By Adinah Brown
Product Marketing Team Lead

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In today’s competitive landscape, delivering superior products and flawless user experiences is paramount. However, ensuring optimal performance while managing cloud costs can feel like an impossible task. Despite recruiting top talent, investing in monitoring technology, and leveraging cloud provider discounts, many organizations hit a savings glass ceiling. Thankfully, a new era of Machine Learning (ML) for FinOps has arrived, offering unprecedented cloud savings.

ML algorithms are able to constantly analyze cloud usage patterns and automatically optimize resources in real-time. This means cloud users are able to get deeper cloud cost efficiency without any manual intervention or risk to application performance.

Why ML is Your New Superpower

Incorporating ML into your FinOps strategy is the key to unlocking hidden opportunities for cost optimization, resource scalability, and risk mitigation. By doing so, you can reap the following benefits:

• Leverage Discount Opportunities Faster: Leave manual effort behind as advanced ML models surpass human capabilities. Tap into that 20-30% of your servers that are still running On-Demand and are generating a prohibitive expense. With ML, you can achieve unparalleled savings by seamlessly scaling discount commitments to match application demand.
• Maximize Savings: Break free from always hitting a limitation of accessing greater savings. By accurately anticipating future resource requirements, the ML model is able to direct the efficient scaling of resources, ensuring that just enough resource capacity is provisioned as it’s needed and released when it’s not.
• Effortless Savings: Don’t let resource limitations or a lack of advanced FinOps skills hinder your savings potential. ML-powered platforms operate in real-time, supporting the efficient utilization of cloud spend and freeing up your team to focus on core development tasks. Experience effortless savings as ML handles the optimization processes on your behalf.
• Eliminate Risk: Take the performance risk out of running applications thinly provisioned. ML-powered solutions are designed to optimize the running costs of your application while minimizing the associated risks by ensuring you always have the capacity you need, just as you need it.

Zesty’s ML-Powered Approach to FinOps

As a leader in ML-based FinOps solutions, Zesty takes pride in offering a transformative approach to optimizing cloud costs. By harnessing the power of Machine Learning, we bring a game-changing solution that revolutionizes how organizations manage their cloud expenses.

We do so by offering solutions for both compute and storage, which are built with ML algorithms to continuously match cloud resources to demand, saving cloud professionals both time and money:

• Compute Cost Optimization: Commitment Manager dynamically adapts AWS discount commitments coverage based on changing infrastructure needs. It combines the flexibility of On-Demand pricing with the discounted structure of Reserved Instances, reducing EC2 costs by up to 50% and maximizing your AWS discount commitment coverage.
• Storage Cost Optimization: Zesty Disk automatically adjusts block storage volumes in real-time, aligning with application needs. With the ability to both expand and shrink the filesystem, it not only eliminates the need to excessively over-provision but also ensures optimal performance and stability, ensuring you always have the capacity for peaks and surges in demand.

Final Words

To unlock hidden cloud savings and overcome the challenges of manual management, it’s time to embrace the power of ML in your FinOps strategy. Zesty’s ML-based solution, gives you access to an Eden of savings by optimizing compute and storage resources effortlessly while simultaneously minimizing performance risk to ensure top-notch application performance.