How Cloud Cost Optimization is Economically Imperative 

How is cloud cost optimization impacting your business

Part of the popularity of public clouds is the “pay as you go” model that only charges for the resources you use, or at least those you reserve. While this may seem beneficial,  it can actually result in unnecessary costs if not managed correctly. The challenge is that cloud infrastructure is multivariate and thus difficult to intuitively understand. In addition, as infrastructure expands, it becomes even more complex and opaque. In order for enterprises to run their applications without wasteful spending, cloud cost optimization is essential.

Not planning for cloud cost optimization will negatively impact your business. As you expand your workload, your cloud spend is going to grow. If you don’t have an optimization system in place, you can face cost overruns, hinder your application performance, and have unnecessary cloud spend such as costs incurred by idle resources. 

Now saving money makes intuitive sense, but there is more to cloud cost optimization. Cost optimization in cloud environments needs to balance reducing cost and maximizing the performance of applications and infrastructure. That means that while saving money, you are also making sure that your app is running well and most efficiently making money (or at least not losing money).


In the cloud, the environment changes constantly and oftentimes there is not a certain person allocated to make all decisions on how to manage cost. Add to that the complexity of modern cloud systems and actually figuring out where all the expenses are coming from can be challenging. This is why a cloud cost optimization plan needs to be executed. 

Some factors to consider when creating an optimization plan:

  • Monitoring (or rather lack thereof)
    • Application performance – e.g. Saving on larger VMs when it impacts app performance is a poor trade-off.
    • Resource utilization – e.g. You want to be aware of both idle machines and those that are nearing capacity.
    • Costs – To keep track of who is spending what and which components are generating specific costs.
  • Use of scaling (up and down, horizontal and vertical) – Static infrastructure with changing loads results in underutilized capacity or over capacity problems or both. 
  • Leveraging automation appropriately – Having engineers manage automatable management tasks is poor value as those engineers could be better spending that time adding features or improving efficiencies.
  • Avoiding treating cloud resources like traditional IT infrastructure – The desire to “own” infrastructure permanently is an antipattern for cloud systems.  This is the pets vs cattle analogy that is often referenced in cloud systems. And if your engineers are keeping under or unused pet servers, you are losing money.
  • Understanding value vs. cost –  Yes, you want to save money, but more importantly, continue to make more money.  Sometimes more spending actually increases your ability to make more.  Don’t confuse cost savings with value.
  • Setting limits on system parameters – Infrastructure types and on specific system costs, potentially distributed as team or business unit quota limits.


  • Enhanced performance: if your application runs out of instances, this will slow down your performance and impact your end-user experience. 
  • Costs will decrease: once you start provisioning your application efficiently, you will eliminate extra cloud spend that was once used on extra resources.

So, what’s the point?

By not optimizing their cloud cost businesses are not using their resources efficiently. Cloud cost optimization allows enterprises to run their applications at acceptable or minimal cost while also maximizing performance based on business objectives. Cloud cost optimization is not limited to simply improving cost. It also helps enterprises improve company responsibilities, security, and transparency. 

Though there are tools available from most cloud providers to monitor cloud cost. Some even can automate certain aspects of system optimization, they do not provide the benefits of Opsani. Cloud cost optimization should be at the top of enterprises’ objectives as it places enterprises on a path of success for the future. 

How Opsani performs cloud cost optimization

Opsani was built to simplify the optimization process by using a machine learning AI algorithm to automatically test and improve optimal settings while also reacting appropriately to changing environmental conditions such as increased application load. Because the AIs ability to manage multivariate probabilities and come up with the best solutions rapidly, this can translate into huge time savings for engineers. Let’s looks at some of Opsani’s features:

  • Autonomous predictive auto scaling: Opsani uses machine learning technology that uses predictive analytics to determine when applications need to scale up or scale down. Therefore users do not have to manually tune their applications and have excess resources on standby to plan for an increase in traffic demands.
  • Rightsizing your applications: Selecting the correct instance size you have to take into consideration what combo of memory and CPU will support the demand of your workload, without resulting in idle resources. Given the myriad choices from many vendors, this is another case where an AI system provides greater speed and efficiency when compared to human engineers.
  • Eliminating idle resources: Opsani will identify and remove unused resources so that you are not wasting money.
  • Scheduling: To ensure resources are being used efficiently, create a schedule to power down resources not used when traffic drops.
  • Setting Budgets: Create a budget of how much IT can spend on the cloud, this will help stay on track and reduce the risk of costs getting out of control. Again, Opsani can take care of the complexity of both the cost limitations and available infrastructure options to find the optimal resource to use.

The primary goal of Opsani’s continuous optimization engine is to make sure that your cloud system is providing the greatest value.  Opsani takes the complexity of system limits and desired business outcomes, calculates the optimal outcome, and then returns the appropriate configuration changes.   The end result of this automated process is reduced cost, improved application performance, and engineers that are freed up from toil to do interesting things for your business.  

Contact Opsani to know more about how they can help you optimize your infrastructure and cut your costs with the power of AI and ML. You can also sign up for a free trial and experience how Opsani can take your business to greater heights.