Sebastien Leger

1. Using the TICK stack? All anomalies should be tagged with the model name and I believe the UI in TICK version 1.7 can filter tagged anomalies in dashboards. 2....

1: I guess not, since this development is based on the original TICK 1.6 version and I think tagged anomalies in the UI were introduced in 1.7. We would have...

Significant changes have been introduced in the master version yesterday. You can have a look into scheduled jobs to perform regular training. This implementation is new and the documentation is...

@camAtGitHub, Hi, many thanks for your feedback! No Grafana integration yet, I will reply in private. On point 1, we've implemented "match_all" that translates to narrow down the data-set with...

@bdeam @camAtGitHub @jorgelbg : support for Grafana discussion in the community forum, https://community.grafana.com/t/metrics-forecast-and-outlier-detection-automl-automation/13906 6.x seems to use React, it's good news!

So, you want to train one model using more than one time-series, using tags to query the data set. You want to use this model for predictions (run inference) using...

Hi @daradermody, you're right. In the TICK-L we solved this scenario with a "locked" panel. Certain settings (eg the features list, bucket interval, span, forecast) cannot be changed once the...

Documentation is included in the OSS, docs/reference/* feel free to contribute. Thank you @daradermody

@daradermody Hi Dara, it's a good catch thanks! 2 things in your comment: - [ ] match_all bug, with Elasticsearch. You're right, the query should only apply to relevant feature...

the match_all logic in elastic.py will have to be changed to solve this issue, and we need a new unit test into test_elastic.py for better test coverage in this scenario.