In the current dynamic business environment, cloud computing has emerged as the fundamental driver of innovation and scalability. As companies increasingly rely on the cloud for their business initiatives achieving cloud cost optimization remains a significant hurdle.

What is Cloud Cost Optimization?

Cloud cost optimization is the best practice to make the best use of a cloud environment, with optimum cost and efficient cloud waste management. It’s no secret that cloud cost optimization is easier said than done because of the unpredictability of a cloud environment.

Companies therefore rely on AWS cost optimization or Azure cost optimization, which provides cloud cost optimization tools that forecast monthly reports, detect anomalies and give insights on ways to attain cloud computing cost savings.

In this article, we will explore how advancements in artificial intelligence (AI) and automation are being leveraged to take cloud cost optimization to new heights.

Need to embrace AI and Automation for Cloud Cost Optimization

The recent disruption of the technology landscape by Artificial Intelligence and automation has caused quite a rippling impact in diverse sectors and it seems to continue expanding. In the past few months, the realization of the revolutionary and transformative potential of AI and automation has become apparent.

In 2024, companies are confident in making significant investments in AI capabilities. Many industries are in the process of AI integration with their products and services to market while managing unplanned budgetary expenditures to meet the new demand. This sudden increase in demand has also created a need to upgrade the cloud capabilities with effective cloud computing cost savings.

According to a recent Forbes survey, 63% of executives believe AI increases revenues, and 44% see how AI has reduced costs so it is high time to leverage AI and automation for effective cloud cost optimization in 2024.

Unleashing the power of AI and Automation for Cloud Cost Savings

For the business to stay relevant in the market, companies must manage different facets to near to perfection which often takes a toll and results in a lack of clarity. At times, businesses have huge demands in terms of deadlines and release cycles. There are times when there is a lack of time or human resources to monitor cloud consumption and trends around their cloud usage along with completing their essential day job. Such activities are crucial in the cloud environment to ensure cloud cost savings. In fact, for certain activities, AI can bring much better outcomes as compared to a team of people which makes investment in AI a very good bet and an intelligent step for ensuring cloud cost savings.

Enhanced AI and automation integration can prove to be the best weapon for effective cloud cost optimization in 2024. Here is how:

1. AI enabled cloud analytics - AI and automation are designed in a way to analyze patterns, and algorithms to use the data for accurate results. Artificial Intelligence can easily learn and comprehend past data and use that information to maximize cloud cost savings. AI is well-equipped to analyze cloud cost analytics and provide insights ahead of time.
2. Identifying Right Sizing Opportunities- Forecasting the cloud usage by manual intervention does not provide complete accuracy. As the computer or disk usage scales up or down, AI can adjust the resources according to real-time application needs, right-sizing instance types to workload needs. By using automation, elimination or downsizing of instances can be done automatically without manual changes and configurations.
3. Dynamic resource scaling- This enables us to understand the reason for the increase in cloud usage, a projected spike in traffic, or forecast what cloud infrastructure will be required without wasting cloud resources. So AI can be useful in forecasting resource scaling without affecting the business efficiency due to unpredictability.
4. Cloud monitoring- Manually analyzing data points without losing accuracy can be a daunting task. Moreover, the resources engaged in monitoring can be better utilized for other tasks. Using AI, cloud monitoring can be accurately done 24/7 and measure cloud usage in real-time. This results in significant cloud computing cost savings.
5. Managing Elastic Block Storage- With the help of AI, the unused EBS can be identified and their usage trends can be predicted.
6. Spotting Anomalies - Abnormal cost patterns are easily identified and rapidly escalated by trigger alerts. This ensures cloud computing cost savings.
7. Improved overall efficiency - Integration of AI and automation into the process of cloud cost optimization accelerates the overall business efficiency. By reducing the need for manual intervention, the probability of human errors is also diminished and elevates the overall accuracy in cloud cost optimization.
8. Automated Resource Tagging - By implementing automation in cloud related activities, tagging of cloud resources can be done efficiently. Automated resource tagging ensures that cloud costs are accurately tracked and ensures effective cloud cost savings.

Cloud cost optimization is a challenging task. Integrating artificial intelligence and automation tools to manage this workload can be useful.