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اشتراک گذاری
Send us a text In this conversation, Amit Saar shares his journey from software engineering at Microsoft to founding OpenOps. He focuses on the challenges and solutions in FinOps. He highlights the need for automation, accountability, and balancing innovation with governance in managing cloud costs. Amit points out the fatigue that engineering managers face due to overwhelming demands. He stresses the need for better tools and practices to streamline FinOps processes. The discussion also covers the challenges of automating FinOps, the role of no-code platforms, and the importance of community engagement through open sourcing. Topics include the fragmentation of systems in enterprises and the advantages of a no-code approach for automation. Amit discusses monetization strategies for sustaining an open-source model. The conversation wraps up with practical advice on getting started with OpenOps.…
WNiCF - Interview with Henk - Time series, forecasts and anomaly detections, all hard problems to crack.
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محتوای ارائه شده توسط The FinOps Guys - Stephen Old and Frank Contrepois, The FinOps Guys - Stephen Old, and Frank Contrepois. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط The FinOps Guys - Stephen Old and Frank Contrepois, The FinOps Guys - Stephen Old, and Frank Contrepois یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal
- We discussed the challenges of working with time series data, particularly in the context of machine learning and AI, highlighting the complexity and the need for automation in feature engineering.
- The importance of balancing accuracy and complexity in model creation was emphasized, with a focus on avoiding overfitting and ensuring models remain effective in real-world applications.
- The potential integration of business context data, such as sales data, with cloud consumption data to enhance anomaly detection and forecasting models was proposed.
- The discussion touched on the economic value of anomaly detection, with a focus on proving that early detection can lead to significant cost savings.
- The target audience for the anomaly detection system was identified as FinOps managers, who would use the system to manage cloud-related financial topics and coordinate with engineers to address anomalies.
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