Deep dive into how App 360 helps reduce troubleshooting time with Anomaly Detection. With Anomaly Detection for App 360, Logz.io users can now enlist targeted automation to do more work for you - automatically monitoring and alerting any issues occurring within the specific services and microservices identified as most critical.

In this video, we walk you through the latest features of Grafana Cloud Application Observability, designed to accelerate anomaly detection and root cause analysis. Application Observability offers an out-of-the-box solution for monitoring applications and minimizing MTTR. It natively supports both OpenTelemetry and Prometheus and allows you to seamlessly unify application and infrastructure insights.

Azure MVP, Michael Stephenson (aka Mike) walks through a practical example of Azure anomaly detection and the importance of keeping an eye on costs in Azure. Using Turbo360's cost analyzer module, Mike shows us how to efficiently manage everyday expenses and save money. Mike shares a scenario where he manages a Data Gateway service on Azure within a limited budget. He then explains how changes in resource scheduling led to unexpected cost increases. Using the anomaly detection feature, he identifies the abnormal cost behavior and discusses the significance of promptly addressing such issues.

In 2018 Datadog released Watchdog to proactively detect anomalies on your observability data. But what defines an anomaly? How do you avoid false positives? At Datadog Summit London 2024, Nils Bunge, product manager at Datadog, shared the story of the creation of the first Datadog AI feature (Watchdog Alert), what we learned from it and how we applied those lessons to all the added AI functionalities across the years.

In this video, Michael Stephenson demonstrates the anomaly detection feature in Turbo360, focusing on enhancements in cost monitoring. This feature allows users to easily identify deviations in Azure costs and receive alerts when anomalies occur. It simplifies configuration, enabling daily monitoring with alerts sent to specified channels. Anomalies can be detected at both high-level and granular levels, aiding in overall Azure cost management.