Zesty has unveiled a multicloud management platform that combines analytics with existing automation tools infused with artificial intelligence (AI) to surface recommendations that can be automatically implemented.
Company CEO Maxim Melamedov said the Cloud Insights and Automation Platform will make it simpler for IT teams to embrace best FinOps practices to rein in cloud computing costs.
Rather than constantly overprovisioning cloud computing resources, IT teams will be able to leverage analytics to optimally thin provision cloud infrastructure resources in a way that enables them to be dynamically spun up and down as needed, he added.
As more workloads shift to the cloud, IT leaders are being pressed to rein in costs. Historically, developers have always tended to overprovision IT infrastructure to ensure application availability, a habit they continue to indulge even though cloud infrastructure resources are designed to be made available as needed.
That’s an especially critical issue for any organizations that are impacted by seasonality, said Melamedov. Large amounts of cloud infrastructure resources might sit idle for much of the year just to ensure that enough IT infrastructure resources are available to handle any spike in demand for resources, he added.
At the core of the automation capabilities enabled by Zesty are two stand-alone tools that can be acquired separately. Commitment Manager and Zesty Disk make use of machine learning algorithms to optimize consumption of Amazon Web Services (AWS) resources. With the launch of Cloud Insights and Automation Platform those AI capabilities are now being extended across multiple clouds.
In comparison, the cost control tools provided by cloud service providers are simply too generic to be truly effective, said Melamedov.
It’s not clear how many organizations are embracing best FinOps practices to get a better understanding of their monthly cloud computing bills. In addition, IT teams can also correlate reduced cloud spending to lower energy costs that improve their sustainability posture, noted Melamedov.
Many organizations today find it challenging to assess the true cost of cloud computing services due to a lack of pricing transparency. The one thing that is certain is that as AI continues to advance, IT teams should be able to more easily reduce cloud costs in what are today often highly dynamic environments where changes to code being made daily can make it difficult to manage infrastructure spending.
FinOps tools will also make it easier for cloud service providers to conclusively show that the total cost of running a workload in the cloud is usually less expensive than an on-premises IT environment, said Melamedov.
Regardless of where a workload is deployed there will be a lot more focus on IT infrastructure utilization rates. IT teams during uncertain economic times are being pressed by finance teams to show a return on investment (ROI) in infrastructure. The challenge now is finding a way to go beyond dashboards that show how much is being spent to using the data to automate processes that can impact cloud computing costs before the next bill comes due at the end of the month.
