • Select SKUs that support zone redundancy or regional failover.
   • Validate that the selected tier meets your recovery time objectives (RTOs) and recovery point objectives (RPOs).

Define a regional deployment strategy for each workload

A regional deployment strategy establishes the reliability, compliance, and recovery posture of your workloads. This strategy determines whether a workload operates in a single Azure region or spans multiple regions. You must define this strategy early to align with business continuity, compliance, and service-level expectations

1. Document the regional scope of each workload. Identify whether the workload operates in a single Azure region or across multiple regions. This decision affects latency, availability, and cost. Single-region deployments simplify architecture and reduce cost but increase risk of regional outages. Multi-region deployments improve availability and resilience but increase complexity and cost. Document the selected scope for each workload.

2. Use reliability requirements. Identify whether the workload operates in a single region or multiple regions. Define service level objectives (SLOs), recovery point objectives (RPOs), and recovery time objectives (RTOs). For more information, see Manage reliability in Azure. Manage reliability in Azure.

3. Validate compliance with regulatory and industry standards. Ensure that your deployment architecture and backup configurations meet applicable compliance requirements, such as MARS-E, HIPAA, or GDPR. Multi-region deployments might introduce data residency or sovereignty concerns. Work with your compliance team to validate that your regional strategy aligns with legal and regulatory obligations.

Estimate costs based on architecture

A cost estimate provides the financial foundation for cloud adoption planning. Accurate cost estimation supports budgeting, governance, and business case development. You must estimate costs based on your defined architecture and continuously refine those estimates to align with actual usage and business goals.

Use cost estimation tools to model architecture costs

1. Use cost estimation tooling. The Azure Pricing Calculator allows you to estimate costs for each service in your architecture. For existing workloads, use historical usage data to inform estimates. For new workloads, estimate based on projected usage and test deployments. This approach ensures that cost estimates reflect realistic consumption patterns and architectural decisions. If you use Azure Migrate, you can estimate costs for all discovered on-premises workloads.

2. Estimate operational cost. Identify required skills and training for teams to operate and support the target service model. Plan for changes in engineering practices and delivery processes that the new service model introduces. Engage stakeholders to validate assumptions and align service model decisions with business objectives.

Estimate operational costs for the target service model

1. Identify required skills and training. Determine the skills your teams need to operate and support the target architecture. Include training costs and time in your estimate. This step ensures that your teams can manage the environment effectively after migration.

2. Plan for changes in engineering and delivery processes. Evaluate how the new service model affects your current engineering practices. Include the cost of process changes, tooling updates, and stakeholder engagement. Validate these assumptions with business and technical stakeholders to ensure alignment.

Reevaluate cost estimates when projections deviate

1. Compare cost estimates to budget expectations. Review the output from the Azure Pricing Calculator and compare these cost estimates to your organization’s budget. This comparison identifies discrepancies between projected costs and financial targets. If the estimate is too high or too low, investigate the underlying causes to determine whether architectural changes are necessary.

2. Identify high-cost architectural elements. Focus your analysis on services with premium SKUs, multi-region deployments, or high consumption rates. These architectural elements often drive significant costs. Determine whether these choices are essential to meet business, performance, or compliance requirements, and document the rationale for each high-cost component.

3. Adjust the architecture to align with cost goals. Modify service selections, SKUs, or deployment regions for cost optimization. Make sure to maintain required performance and compliance levels. Perhaps you use a single region with availability zones rather than multiple regions. This adjustment process ensures that your architecture supports both technical and financial objectives. Validate each change to confirm that it doesn't introduce new risks or compromise workload requirements.

Validate assumptions through test deployments

1. Deploy representative workloads in a test environment. Test deployments provide real-world data about resource consumption and performance. This data enables you to compare actual usage to your initial cost estimates and identify any discrepancies. Deploy workloads that match your production scenarios for the best results.

2. Refine your cost model based on test results. Update your cost estimates to reflect the observed usage patterns from your test deployments. This refinement increases the accuracy of your cost model and enables more informed architectural and financial decisions. Adjust service selections, SKUs, or configurations as needed to optimize costs and performance.

Establish a cost baseline

1. Record all service selections, SKUs, regions, and estimated costs. Include this information in your cloud adoption plan. This documentation supports governance and enables future reviews.

2. Save cost estimates as a baseline. Use this baseline to monitor cost variance during and after deployment. Analyze deviations to identify optimization opportunities and improve future estimates.

Next step

Document your cloud adoption plan