Integrations
WhyLabs integrations make it possible to switch on observability for your ML model monitoring and data pipeline monitoring with less than five lines of code.
Seamless integration with your existing pipelines and tools
WhyLabs offers integrations with best-in-class technologies including Clouds, Data Sources, Deployment Managers, and Data Labeling Platforms .
Our list of integrations are growing fast but perhaps you need one that’s not listed? You can request integrations here.
clouds
AWS
Switch on WhyLabs observability in a few clicks in the AWS Marketplace. We are AWS experts, so bring your toughest ML monitoring challenges over.
DetailsDatabricks
Big data pipelines, distributed data pipelines, AutoML pipelines, Databricks model serving... all of these can be monitored today.
DetailsAzure
If you call Azure your home, switching on WhyLabs is as easy as adding three lines of code.
DetailsGoogle Cloud
WhyLabs can monitor your hybrid & multi-cloud data and ML solutions hosted on GCP.
DetailsConfluent
Monitor and log data in motion so your organization can innovate in the digital-first world.
DetailsSnowflake
Power up observability and monitoring for your AI applications running on Snowflake!
DetailsOn Premise
Plug whylogs open source telemetry agent to your custom infrastructure. For containerized architecture, use our container as a sidecar. We’ve got you covered!
Detailsgenerative AI
data sources
Modin
Those 1TB DataFrames are about to become high quality.
data and ML pipelines
Flyte / Union AI
Include monitoring in your production-grade orchestration for machine learning workflows and data processing.
DetailsZenML
Open-source data logging meets the open-source MLOps framework for creating portable, production-ready pipelines.
DetailsAirflow
Use whylogs with your Airflow plug-and-play operators to execute your ML monitoring tasks.
DetailsKedro
Add monitoring to create even more robust and scalable data pipelines built with Kedro.
Prefect
Use Prefect with whylogs for data logging and monitoring.
Dagster
Use WhyLabs with Dagster to develop and maintain assets.
deployment managers
Amazon SageMaker
MLOps platform built to work with AWS infrastructure now with fully integrated WhyLabs monitoring!
Details
Vertex AI
If you build, deploy, and scale machine learning models on Vertex, you can monitor them too!
Contact UsNimbleBox
Run fast, deploy often, and don’t forget to monitor.
feature stores
Tecton
Feature platform for real-time machine learning meets platform for real-time monitoring.
Contact Us
Hopsworks
Development and monitor machine learning models at scale with Hopsworks and WhyLabs.
data version control
Pachyderm
Automate and monitor complex data engineering pipelines.
DVC
Use data logging and version control systems for data science and machine learning projects.
data labeling platforms
Toloka
Crowd-sourced data collection and annotation can integrate with ML monitoring in WhyLabs to fix issues such as data drift.
Contact UsSnorkel
If data labeling is automated, data quality should be too!
experiment trackers
Weights & Biases
Track ML experiments, dataset versions, and monitor models in production!
Neptune AI
Add monitoring to your metadata store for MLOps with WhyLabs and Neptune.
serving architectures
Seldon
Integrate with Seldon to deploy, monitor and explain machine learning models.
notifications
ServiceNow
Resolve issues with ML models faster by integrating monitoring into your automated workflows.
Request an integration
Don’t see an integration you need? Let us know what integrations you would find useful to enable ML model monitoring in your pipeline. Have you already built an integration that you want listed on this page? Let us know using the form below.
