Deepchecks Hub
Deepchecks Hub takes everything from the open
source packages and turns in into a secure, scalable
deployment that supports validating many models in
parallel.
Key Capabilities of Deepchecks Hub
Integrated Into Your Team’s Workflow
Your team doesn’t work in a sterile environment, they
want Deepchecks to fit in with the tools they already
have like: Databases and blob storage for the logged
production data, PagerDuty, Slack and similar for
alerting mechanisms, and more. These are supported
in Deepchecks Hub.
Flexible Deployment Options
Deepchecks Hub is built with various deployment
options, to take various data deployment needs into
account. Choose from On-Premises for complete
control, SaaS for convenience, or Single-Tenant SaaS
with dedicated resources for a mixture of the two.
Security and Identity Management
Your data's safety is our top priority. We use Role-
Based Access Control (RBAC) to ensure only the right
people have access to the right information. Our Single
Sign-On (SSO) feature lets users access multiple
services with just one set of login credentials. This
setting not only makes managing access simpler, but
also faster and safer.
Scalability
The deployment of Deepchecks Hub is meant for scale
and reliability. It’s built to handle a large amount of
models in parallel, and works well even as the data
scales. While Deepchecks Open-Source is meant to
contain everything you need for a small scale, the
deployment of Deepchecks Hub is No better for
production environments.
Deepchecks Hub
Continuous validation of your data and models is vital for successful ML-based systems. ML and IT teams need to
monitor model performance, resolve issues quickly, and quickly find the root cause of production issues.
Deepchecks Hub provides flexibility, customization, and continuous usage, with robust infrastructure features
build on top of the open-source version.
Our Approach
Built with Context
Deepchecks Hub works in the context of your ML, DevOps
and IT solutions. We achieved it by building our own
system on top of a rich SDK and a webhook for alerts. This
enables you to send data, configure monitors, alert rules
and trigger alerts in any 3rd party system.
Built for Scale
Our architecture uses scalable building blocks, which grow automatically as you scale
the number of models and amount of data you work with.
Real Time
When you have a production issue, you would like to get a
notification ASAP, which is exactly what Deepchecks does
for you. Deepchecks tracks your model metrics in real time
and raises alerts as they happen.
Secure
with the following security and privacy table stakes:
Single Sign On
Using “social login” (via
google) or your enterprise
SSO (Via SAML)
Data Privacy
Keeping your data
encrypted on transit and
at rest
Data Separation
A multi-layered architecture
ensures that customers data
is kept separate
Secure SDK
Gives you the capability to
extend our system in a
secure way
Open Source & Community
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