# Mixing production and non-production applications in the same App Service plan Canonical: https://www.pointfive.co/efficiency-hub/inefficiencies/mixing-production-and-non-production-applications-in-the-same-app-service-plan Production and non-production applications are hosted within the same App Service Plan. By: Aaran Bhambra [Cloud Efficiency Hub](https://www.pointfive.co/efficiency-hub) # Mixing Production and Non-Production Applications in the Same App Service Plan The short version Production and non-production applications are hosted within the same App Service Plan. [Aaran Bhambra](https://www.linkedin.com/in/aaran-bhambra/) FinOps Engineer / DevOps Engineer @ WTW Azure service [Azure App Service Plans](https://www.pointfive.co/efficiency-hub/cloud-services/azure-app-service-plans) Category [Compute](https://www.pointfive.co/efficiency-hub/service-category/compute) Reference CER-0283 Type Inefficient Architecture ## Explanation Why the waste happens and who it affects. Production workloads often require higher availability, performance, or scaling characteristics, driving the plan toward larger or higher-cost SKUs. When non-production workloads share that plan, they inherit the higher cost structure even though their availability and performance requirements are typically much lower, resulting in unnecessary spend. ## Billing model The pricing dimensions that drive this cost. All applications within an App Service Plan share the same SKU and instance cost, regardless of individual workload criticality. ## How to detect 3 checks to find it in your estate. - Identify App Service Plans hosting a mix of production and non-production applications - Review whether non-production workloads are constrained by production-level sizing decisions - Assess whether environment separation is preventing appropriate right-sizing ## How to fix 3 ways to remove the waste. - Separate production and non-production applications into different App Service Plans - Size non-production plans independently using lower-cost SKUs aligned with reduced requirements - Align App Service Plan design with environment criticality and lifecycle expectations ## Documentation Vendor references for pricing and configuration. [https://learn.microsoft.com/en-us/azure/app-service/app-service-plan-manage](https://learn.microsoft.com/en-us/azure/app-service/app-service-plan-manage) [https://learn.microsoft.com/en-us/azure/app-service/environment/intro](https://learn.microsoft.com/en-us/azure/app-service/environment/intro) ## Related inefficiencies [Browse the library](https://www.pointfive.co/efficiency-hub) - Azure App Service Plans CER-0291 ### [Overprovisioned Azure App Service Plan](https://www.pointfive.co/efficiency-hub/inefficiencies/overprovisioned-azure-app-service-plan) An App Service Plan is sized larger than required for the applications it hosts. Plans are often provisioned conservatively to handle anticipated peak demand and are not revisited after workloads stabilize. Because pricing is tied to the... Compute - Azure App Service Plans CER-0404 ### [Missing Reservations for Steady Premium v3 and Isolated v2 App Service Plans](https://www.pointfive.co/efficiency-hub/inefficiencies/missing-reservations-for-steady-premium-v3-and-isolated-v2-app-service-plans) Production App Service plans on Premium v3 (or later) and Isolated v2 often run a fixed minimum instance count all year: a web front end that never scales below two or three instances, or an App Service Environment sized for a steady... Compute - Azure Functions CER-0315 ### [Orphaned Azure Function Apps with No Active Functions or Triggers](https://www.pointfive.co/efficiency-hub/inefficiencies/orphaned-azure-function-apps-with-no-active-functions-or-triggers) Azure Function apps can persist long after the applications or workflows they supported have been retired - particularly in development, testing, and experimentation environments where cleanup is often overlooked. Even when no functions... Compute --- Source: the public page above. Product screenshots and illustrative interfaces are examples, not live customer data.