April 19, 2022
If you are using Tecton with Databricks, your team’s Tecton account admins can now directly configure Databricks credentials in the UI without having to contact Tecton support. To update Databricks configuration, navigate to the Compute tab in the UI.
Read MoreFebruary 25, 2022
Tecton SDK version 0.3 has just been released and is now available. We highly recommend upgrading to version 0.3 to access new features and improvements. Note that version 0.2 of the SDK will continue to be supported until June 2022. For an …
Read MoreJanuary 31, 2022
New CLI features for release automation We typically recommend integrating Tecton with your CI/CD process to ensure the reliability of your features. The new json output and ‘apply by plan ID’ functionality enables adding more safeguards …
Read MoreJanuary 10, 2022
Feature View Filtering The Features page now includes a filter dropdown to limit results to specific Feature View types or Families. More filtering options will be coming soon. Beta SDK documentation Tecton’s SDK reference now stable and beta …
Read MoreDecember 13, 2021
Tecton SDK v0.2 and beta releases Tecton is introducing a new SDK versioning and release process, starting with the v0.2 release. This new process aims to improve the reliability of our SDK for production applications by creating separate stable and …
Read MoreNovember 29, 2021
You can now track the infrastructure costs incurred for individual FeatureViews with AWS Cost Explorer. This functionality can help you identify how to optimize your infrastructure cost with Tecton. Tags configured for a FeatureView are passed …
Read MoreNovember 21, 2021
Using an on-demand instance for the Spark driver node can make stream processing more reliable by preventing losing the entire cluster to spot termination.
Read MoreNovember 8, 2021
The new Jobs tab in the Web UI makes it easy to keep track of materialization jobs for all of your features. You can navigate to the Jobs tab by click on ‘Jobs’ in the sidebar, under the Resources section. You can then filter by date, or …
Read MoreOctober 26, 2021
Back in May, we announced the release of the Framework v2 API. After helping customers transition to the new Framework over the last 6 months, we're finally removing outdated methods from the SDK with release 0.1.0.
Read MoreOctober 21, 2021
Tecton now natively supports Array type features with Float32, Float64, Int64, and String type elements.
Read MoreOctober 15, 2021
Tecton is releasing a new Run API to be used for dry-run executing a FeatureView's transformation the same way Tecton will execute it during materialization or at feature retrieval time.
Read MoreOctober 8, 2021
cton is releasing a new API to be used for feature retrieval. For fetching features from the offline store, we've introduced the method get_historical_features. For fetching features from the online store, we've introduced the method get_online_features.
Read MoreUnfortunately, Tecton does not currently support these clouds. We’ll make sure to let you know when this changes!
However, we are currently looking to interview members of the machine learning community to learn more about current trends.
If you’d like to participate, please book a 30-min slot with us here and we’ll send you a $50 amazon gift card in appreciation for your time after the interview.
or
Interested in trying Tecton? Leave us your information below and we’ll be in touch.
Unfortunately, Tecton does not currently support these clouds. We’ll make sure to let you know when this changes!
However, we are currently looking to interview members of the machine learning community to learn more about current trends.
If you’d like to participate, please book a 30-min slot with us here and we’ll send you a $50 amazon gift card in appreciation for your time after the interview.
or
Interested in trying Tecton? Leave us your information below and we’ll be in touch.
Unfortunately, Tecton does not currently support these clouds. We’ll make sure to let you know when this changes!
However, we are currently looking to interview members of the machine learning community to learn more about current trends.
If you’d like to participate, please book a 30-min slot with us here and we’ll send you a $50 amazon gift card in appreciation for your time after the interview.
or