Anodot, the autonomous business monitoring company, today announced the results of an independent survey that reveals how organizations struggle to control skyrocketing cloud computing costs of the remote workforce, even as business moves to a hybrid model.
In Q2 of 2021, Anodot surveyed more than 100 senior IT, finance, and operations leaders on their experiences managing cloud costs during the pandemic and shortly thereafter as vaccinations became commonplace and more people returned to work. The survey revealed the following:
For most organizations, cloud services and Software-as-a-Service represent a large and fast-growing share of their budgets. Cloud computing is projected to make up 14% of enterprise IT spending worldwide in 2024 ? up from 9% in 2020, according to a recent report by research firm Gartner. This will continue a trend. Gartner says that worldwide spending on public cloud services will grow 18% this year alone to a total of $304.9 billion, up from $257.5 billion in 2020.
"Cloud costs are extremely hard to track" according to Anodot Co-Founder and CEO David Drai, who said this makes it challenging for IT, finance, and operations teams to manage cash flow and set reasonable expectations for cloud usage. "Undetected mistakes often account for rising cloud costs and those glitches are not found by traditional monitoring tools used by most organizations. Given the rise in cloud costs due to digital transformation and a shift to hybrid workforce models, it is incumbent on IT leaders to use the correct tools to monitor their cloud costs."
Using traditional approaches to business monitoring for cloud costs can take days as well as waste valuable time for the engineers who need to review dashboards. Anodot's AI and ML tools speed time to detection by 70 percent, and many companies can identify cost-related issues within an hour, saving businesses hundreds of thousands of dollars. As cloud costs take up an increasingly large percentage of companies' IT spending in the move to digitalization, the speed of detection and remediation will be especially critical to financial planning.
AI-Based Cloud Monitoring and Machine Learning Are More Effective
"Within one month of deploying an AI solution, a company can cut cloud costs by 10% and provide long-lasting results that improve IT operations," said Drai. "AI-based cloud monitoring and machine learning are the most effective ways to control cloud costs, offering the ability to detect and resolve spikes in cloud usage before significant expenses are incurred. This is the most accurate technology for problematic usage before they take a toll on revenues."
To further boost cloud cost optimization, AI-based cloud cost monitoring can also forecast future cloud costs so that organizations can conduct better advance planning.
To learn more about how AI-based cloud monitoring and machine learning works, visit here: https://www.youtube.com/watch?v=UgIXjUinv54&ab_channel=Anodot
Anodot's Business Monitoring platform uses machine learning to constantly analyze and correlate every business parameter, providing real-time anomaly alerts and forecasts in their context. Fortune 500 companies, from digital business to telecom, trust Anodot's patented technology to reduce time to detection and resolution for revenue-critical issues by as much as 80 percent. Anodot is headquartered in Silicon Valley and Israel, with sales offices worldwide. To learn more, visit www.anodot.com and follow them on LinkedIn and Twitter.
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