Monitor ML applications at scale
ML models and applications are complex and opaque. Ensuring optimal model performance and reliability depends on the orchestration of countless moving parts. Deliver fast, scalable and maintainable ML applications by monitoring your ML pipelines for anomalies in:
Data preprocessing & transformation
ETL & data integrity
Pipeline workflows & tasks failures
Training & deployment
ML model accuracy & performance
ML dev issues are notoriously hard to detect
Problems in the ML application development process — from biased training sets to glitches in input features to context blindness — are notoriously challenging to identify and resolve. But while these issues don’t often throw straightforward errors or exceptions, they adversely affect the derived insights that underpin customer experience, revenue generation and streamlined operations — with significant and costly results. Monitoring multiple production models and unexpected changes in ML model performance efficiently and at scale can only be done using another set of ML algorithms: automated anomaly detection.
No integrations needed
Connect your ML application and pipeline data on the fly using one of our built-in collectors. Anodot learns the normal behavior of every single metric within minutes, and starts monitoring all incoming data in real-time.
Detect performance issues faster
With Anodot you can detect performance issues faster and identify bad ML workflows earlier. Anodot monitors billions of data events autonomously, and flags the single, scored, spot-on alerts that you need to know about right now. Relevant stakeholders are immediately notified via email, Slack, PagerDuty or even Webhook.
Adapt autonomous monitoring to your needs
There’s no need to define what data to look for or when, no manual thresholds to set up or update. Monitoring your ML application with Anodot’s AI-driven anomaly detection is completely autonomous. Advanced pipeline monitors can be easily created with Anodot’s adaptive alert dashboard.
Take your ML application monitoring to the next level
Real-time high-definition coverage
Fastest incident detection and resolution
Fully autonomous analytics