* add function to convert StateTransition to LokiEntry
* add QueryResultBuilder
* update backtesting to produce result similar to historian
* make shouldRecord public
* filter out noop transitions
* add experimental front-end
* add new fields
* move conversion of api model to AlertRule to validation
* add extra labels
* calculate tick timestamp using the same logic as in scheduler
* implement correct logic of calculating first evaluation timestamp
* add uid, group and folder uid they are needed for jitter strategy
* add JitterOffsetInDuration and JitterStrategy.String()
* add config `backtesting_max_evaluations` to [unified_alerting] (not documented for now)
* remove obsolete tests
* elevate permisisons for backtesting endpoint
* move backtesting to separate dir
Backend:
* Update the Grafana Alerting engine to provide feedback to HysteresisCommand. The feedback information is stored in state.Manager as a fingerprint of each state. The fingerprint is persisted to the database. Only fingerprints that belong to Pending and Alerting states are considered as "loaded" and provided back to the command.
- add ResultFingerprint to state.State. It's different from other fingerprints we store in the state because it is calculated from the result labels.
- add rule_fingerprint column to alert_instance
- update alerting evaluator to accept AlertingResultsReader via context, and update scheduler to provide it.
- add AlertingResultsFromRuleState that implements the new interface in eval package
- update getExprRequest to patch the hysteresis command.
* Only one "Recovery Threshold" query is allowed to be used in the alert rule and it must be the Condition.
Frontend:
* Add hysteresis option to Threshold in UI. It's called "Recovery Threshold"
* Add test for getUnloadEvaluatorTypeFromCondition
* Hide hysteresis in panel expressions
* Refactor isInvalid and add test for it
* Remove unnecesary React.memo
* Add tests for updateEvaluatorConditions
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Co-authored-by: Sonia Aguilar <soniaaguilarpeiron@gmail.com>
* add test for the bug
* update backtesting evaluators to accept a number of evaluations instead of `to` to have control over the number evaluations in one place
* Implement backtesting engine that can process regular rule specification (with queries to datasource) as well as special kind of rules that have data frame instead of query.
* declare a new API endpoint and model
* add feature toggle `alertingBacktesting`
Yuri Tseretyan
Matthew Jacobson
Ryan McKinley
Alexander Akhmetov
Jo
Andreas Deininger