Site reliability engineers (SREs) often face challenges in keeping an organization’s sites running smoothly as the complexity of distributed systems steadily increases. With the rise of microservices, cloud-native architectures, and massive data volumes, manual monitoring and troubleshooting are no longer sustainable. SREs must navigate hurdles like alert fatigue, incident response delays, and the constant pressure to maintain system reliability.

Organizations invest heavily in robust systems, talented personnel, and sophisticated tools to ensure smooth operations. Yet, small anomalies often escape attention—minor glitches in applications, occasional lags in processes, or subtle irregularities in performance metrics. These may appear insignificant, but when left unaddressed, they can cascade into significant disruptions, leading to operational inefficiencies, financial losses, and reputational damage.

With this blog post, we continue our quarterly “What’s New” series to inform a broader audience about the latest features and improvements made to VictoriaMetrics Anomaly Detection (or simply vmanomaly). This post covers Q3'24 progress along with early Q4 to accommodate a slight shift in the publishing schedule — why not take advantage of it? Stay tuned for upcoming content on anomaly detection.

When you investigate an incident, context is everything. Let’s say you’re working on-call and get pinged in the middle of the night. You open the alert and it sends you to a dashboard where you recognize a latency pattern. But is the spike normal for that time of day? Is it even relevant? Next thing you know, you’re expanding the time window and checking other related metrics as you try to figure out what’s going on. It’s not to say you won’t find the answers.

Today, we’re excited to unveil the Anomaly Detection feature. It will enable users to create smarter alerts based on dynamic metrics, moving beyond traditional fixed-threshold alerts. It will soon be available to all our users and is currently undergoing beta testing with select users. By detecting deviations from expected patterns, Anomaly Detection will help you stay informed about critical issues without getting overwhelmed by irrelevant alerts. Let’s dig in deeper.

In the world of IoT, ensuring the reliability, efficiency, and security of connected devices is critical. As IoT devices generate massive amounts of data, detecting anomalies becomes increasingly important. Anomaly detection helps identify potential issues before they escalate, providing businesses with valuable insights and the ability to improve operational efficiency if used correctly. In this article, you will learn about some potential use cases for anomaly detection across different industries.