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Suboptimal Architecture Selection for Azure Virtual Machines
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Suboptimal Architecture Selection for Azure Virtual Machines
Jurian van Hoorn
Service Category
Compute
Cloud Provider
Azure
Service Name
Azure Virtual Machines
Inefficiency Type
Suboptimal Pricing Model
Explanation

Azure provides VM families across three major CPU architectures, but default provisioning often leans toward Intel-based SKUs due to inertia or pre-configured templates. AMD and ARM alternatives offer substantial cost savings; ARM in particular can be 30–50% cheaper for general-purpose workloads. These price differences accumulate quickly at scale.

ARM-based VMs in Azure (e.g., Dps_v5, Eps_v5) are suited for many common workloads, such as microservices, web applications, and containerized environments. However, not all applications are architecture-compatible, especially those with dependencies on x86-specific libraries or instruction sets. Organizations that skip architecture evaluation during provisioning miss out on cost-efficient options.

Relevant Billing Model

Azure VMs are billed based on the underlying hardware architecture, instance size, and region. ARM-based VMs, identified by a "p" in the SKU name (e.g., D4ps_v5), offer significantly lower pricing than comparable x86-based instances. AMD-based SKUs (e.g., E4as_v5) are typically priced lower than Intel-based equivalents. However, Azure does not automatically guide architecture selection, so users often default to Intel SKUs out of habit or compatibility assumptions. This can lead to missed savings if workloads are architecture-flexible.

Detection
  • Run Azure Resource Graph queries to inventory current VM SKUs by architecture
Remediation
  • Assess workload compatibility with ARM or AMD architectures
  • Propose migration to ARM-based SKUs for supported workloads to reduce compute costs
  • Use AMD-based instances as an intermediate option when ARM compatibility is not feasible
  • Incorporate architecture evaluation into provisioning workflows and cost governance reviews
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