Many of today’s business services from companies such as Uber, Facebook and Twitter are running applications at “hyper-scale”, producing massive amounts of streaming data. Due to the adoption of DevOps and infrastructure monitoring automation, startups and unicorns alike are generating millions of data points per second. With this volume of data, production ops teams are no longer able to keep up with what alarms are valid, much less how to fix them. Perspica’s artificial intelligence powered analytics enables enterprises to analyze high volumes of application and infrastructure data in real-time, allowing them to keep their critical services and applications running at the speed of business. Our powerful observability and analytics solution enables TechOps and DevOps teams to improve operational performance and efficiency where hyper-scale and performance are essential. Perspica’s Incident Replay™, a time machine for telemetry and topology data, automates root cause analysis while using predictive analytics to detect early warnings and prevent outages. Simply put, Perspica consumes a company’s entire time series data stream and applies machine learning algorithms to automatically baseline system performance to identify what is normal. Using these baselines, customers have visibility into their anomalous data in real-time using Perspica’s unique heuristic anomaly detection approach. By using AI to implement an advanced alarming strategy, Perspica generates only actionable alarms for the metrics which represent a problem, dramatically reducing alert fatigue.