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How automation is helping to control cloud costs

cloud-automation

The promise of the public cloud is driving companies to invest vast amounts of resources in cloud initiatives – not always with the expected results. In this post, we discuss the challenge of managing cloud costs, the drawbacks of a manual approach and the reasons an automated approach is the answer.

The chaos of cloud costs

In their ongoing drive for digital innovation, organizations waste large amounts of money on inefficient use of the public cloud. The potential for transformative operational efficiency and innovation is driving cloud spend ever higher, but the 2021 State of the Cloud Report reveals that cloud budget overruns average 24%.

The shift from a Capex (capital expenditure) to an Opex (operational expenditure) cost model for IT spending and a lack of robust cost governance systems are among the reasons why cloud spending can easily escalate without delivering the anticipated results.

Companies new to the cloud must also contend with a variety of discount plans, hugely detailed bills and complex options for deploying workloads that can lead to overprovisioning. Taking all these changes into account, embracing the cloud can be a costly move for organizations without effective cloud cost optimization strategies.

The manual approach to cloud cost management

Organizations know they are in trouble with their cloud spending, and many are intent on doing something about it. In fact, IDC predicts that through 2022, companies aware that at least 20% of their public cloud spending is wasted intend to halve their cloud waste by investing more in public cloud cost management.

Devising a plan to manage your cloud costs is a complex process with multiple steps:

  1. Identify where waste is occurring by tracking where costs are incurred.
  2. Determine which costs are likely to recur in a predictable way.
  3. Earmark these workloads for your cloud provider’s commitment discount plan.
  4. Find costs that can be eliminated (e.g., unused instances left running).
  5. Get recommendations on right-sizing instances that may have been overprovisioned.
  6. Make educated predictions of your future cloud requirements and plan how to deliver that capacity.
  7. Negotiate cloud compute discounts with your providers for compute commitments.
  8. Ensure that your system of cloud cost governance is watertight.

And you still can’t sit back and wait for those slimmed-down cloud bills to arrive: Analyzing your usage, gaining insights from it, applying appropriate cloud infrastructure changes, researching pricing plans and all the other work associated with cloud cost optimization is an ongoing process that is prone to human error and particularly time-intensive.

But there is an approach to controlling cloud costs that takes the hard work and potential for human error out of it: cloud cost automation.

The automated alternative

As soon as you opt for the automation route to cloud cost control, you start saving money. Simply reducing the amount of time spent manually managing cloud costs creates savings because not only are you freeing your staff to work on the features and products that will attract and retain customers, you are also helping to eliminate human error – meaning less time wasted on diagnosing and debugging.

Automation makes light work of processing and interpreting data to make and implement informed recommendations. Rather than attempting to analyze previous usage and forecast future requirements internally, you can rely on automated technologies to match your requirements to the most cost-efficient instance types and sizes available. If you start to use more or less compute resources than you predicted, commitments moved to your account can be adjusted.

The process is seamless and dynamic, with all changes happening in real time to maximize your cloud cost optimization opportunities. This is how it works with DoiT’s Flexsave.

Flexsave uses customers’ Google Cloud and AWS billing data to analyze patterns in on-demand resource utilization so it can customize the appropriate blend of DoiT's wholesale SPs, RIs and CUDs for each customer’s billing account. When usage changes,  Flexsave adjusts the configuration of compute discounts to optimize savings.

For customers with unpredictable resource needs, this kind of flexibility is invaluable and virtually impossible to achieve without automation. Take a company like NiceHash, a global hash power marketplace where buyers and sellers of computing power traders connect to mine cryptocurrencies.

Cryptocurrency mining is an ever-growing, ever-moving industry, where changes in demand are frequent, steep and unpredictable. To complicate matters, the hardware needed to process cryptocurrency mining is state of the art, requiring continuous changes in the number of virtual machines and upgrades to the latest, cutting-edge machines as they appear. These requirements make it impossible for NiceHash to leverage Google Cloud Committed Use Discounts (CUDs) because they would have to commit to a specific processor type.

That’s where Flexsave comes in. As Denis Tomasevic, NiceHash’s head of infrastructure and security, explains “With Flexsave by DoiT, we maximize our performance by having the flexibility to switch machines whenever we need, while realizing CUD discounts on those machines at the same time!”

Cloud cost optimization automation in practice

The ideal technology for cloud cost optimization automation does not tie you to any of the main cloud providers’ compute commitments. This offers immense relief for most organizations, given the costs that could accrue from committing yourself to a specific discount plan for up to three years, regardless of how your usage changes. Flexsave, for example, will adjust your discounts according to your usage without ever binding you to a specific commitment.

There is no risk associated with a good cloud cost optimization product. Even if your usage spikes or plummets, you should have no fears about overpaying for unexpected extra capacity or paying for underutilized resources. The right automation mechanism will provide access to compute discounts, so you don’t have to worry about capacity planning.

Possibly the biggest benefit robust automation can deliver is the peace of mind you get knowing that your cloud cost management is under control without you having to spend time worrying about it.

The future of cloud cost control

Buying compute commitments from your cloud provider can reduce your compute costs significantly, but choosing the right ones and managing them properly is difficult to get right. You may have to buy reservations from different providers, and there is no guarantee you won’t be left with unused resources or forced to purchase instances on-demand to meet spikes in demand.

Flexsave automates the process, dynamically maximizing your cloud-compute discounts for AWS and Google Cloud without any of the risks or limitations of long-term use commitments. Customers generally save the equivalent of a 1-year commitment discount on their cloud-compute spend with on-demand access to DoiT International's wholesale inventory of AWS Savings Plans and Reserved Instances and Google Cloud’s Committed Use Discounts.

Attempting to control cloud costs manually defies the spirit of the cloud, intended as a spark for agility, innovation and technological cost-effectiveness. Relying on manual methods of cloud cost management compromises your ability to serve your customers and mires your teams in tedious, uninspiring work. However, when you start to replace manual intervention with automation, you accelerate your processes, maximize your savings and free your teams to focus on developing the products and features your customers want.

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