Explore spike detection techniques for alert correlation in large-scale microservices architectures through this SREcon21 conference talk. Delve into LinkedIn's approach to identifying root causes during production outages amidst thousands of interconnected services. Learn about the challenges of distinguishing genuine issues from false positives in a complex alert landscape. Discover how LinkedIn implemented anomaly detection using Modified Z-Score and Median Absolute Deviation (MAD) to streamline their alert correlation system. Gain insights into practical applications, challenges faced, and results achieved in reducing false escalations and minimizing issue resolution time. Understand the nuances of correlation versus causation in the context of microservices monitoring and troubleshooting.