As cloud computing continues to grow in popularity, so does the need for accurate cloud cost forecasting. With cloud costs being variable and unpredictable, it can be difficult to know how much you’re going to spend each month; and can lead to budget overruns and financial problems. This makes cloud cost forecasting a necessary step in owning and managing your cloud efficiently.
In simple terms, cloud cost forecasting is the process of predicting future cloud costs. By forecasting your cloud costs, you can gain visibility into your spending and make informed decisions about how to optimize your cloud resources.
Cost forecasting can be beneficial in many ways:
- Avoid budget overruns – By knowing how much you’re going to spend in the future, you can make sure that you have enough money allocated to your cloud budget.
- Reduce cost – You can see where you’re overspending and take steps to reduce your costs.
- Better business decisions – By knowing how much you’re going to spend in the future, you can make sure that you’re using your cloud resources efficiently.
There are several different methods that you can use to forecast your cloud costs. One popular choice is to use historical data to predict future trends; another method is to use machine learning (ML) to predict future costs. We combine the best of these two worlds and bring to you: ML-powered Forecasting.
Introducing Machine Learning-Powered Forecasting in VMware Tanzu CloudHealth
As a user, you have the ability to choose up to the last 12 months of historical data to forecast costs for the current month and project up to 36 months. Tanzu CloudHealth (formerly VMware Aria Cost powered by CloudHealth) factors in seasonality, periodicity, historical trends, and deviations. You also get the ability to see and compare budgets, forecasts, and actuals to understand your portfolio even better.
Features
- Integrated ML model for improved accuracy
- Short and long-term forecasting
- Customizable forecasting per business requirements
- Ability to visualize past and estimated usage trends in one place with a budget threshold
- Budget vs. actual vs. forecast depictions enable a better understanding of your portfolio
- Forecasted cost and planned budget comparison with a focus on budget deficit
You also get the ability to feed in your business knowledge in the form of a growth factor to tweak what the algorithm should receive as the input and give results accordingly. For example, you may already be expecting a new project, a new line of business or simply more business, and hence more infrastructure cost but the ML system would not know this. With Tanzu CloudHealth forecasting, you can feed in this information and then let the machine learning feature do its job of giving you its best forecasts based on the information inputted.
What can ML-powered forecasting enable you to do?
- Improve accuracy of forecasts to establish achievable budgets
- Commit to reservation and savings plans with confidence
- Provide future investment planning and innovation in the cloud
Looking Ahead
Cloud cost forecasting is the future of managing cloud. By forecasting your cloud costs, you can gain visibility into your cloud spending, make informed decisions about how to optimize your cloud resources, and reduce unwanted cloud spend.
We at VMware Tanzu CloudHealth intend to continue to improve forecasting innovations with extended filters, ability to include/exclude line items and costs, integration with budget, and much more. Stay tuned!
