Using Automation To Optimize Azure Spend

Using Automation To Optimize Azure Spend

CloudHealth Tech Staff Cloud Tech Journalist
Published: January 07, 2020
4 Min Read

Despite the Azure Cost Management tool being good at what it does, there are still gaps in its capabilities that can prevent businesses from being able to optimize Azure spend. By using the CloudHealth platform to monitor, manage, and optimize Azure resources, businesses can be confident they only pay for what they use.

Azure users are unlikely to overspend as much as the “average” business lacking cost optimization processes because of the Azure Cost Management tool. This tool has multiple capabilities including the Azure Advisor which provides rightsizing recommendations for Virtual Machines and identifies some (but not all) resources suitable for termination. It also makes recommendations about buying reserved Virtual Machine instances to obtain a discount against pay-as-you-go pricing.

Limitations of the Azure Cost Management tool

Inasmuch as the Azure Cost Management tool is good at what it does—and will help a business go some way towards being able to optimize Azure spend—there are gaps in its capabilities. For example, although its recommendations about purchasing reserved Virtual Machine instances can help businesses reduce costs, the tool doesn’t identify under-utilized reserved Virtual Machine instances—meaning that business could be overspending on reserved instance purchases they’re not using.

Similarly, there have been issues with the Azure Advisor being unable to identify unattached disks, and failing to notice over-provisioned resources. These may be isolated issues due to misconfigurations or the complexity of configuring Azure resources, but even small oversights can add a considerable amount to how much businesses spend on Azure when unused or under-utilized resources are allowed to continue running for months on end. The total amount of overspend could be colossal.

In the cloud, you pay for what you provision, not what you use

The reason why it’s so important to have total visibility of your cloud environment in order to optimize Azure spend is that in the cloud you pay for what you provision, not what you use. Therefore, if you provision fifty Virtual Machines with more capacity than they need, you pay for the capacity you have provisioned whether you use it or not—and if you can’t see that you have fifty over-provisioned Virtual Machines, you will continue paying for the excess capacity month after month after month.

Over-provisioned Virtual Machines are the most commonly-used examples of why businesses need to optimize Azure spend because it’s the cost reduction initiative with the potential for the biggest impact on cost reduction. However, there are likely many more resources in businesses’ cloud environments that are unnecessarily driving up costs. We identified ten in our eBook “Best Practices for Reducing Spend in Azure”, but as Azure continues to expand its services, there will likely be more in the future.

10 Best Practices for Reducing Spend in Azure

Using automation to optimize Azure spend

Reducing spend in Azure may optimize your cloud environment in the short-term, but over time more unattached persistent disks, unused load balancers, and aged snapshots will build up in your inventory, causing your business to overspend once more— you’ll certainly be paying for more resources than you use. The way to remedy this situation is to use policy-driven automation to optimize Azure spend around the clock. 

Policy-driven automation consists of a system administrator applying a policy to a cloud management platform such as CloudHealth and instructing the platform to take a specific action if the policy is violated. Examples include:

  • If the projected month-to-date spend is greater than 100% of the budget, send an email notification to the budget owner.
  • If a snapshot is older than 2 months and subsequent snapshots exist, delete the snapshot and send an email notification to the owner.
  • If an asset is launched lacking a tag or with a tag that doesn’t conform to your tagging policy, stop the asset and send an email notification to the owner. 
  • If a reserved Virtual Machine instance is utilized less than 75% during the month, send an email notification for possible exchange or cancellation.

There are multiple other uses of policy-driven automation that can help businesses operate smoothly in the cloud. Policies can be applied that identify under-performing resources suitable for an upgrade, or that prevent security issues. For example, you can assign a range of IP addresses from which users are allowed to log into the Azure Cloud to prevent cybercriminals from remotely taking over your account.

Find out more about policy-driven automation for optimizing Azure spend

If your business operates in the Azure Cloud, and you have concerns you may be overspending due to a lack of optimization processes, don’t hesitate to get in touch and speak with our team of cloud experts. Our team will be happy to further explain the capabilities of our cloud management platform and organize a free demonstration of CloudHealth in action tailored to your business’s requirements.

10 Best Practices for Reducing Spend in Azure
CloudHealth Tech Staff , Cloud Tech Journalist

The CloudHealth Tech Staff team is made up of industry experts who report on trending cloud news, offer cloud management best practices, and compare products and services across the major cloud providers. As a part of CloudHealth, the CloudHealth Tech Staff come from all different backgrounds making them unique leaders in this industry.

We Think You Might Like These: