In this article Compute: Matching resources to workload requirements Storage: Balancing performance and lifecycle management Networking: Improving efficiency without compromising resiliency Continuous optimization is where long-term savings happen Continue your Azure IaaS optimization journey Create a resilient infrastructure with Azure This blog post is the third part of a blog series called Azure IaaS which will share best practices and guidance to help you build a trusted infrastructure platform—from performance, resiliency, and security to scalability and cost efficiency.
As organizations modernize infrastructure, migrate mission-critical workloads, build cloud-native applications, and scale AI— cost efficiency remains a foundational principle of cloud architectures. Discover the Benefits of Azure IaaS Yet cloud costs are rarely driven by a single decision. More often, across Azure Infrastructure-as-a-Service (IaaS) environments, they are the result of many compounded architectural choices across compute, storage, and networking.
Common examples include overprovisioning infrastructure when selecting a larger virtual machine than a workload requires or keeping infrequently accessed data on premium storage, building resilient architectures that introduce unnecessary overhead, or collecting and retaining more operational data than is needed. Individually, these decisions may seem minor, but over time they can significantly impact both cost and operational efficiency.
These challenges become even more important as organizations expand AI initiatives, modernize applications, and support growing performance and resiliency requirements. The opportunity lies in addressing these inefficiencies before they become entrenched. By making informed infrastructure decisions during planning, deployment, and ongoing operations, organizations can improve resource utilization, reduce total cost of ownership (TCO), and create a more scalable foundation for future growth.
In this blog, we’ll explore some of the most common infrastructure cost challenges organizations face today and examine how Azure IaaS capabilities across compute, storage, and networking can help improve efficiency, reduce TCO, and highlight resources available in the Azure IaaS Resource Center to help you make more informed decisions. Many of the most impactful optimization opportunities originate long before a workload enters production.
To better understand where these opportunities exist, let’s examine common efficiency challenges (and solutions) across compute, storage, and networking. Compute: Matching resources to workload requirements Compute inefficiencies are often the easiest to identify because they directly affect both performance and infrastructure spend. The goal is not simply to select the lowest-cost compute option, but rather to align infrastructure resources with workload requirements while preserving flexibility for future growth.
Azure provides a broad portfolio of virtual machine options , enabling organizations to select the architecture, processor type, performance profile, and scale characteristics that best match workload needs; allowing organizations to align infrastructure investments with workload needs rather than paying for unused capacity. Equally important is taking advantage of Azure’s flexible pricing options .
Depending on workload characteristics, organizations can combine Pay-As-You-Go pricing, Azure savings plans , Azure Reservations , and Azure Spot Virtual Machines to better align costs with actual usage patterns. For highly scalable environments, services such as Azure Virtual Machine Scale Sets automatically balance compute demand with available capacity by scaling resources up or down in real time, ensuring the environment is right-sized while optimizing cost efficiency.
Azure Compute Fleet help organizations intelligently balance capacity, availability, and price-performance across large deployments; reducing the operational complexity associated with managing infrastructure at scale. The result is a compute environment that is not only cost-efficient, but also better aligned to application requirements and business outcomes.
Storage: Balancing performance and lifecycle management Storage inefficiencies often develop gradually, at times making them difficult to identify until environments reach significant scale. The key is to ensure that performance, capacity, and data access requirements remain aligned. Choose the right storage service for the workload Storage performance requirements vary dramatically across workloads.
Some applications demand consistent low-latency block storage, while others prioritize storage capacity, durability, or long-term retention. Selecting the appropriate storage service and performance tier is critical to maximizing both efficiency and value. For example: Business applications may benefit from Premium SSD v2 offerings .
Business-critical transactional databases may require Ultra Disk to meet stringent low-latency performance requirements. Large-scale block storage environments can benefit from consolidated architectures using Azure Elastic Storage Area Network (SAN) . Linux/Windows file shares, home directories, and shared storage scenarios may benefit from Azure Files or Azure NetApp Files .
Object storage workloads often benefit from the alignment between Azure Blob Storage tiers and data access patterns. Automate data lifecycle management Equally important is ensuring data remains on the appropriate storage tier throughout its lifecycle. In many environments, data access patterns change significantly over time, yet storage configurations remain static.
This disconnect often results in organizations paying for performance they no longer need. Azure Blob Storage provides capabilities that help organizations automatically align storage costs with data access patterns.
Originally published at azure.microsoft.com
