Domino Model Monitor is a paid platform for evaluating production machine-learning models and alerting teams when performance or data conditions deteriorate enough for review. It monitors data drift, model quality, bias, data quality, and performance metrics from a central dashboard showing model status, summaries, alerts, and monitoring results. Automated prediction-data pipelines and metric generation support ongoing oversight. When remediation is needed, users can recreate a model’s development environment, retrain with production data, and redeploy it. Models built in Python, R, SAS, MATLAB, TensorFlow, or DataRobot can be registered. The Elastic Monitoring Engine is designed to scale and ingest data from Amazon S3, Azure Blob Storage, Azure Data Lake, Google Cloud Storage, and HDFS. Domino supports web, API, and self-hosted deployment, including cloud VPCs, on-premises systems, and air-gapped environments. Pricing is available on request, with no free plan.
Who it is for
Domino positions this platform for large AI-driven enterprises and regulated industries running mission-critical AI. It suits teams needing model registries, experiment tracking, pipeline orchestration, serving, versioning, and managed compute.
What is good
- Tracks data drift and model quality
- Central dashboard with customized alerts
- Supports Python, R, SAS, MATLAB, TensorFlow
- Self-hosted and air-gapped deployment options
- Includes model registry and experiment tracking
What to know first
- Paid service with pricing on request
- No free plan
- Support terms vary by plan
- Designed primarily for large enterprises
Verdict
Domino Model Monitor combines monitoring, alerting, remediation workflows, and deployment choices for organizations managing production models. Its broad framework support and regulated-environment options are useful, but buyers must request pricing and select a support tier.
Get started with Domino Model Monitor
- Visit https://domino.ai/platform/model-monitoring.
- Choose a plan: Premium, Domino Cloud or Enterprise; pricing is available on request.
- Select web, API or self-hosted deployment, including a supported cloud VPC or on-premises environment.
- Register a model built with Python, R, SAS, MATLAB, TensorFlow or DataRobot for monitoring.
- Configure monitoring and alerts, then use production data to retrain and redeploy when needed.
Limits to know first
Premium allows up to two deployments, one production and one non-production, and up to two upgrades per year. Domino Cloud includes one deployment. Enterprise allows up to two deployments and two upgrades per year.
Questions about Domino Model Monitor
Is there a free plan?
No. Domino Model Monitor is a paid product.
Where can it be deployed?
It supports web, API and self-hosted platforms. Self-managed deployment is available in AWS, Azure or GCP VPCs, on-premises and secure air-gapped environments.
Which model frameworks can be monitored?
Models built in Python, R, SAS, MATLAB, TensorFlow or DataRobot can be registered.
What does each plan include?
Premium has five service accounts, five admin licenses, unlimited consumer licenses, up to two deployments and up to two upgrades per year. Domino Cloud has five service accounts, five admin licenses, unlimited consumer licenses, one deployment, continuous upgrades and Nexus Data Planes deployment. Enterprise has ten service accounts, ten admin licenses, unlimited consumer licenses, up to two deployments and two upgrades per year.
What security certifications and compliance support are stated?
Domino states certifications for ISO 27001, ISO 9001, SOC 2, HIPAA and GDPR, and support for 21 CFR Part 11 and Annex 11 compliance.
Domino Model Monitor plans and pricing
All plansCompared on ML experiment tracking software
- Free plan
- No
- Drift monitoring
- Yes
- Model performance metrics
- Yes
- Data quality checks
- Yes
- Bias monitoring
- Yes
- Deployment options
- hybrid
