Finout, the cloud cost observability platform, today launches world’s first end-to-end anomaly detection for FinOps. Finance and engineering teams now have a single, centralized dashboard to monitor cost spikes and other unusual spending behavior across all of the major cloud providers and various 3rd party SaaS services. Combined with Finout’s virtual tagging, Finout can easily identify unwanted cost spikes by specific individuals, teams, or applications in order to reduce waste and increase profitability.
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Finout's anomaly detection improves profitability for teams. (Photo: Finout)
“Finout is cloud agnostic and can instantly identify a cost anomaly wherever it is in your tech stack,” said Roi Ravhon, CEO & Co-Founder of Finout. “There’s a big difference between cloud costs increasing because the R&D team accidentally left a staging environment running overnight, or if it’s because one of your features gained new traction and business is growing. Modern organizations that operate in the cloud need the ability to quickly know where a spending anomaly is happening and then understand why it is happening.”
End-to-end anomaly detection in the cloud is extremely complex, given the high dynamic and distributed nature of modern applications. Simply establishing what should be considered “normal” requires the use of advanced data analysis. Other factors that contribute to the complexity include the presence of multiple data sources, myriad variables that make root cause analysis difficult, and mitigating the amount of false-positives to maintain a healthy signal-to-noise ratio.
Finout uses machine learning to automatically establish baselines and expected usage of both technical resources and organizational cost allocations. Once a resource or a business unit is deviating from this baseline, Finout automatically triggers a full-context alert so that developers, operators, and finance all have everything they need to quickly investigate and stop the cost anomaly before spend grows out of control.
Key Benefits of Finout’s Anomaly Detection Solution
1. Automatic alerts on Slack or Email without the need for manual configuration
2. Native integration with the Finout MegaBill for anomalies on any virtual tag such as application, environment, or team.
3. Cloud agnostic for comprehensive analysis.
4. Complete control and visibility – only pay for necessary cloud resources and nothing more.
5. Full-context notification channeling to email and Slack.
What separates Finout from the competition is the ability to track not only all of the major cloud providers such as AWS, Google Cloud, and Microsoft Azure; but also Kubernetes, Snowflake, Databricks, Datadog, and other 3rd party SaaS services in one MegaBill. After locating an anomaly, users are able to drill in and analyze the specific issue, in order to avoid waste and reduce the average company’s cloud spend by more than 20%.
“Using Finout’s business-context capabilities, we gained new insights by breaking cost down by specific customers and features,” said Ofir Tam, Technical Product Leader at Orca Security. “This enabled us to fine-tune our tech stack for the best value and increase our profitability.”
More information: https://www.finout.io/anomaly-detection
About Finout
Finout emerged out of stealth in June 2022 with $18.5 Million in funding from Team8 Capital, Pitango First, R Squared Ventures, Jibe Ventures, Ariel Maislos and industry-leading angel investors. The platform is already being used in production within companies such as WIZ, Orca Security, Riskified, AlphaSense and many more. Finout combines all invoices across various cloud providers and services such as AWS, Datadog, Kubernetes, Snowflake and GCP into one centralized bill, enabling an unparalleled view of cloud spend in seconds, then helping FinOps, DevOps and Finance time reduce time on data gathering and analytics, reduce spend and increase profitability across all services and business units such as cost per feature or customer.
View source version on businesswire.com: https://www.businesswire.com/news/home/20230307005013/en/
Finout uses machine learning to automatically establish baselines and expected usage of both technical resources and organizational cost allocations.
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Adam LaGreca
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