Optimizing Azure Costs: Best Practices for Resource Allocation

Optimizing Azure costs is not a one-time activity. Learn more about how your business can utilize Azure while keeping costs low.

Table of Content

    Introduction

    Cloud computing has revolutionized the way organizations deliver and consume IT services, offering unprecedented flexibility, scalability, and agility. However, cloud computing also introduces new challenges for managing costs, as resources are provisioned and consumed on-demand, and pricing models are complex and dynamic. As one of the leading cloud providers, Azure offers a wide range of services and features to meet the diverse needs of its customers, but also requires careful planning and monitoring to optimize resource allocation and avoid overspending. 

    Azure Pricing Model

    Azure’s pricing model is based on the pay-as-you-go principle, meaning that customers only pay for the resources they use, and can scale up or down as needed. However, there are several factors that affect the total cost of Azure services, such as the type, size, and location of the resources, the duration and frequency of usage, the availability and performance level, and the licensing and support options. Azure also offers different purchasing options, such as on-demand, reserved, and spot instances, which have different pricing and billing implications. Customers need to understand how Azure charges for each service and option, and how to estimate and compare costs using tools such as the Azure Pricing Calculator and the Azure Cost Management portal. 

    Cost Management Tools

    Azure provides several tools and features to help customers manage and optimize their cloud costs, such as:

    • Azure Cost Management: A portal that allows customers to monitor, analyze, and control their Azure spending, by providing visibility into their current and forecasted costs, and enabling them to set budgets, alerts, and policies to enforce cost accountability and compliance. 

    • Azure Advisor:
      A service that provides personalized recommendations to optimize Azure performance, security, reliability, and cost, by identifying and suggesting improvements for underutilized or overprovisioned resources and highlighting opportunities to use Azure’s cost-saving features.
       
    • Azure Policy: A service that allows customers to define and apply rules and standards for Azure resources, such as naming conventions, tags, locations, sizes, and SKUs, to ensure consistency and compliance across the organization, and to prevent unnecessary or unauthorized resource creation or modification. 
    • Azure Resource Graph: A service that allows customers to query and explore their Azure resources across subscriptions and resource groups, using a powerful and flexible query language, to gain insights into their resource inventory, configuration, and dependencies, and to identify potential issues or opportunities for optimization. 

    Best Practices for Resource Allocation

    While Azure’s tools and features can help customers manage and optimize their cloud costs, organizations also need to follow some best practices for resource allocation, such as: 

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    • Aligning resource allocation with business objectives: Customers should align their resource allocation with their business objectives, such as performance, availability, security, and scalability, and prioritize the resources that are critical for achieving those objectives, while minimizing the resources that are not. 
    • Right-sizing resources: Customers should right-size their resources, meaning that they should choose the appropriate type, size, and configuration of resources that match their actual workload requirements, and avoid overprovisioning or under provisioning resources that can result in wasted or insufficient capacity. 
    • Adjusting capacity to meet demand: Customers should adjust their resource capacity to meet the fluctuating demand of their workloads, using Azure’s features such as autoscaling, which automatically adds or removes resources based on predefined rules or metrics, and elastic pools, which allow customers to share resources among multiple databases or containers, and dynamically allocate them as needed. 
    • Leveraging cost-saving features: Customers should leverage Azure’s cost-saving features, such as reserved instances, which offer significant discounts for committing to a certain amount of usage for a specific period, and spot instances, which offer steep discounts for using spare Azure capacity, with the trade-off of being evicted at any time. 
    • Deleting or deallocating unused resources: Customers should delete or deallocate unused or unnecessary resources, such as test or development environments, idle or obsolete virtual machines, or duplicate or redundant data, to free up capacity and reduce costs. 

    Comparing Azure Savings Plan vs. Reserved Instances

    Azure savings plan and reserved instances are both ways to optimize your Azure compute usage by committing to a certain amount of spend or usage for a specific period. However, they have different characteristics and advantages that suit different scenarios and needs. 

    Azure savings plan allows you to save up to 65% on select compute services by committing to a fixed hourly amount for one or three years (ex: $5/hr). You can use any eligible compute service, such as virtual machines, dedicated hosts, or Azure Premium Functions, in any region and operating system, and get the savings automatically applied to your usage. You can also change your compute configuration, such as instance size, series, or region, at any time without affecting your savings. Azure savings plan is ideal for customers who have dynamic or unpredictable workloads that need flexibility and simplicity. 

    Reserved instances are a way to save up to 72% on your compute usage by pre-purchasing a specific instance size, series, and region for one or three years (ex: Ev5 VM in US West). Reserved instances are best for customers who have stable and predictable workloads that do not change frequently. You can also use instance size flexibility to apply your reservation to other instance sizes within the same instance family group. 

    When is the best time to use Azure savings plan vs. reserved instances?

    The best time to use Azure savings plan or reserved instances depends on your workload characteristics, such as usage pattern, instance configuration, and region preference. In general, you should consider the following questions to help you decide: 

    • How long will the resource last? If you plan to use the resource for more than a year, you can benefit from either option. However, if you expect to use the resource for less than a year, you may be better off with pay-as-you-go pricing.
       
    •  What type of resource is it? If you use a variety of compute services, such as virtual machines, dedicated hosts, or Container Instances, you may prefer Azure savings plan, as it covers all eligible compute services. If you use only one type of compute service, such as virtual machines, you may opt for reserved instances, as they offer the highest savings for specific instances. 

    You also need to consider what the workload is being used for to decide what pricing model to use: 

    How can Azure savings plan and reserved instances be used together to optimize savings?

    While Azure savings plan and reserved instances are different options, they are not mutually exclusive. In fact, the optimal solution for most customers is to use a combination of both options to maximize their savings and flexibility. By investing in both options, you can save money and optimize your utilization of your offer commitments. 

    The reserved instances will be applied first, then the Azure savings plan will cover the remaining compute usage that is not covered by your reservations. This way, you get the greatest savings applied first. 

    Customer Example

    To illustrate how an online shopping company would use both Azure savings plan and reserved instances, let’s consider the following scenario: 

    An online retail company has a mix of workloads running Azure compute services, such as: 

    • A continuous integration server that runs on a D2s_v3 virtual machine in the West US 2 region. The server usage pattern is consistent and reliable and does not vary often. 
    • A globally distributed e-commerce application that runs a mix of virtual machines, container apps, and dedicated hosts in multiple regions and in different times of the day. The application’s usage pattern is variable and hard to predict, and it often changes. 
    • A backup service that runs on a B2s virtual machine in the Central US region. The backup service has a low and intermittent usage pattern and does not change frequently. 

    The company wants to optimize their Azure compute spend and gain flexibility. Here is how they would use both Azure savings plan and reserved instances: 

    • They would purchase a D2s_v3 reserved instance in West US 2 for the continuous integration server, as it is a stable and predictable workload that does not change frequently. They would choose a three-year term to get the highest savings. They would also use Azure Hybrid Benefit to save on their Windows Server license cost. 
    • They would purchase an Azure savings plan for the globally distributed e-commerce application, as it is a dynamic and unpredictable workload that needs flexibility. They would choose a one-year term and commit to fixed hourly based on historical usage. The plan would cover the virtual machines, container apps, and dedicated hosts in any region. They would also be able to change the virtual machine instance size, series, or region as needed without affecting their savings. 
    • They would not purchase any option for the backup service, as it has a low and intermittent workload that does not last for more than a year. They would pay as they go for their compute usage and save on their license cost with Azure Hybrid Benefit. 

    Continuous Cost Optimization

    Optimizing Azure costs is not a one-time activity, but a continuous process that requires regular monitoring, analysis, and adjustment of resource allocation, as well as ongoing governance and compliance. Customers should establish a cost optimization culture and framework within their organization, involving stakeholders from different departments and roles, such as IT, finance, and business, and using Azure’s tools and features to track and optimize their cloud spending. Customers should also review and update their cost optimization strategies and practices periodically, to reflect the changing needs and goals of their organization, and to take advantage of the latest Azure offerings and innovations.

    Discover how Azure Cost Confidence by Velosio can help you save at least 10% on your Azure cloud costs with our proven cost optimization strategies. Start with a free audit to identify immediate savings opportunities and take control of your cloud spending today.

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