Release Notes
Welcome 2023! We are extremely excited for the year ahead as we continuously enhance our platform to ensure that you and your team can observe your models in production, detect issues and improve their performance as efficiently as possible.
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In this page, you'll be able to find a constantly-growing list of some of our most impactful new features and enhancements that we release every month.
- Workspaces - For enterprises and organizations which require silos for separate teams/models/data integrations... Aporia introduces workspaces (team silos) managed by Aporia account admins. For more information read our RBAC docs.
- Role Based Access Control - Full role based access control is now available in Aporia! Using account-level and workspace-level permissions, users will only have access to the data and actions for which they are permitted.
- New integrations - We've expanded our integration support and now you can receive alert notifications via your organization Teams & Webhook.
- New data source action - Deleting a data source is available by clicking on the actions button in the data connectors page
Delete existing data connector - Filters in custom metrics - In order to build your custom metric you may need to apply different data filtering in different parts of the calculation. For those cases, Aporia supports custom filtering in custom metrics. For more information and examples read our docs.
- Custom segments - Grouping segments with common logic is now available when creating / editing custom segments. Learn how to use it with our updated Custom Segment Syntax examples.
- New DDCs - For those of you who store your data in BigQuery / Azure Blob Storage, you can now directly and easily integrate it using our new data connectors.
- Value range monitor - You can now create value range monitor to get alerted when your inference data exceeds the desired range.
- Dashboard widgets - You can now control the granularity with which to plot your time series widgets.
- Multiple dashboards per model - Different users might like to get different insights on the same model. For this reason, we added support for creating multiple dashboards per model.
- Error detection for datasets - You will be able to see an indication in the relevant places across the platform in case we detected any error while trying to retrieve your datasets.
- Performance improvements - Resolved various performance bottlenecks and dramatically increased performance at scale.
- Edit versions - You can now edit existing stages by clicking on "edit" in the model versions page
Edit Training / Serving
- REST API - For those of you who would like to create automations for model integration, monitors creation, schema validation, etc. For more information read the REST API documentation.
- Default dashboard - Depending on your model type, a default dashboard will automatically be created to provide you a quick overview and insights on your first integrated version.
- Snowflake data source - For those of you who store your data in snowflake, you can now directly and easily integrate it using our new snowflake data connector.
- Bug fixes - Resolved errors raised by using special characters in version schema.
- Custom segments - You can now create custom segments using a SQL-based syntax, that empowers you to create that exact segment you wish. For more info, check out our docs.
- New custom metrics actions - Deleting a custom metric is available by clicking on the actions button in the custom metrics page
- Cross-version monitoring - We added the ability to use "all versions" in the monitors configurations. This way you can create monitors to detect issues across the unification of all model versions.
- Azure AD authentication for Postgres data source - In addition to using username & password, you can now configure your Postgres data source to use Azure AD authentication. This is available for accounts using SSO integration with Azure AD.
- New model actions - You can now rename and delete your models. Just click on the actions button in the models management page
- Ranking metrics support - [email protected], [email protected] and [email protected] are natively supported in Aporia platform and you can use them in monitors, widgets, custom metrics, etc.
- Databricks deployment over Azure - Aporia deployment over Databricks is now supported for clients using Azure as their cloud provider.
- Bug fixes & performance improvements!
Direct Data Connectors - we are happy to introduce you with our transformative technology that empowers ML teams to effortlessly monitor and track their ML models by seamlessly integrating Aporia with their production database. By directly accessing your existing data lake, you can effortlessly monitor billions of predictions at minimal cloud costs (never duplicate your data!).
Last modified 9d ago