11. Deploy and Serve
In this tutorial, you'll learn how to:
- Mark features as Production-Ready
- Navigate FeatureByte's Approval Flow
- Deploy it for both online and batch serving
- Deploy the refitted model from the previous tutorial
Step 1: Mark a Feature as Production-Ready¶
-
Navigate to the
FeaturesCatalog under theExperimentsection of the menu.
-
Locate the feature "NEW_APPLICATION_EXT_SOURCE_2". Click the three dots next to its current status (e.g., DRAFT)
. Change its readiness to
.

-
Confirm the change.

Note
If your catalog has an Approval Flow enabled, promoting a feature to "Production-Ready" requires approval.
Step 2: Enable the Approval Flow¶
-
Click the settings icon
next to the catalog name at the top of the screen.

-
In catalog settings, enable the 'Approval Flow' option and save changes.

-
A validation mark next to the catalog name indicates that Approval Flow is active.

Step 3: Request Production-Ready Upgrade¶
-
Search for the feature "CLIENT_Max_of_BureauReportedCredits_AMT_CREDIT_SUM_DEBT_To_AMT_CREDIT_SUMs_104w" in the Feature Catlog. Click
and confirm the readiness change.

-
This action triggers an approval request. Click
to open the request.

-
You’ll be redirected to Approve → Feature Requests → New Production-Ready Feature.

Step 4: Review Checks¶
Click the request to view all automated checks.
Note
The system runs several checks — such as compliance with default cleaning operations, validation of feature job setting, table status and backtesting to prevent training-serving inconsistencies.

If any checks fail (e.g., missing backtests):
- Click
to run a "Data Availability and Freshness Analysis". - Then click
to run a backtest.
Once complete, all checks should turn green.

Step 5: Review Feature¶
Review the feature definition and its use of tiles (partial aggregations).


Step 6: Request Review¶
When ready, click
to submit for review.
Your request now awaits approval.

Step 7: Approve and Merge Request¶
Click
to approve.

Click
to merge.
Step 8: Audit Merged Request¶
View merged requests under the Merged tab.

Step 9: Requests by batch¶
To upgrade all features in a feature list to Production-Ready.
- Go to the Feature List Catalog.
-
Click
next to
of the feature list you want to upgrade.

-
Confirm the action.

-
In the pop-up, click
.

-
You’ll be redirected to Approve → Feature Requests → New Production-Ready Feature.

-
Run further backtests if needed.

-
Once all checks passed, select all requests on each page, and then request reviews in batches.

-
Approve and merge requests.


Merged requests appear under the Merged tab.

Step 10: Deploy and Serve Feature List¶
Once all features are Production-Ready, proceed to deploy the list.
-
Initiate Deployment: Click
to initiate deployment.

-
Configure Deployment Details: Provide a descriptive name (e.g.
New Application: 308 Features from XGBoost [293 features: Loan Default Risk Assessment] by cumulative Feature Key Importance (0.95)) and associate the deployment with your Use Case for tracking.
-
View the Deployment: Click
to access the deployment in the DeploymentsCatalog under theManagesection of the menu. -
Enable the Deployment:
Locate the new deployment and select it.

Click the three dots next to the 'NEW' label and choose 'Enable.'

-
Compute a Batch Feature Table: In the
Batch Feature Tablestab, compute a batch feature table from a source table or a managed view that contains the entity ids of your use case.
Note
Online store functionality is not available in the Hosted Tutorials.
If you configured an online store, follow these steps to enable online serving:
-
Click
next to the Catalog name at the top of the screen.

-
In the
Online Servingtab, you’ll find ready-to-use Python and shell script templates for deploying REST API services.

Step 11: Deploy and Serve Model¶
Now deploy the model associated with your feature list.
-
Navigate to the
ModelsCatalog and select the model.
-
Open the
Abouttab, click
. Provide a name (e.g. New Application: XGBoost with top 308 keys)
-
Navigate to the
DeploymentsCatalog, locate your model and enable it.
-
Click the model deployment to view details.
