Konrad Lalik
0a8dccc19a
* Move filtering code to generators for performance reasons Discarding rules and groups early in the iterable chain limits the number of promises we need to wait for which improves performance significantly * Add error handling for generators * Add support for data source filter for GMA rules * search WIP fix * Fix datasource filter * Move filtering back to filtered rules hook, use paged groups for improved performance * Add queriedDatasources field to grafana managed rules and update filtering logic to rely on it - Introduced a new field `queriedDatasources` in the AlertingRule struct to track data sources used in rules. - Updated the Prometheus API to populate `queriedDatasources` when creating alerting rules. - Modified filtering logic in the ruleFilter function to utilize the new `queriedDatasources` field for improved data source matching. - Adjusted related tests to reflect changes in rule structure and filtering behavior. * Add FilterView performance logging * Improve GMA Prometheus types, rename queried datasources property * Use custom generator helpers for flattening and filtering rule groups * Fix lint errors, add missing translations * Revert test condition * Refactor api prom changes * Fix lint errors * Update backend tests * Refactor rule list components to improve error handling and data source management - Enhanced error handling in FilterViewResults by logging errors before returning an empty iterable. - Simplified conditional rendering in GrafanaRuleLoader for better readability. - Updated data source handling in PaginatedDataSourceLoader and PaginatedGrafanaLoader to use new individual rule group generator. - Renamed toPageless function to toIndividualRuleGroups for clarity in prometheusGroupsGenerator. - Improved filtering logic in useFilteredRulesIterator to utilize a dedicated function for data source type validation. - Added isRulesDataSourceType utility function for better data source type checks. - Removed commented-out code in PromRuleDTOBase for cleaner interface definition. * Fix abort controller on FilterView * Improve generators filtering * fix abort controller * refactor cancelSearch * make states exclusive * Load full page in one loadResultPage call * Update tests, update translations * Refactor filter status into separate component * hoist hook * Use the new function for supported rules source type --------- Co-authored-by: Gilles De Mey <gilles.de.mey@gmail.com>
Next generation alerting (ngalert) in Grafana 8
Ngalert (Next generation alert) is the next generation of alerting in Grafana 8.
Overview
The ngalert package can be found in pkg/services/ngalert and has the following sub-packages:
- api
- eval
- logging
- metrics
- models
- notifier
- schedule
- sender
- state
- store
- tests
Scheduling and evaluation of alert rules
The scheduling of alert rules happens in the schedule package. This package is responsible for managing the evaluation
of alert rules including checking for new alert rules and stopping the evaluation of deleted alert rules.
The scheduler runs at a fixed interval, called its heartbeat, in which it does a number of tasks:
- Fetch the alert rules for all organizations (excluding disabled)
- Start a goroutine (if this is a new alert rule or the scheduler has just started) to evaluate the alert rule
- Send an
*evaluationevent to the goroutine for each alert rule if its interval has elapsed - Stop the goroutines for all alert rules that have been deleted since the last heartbeat
The function that evaluates each alert rule is called run. It waits for an *evaluation event (sent each
interval seconds elapsed and is configurable per alert rule) and then evaluates the alert rule. To ensure that the
scheduler is evaluating the latest version of the alert rule it compares its local version of the alert rule with that
in the *evaluation event, fetching the latest version of the alert rule from the database if the version numbers
mismatch. It then invokes the Evaluator which evaluates any queries, classic conditions or expressions in alert rule
and passes the results of this evaluation to the State Manager. An evaluation can return no results in the case of
NoData or Error, a single result in the case of classic conditions, or more than one result if the alert rule is
multi-dimensional (i.e. one result per label set). In the case of multi-dimensional alert rules the results from an
evaluation should never contain more than one per label set.
The State Manager is responsible for determining the current state of the alert rule (normal, pending, firing, etc) by comparing each evaluation result to the previous evaluations of the same label set in the state cache. Given a label set, it updates the state cache with the new current state, the evaluation time of the current evaluation and appends the current evaluation to the slice of previous evaluations. If the alert changes state (i.e. pending to firing) then it also creates an annotation to mark it on the dashboard and panel for this alert rule.
You might have noticed that so far we have avoided using the word "Alert" and instead talked about evaluation results and the current state of an alert rule. The reason for that is at this time in the evaluation of an alert rule the State Manager does not know about alerts, it just knows for each label set the state of an alert rule, the current evaluation and previous evaluations.
Notification of alerts
When an evaluation transitions the state of an alert rule for a given label set from pending to firing or from firing to normal the scheduler creates an alert instance and passes it to Alertmanager. In the case where a label set is transitioning from pending to firing the state of the alert instance is "Firing" and when transitioning from firing to normal the state of the alert instance is "Normal".
Which Alertmanager?
In ngalert it is possible to send alerts to the internal Alertmanager, an external Alertmanager, or both.
The internal Alertmanager is called MultiOrgAlertmanager and creates an Alertmanager for each organization in
Grafana to preserve isolation between organizations in Grafana. The MultiOrgAlertmanager receives alerts from the
scheduler and then forwards the alert to the correct Alertmanager for the organization.
When Grafana is configured to send alerts to an external Alertmanager it does so via the sender which creates an
abstraction over notification of alerts and discovery of external Alertmanagers in Prometheus. The sender receives
alerts via the SendAlerts function and then passes them to Prometheus.
How does Alertmanager turn alerts into notifications?
Alertmanager receives alerts via the PutAlerts function. Each alert is validated and its annotations and labels are
normalized, then the alerts are put in an in-memory structure. The dispatcher iterates over the alerts and matches
it to a route in the configuration as explained here.
The alert is then matched to an alert group depending on the configuration in the route. The alert is then sent through a number of stages including silencing and inhibition (which is currently not supported) and at last the receiver which can include wait, de-duplication, retry.
What are notification channels?
Notification channels receive alerts and turn them into notifications and is often the last callback in the receiver after wait, de-duplication and retry.