fix cubic review

.github/workflows/codeql-analysis-go.yml

@@ -54,7 +54,7 @@ jobs:
           restore-keys: go-artifacts-${{ runner.os }}-codeql-analyze-${{ steps.go.outputs.go-version }}-
 
       - name: Initialize CodeQL
-        uses: github/codeql-action/init@8aad20d150bbac5944a9f9d289da16a4b0d87c1e  # v4.36.2
+        uses: github/codeql-action/init@e46ed2cbd01164d986452f91f178727624ae40d7  # v4.35.3
         with:
           languages: go
 

app/vmalert/rule/web.go

@@ -236,11 +236,11 @@ func NewAlertAPI(ar *AlertingRule, a *notifier.Alert) *ApiAlert {
 	return aa
 }
 
-func (r *ApiRule) ExtendState() {
-	if len(r.Alerts) > 0 {
+func (r *ApiRule) ExtendState(normalizeAlertState bool) {
+	if !normalizeAlertState && r.Type == "alerting" {
 		return
 	}
-	if r.State == "" {
+	if r.State == "" || r.State == "inactive" || r.State == "pending" || r.State == "firing" {
 		r.State = "ok"
 	}
 	if r.Health != "ok" {

app/vmalert/web.go

@@ -122,6 +122,9 @@ func (rh *requestHandler) handler(w http.ResponseWriter, r *http.Request) bool {
 			httpserver.Errorf(w, r, "%s", err)
 			return true
 		}
+		if r.URL.Path == "/vmalert/groups" {
+			rf.normalizeAlertState = true
+		}
 		// only support filtering by a single state
 		state := ""
 		if len(rf.states) > 0 {
@@ -371,16 +374,17 @@ func newAlertsFilter(r *http.Request) (*alertsFilter, *httpserver.ErrorWithStatu
 
 // see https://prometheus.io/docs/prometheus/latest/querying/api/#rules
 type rulesFilter struct {
-	gf             *groupsFilter
-	ruleNames      []string
-	ruleType       string
-	excludeAlerts  bool
-	states         []string
-	maxGroups      int
-	pageNum        int
-	search         string
-	match          [][]metricsql.LabelFilter
-	extendedStates bool
+	gf                  *groupsFilter
+	ruleNames           []string
+	ruleType            string
+	excludeAlerts       bool
+	states              []string
+	maxGroups           int
+	pageNum             int
+	search              string
+	match               [][]metricsql.LabelFilter
+	extendedStates      bool
+	normalizeAlertState bool
 }
 
 func newRulesFilter(r *http.Request) (*rulesFilter, *httpserver.ErrorWithStatusCode) {
@@ -543,8 +547,10 @@ func (rh *requestHandler) groups(rf *rulesFilter) *listGroupsResponse {
 			if !groupFound && !strings.Contains(strings.ToLower(rule.Name), rf.search) {
 				continue
 			}
+			ruleWithExtendedState := rule
+			ruleWithExtendedState.ExtendState(rf.normalizeAlertState)
 			if rf.extendedStates {
-				rule.ExtendState()
+				rule = ruleWithExtendedState
 			}
 			if !rf.matchesRule(&rule) {
 				continue
@@ -552,7 +558,7 @@ func (rh *requestHandler) groups(rf *rulesFilter) *listGroupsResponse {
 			if rf.excludeAlerts {
 				rule.Alerts = nil
 			}
-			g.States[rule.State]++
+			g.States[ruleWithExtendedState.State]++
 			filteredRules = append(filteredRules, rule)
 		}
 		if len(g.Rules) == 0 || len(filteredRules) > 0 {

docs/anomaly-detection/CHANGELOG.md

@@ -17,11 +17,11 @@ Please find the changelog for VictoriaMetrics Anomaly Detection below.
 ## v1.29.7
 Released: 2026-06-25
 
-- UI: updated [vmanomaly UI](https://docs.victoriametrics.com/anomaly-detection/ui/) from [v1.7.1](https://docs.victoriametrics.com/anomaly-detection/ui/#v171) to [v1.7.2](https://docs.victoriametrics.com/anomaly-detection/ui/#v172), see respective [release notes](https://docs.victoriametrics.com/anomaly-detection/ui/#v172) for details. Notable mentions include `api/v1/server/model` endpoint for accessing production models config and queries from UI, manually or through [AI assistant](https://docs.victoriametrics.com/anomaly-detection/ui/#ai-assistance).
+- UI: updated [vmanomaly UI](https://docs.victoriametrics.com/anomaly-detection/ui/) from [v1.7.1](https://docs.victoriametrics.com/anomaly-detection/ui/#v171) to [v1.7.2](https://docs.victoriametrics.com/anomaly-detection/ui/#v172), see respective [release notes](https://docs.victoriametrics.com/anomaly-detection/ui/#v172) for details.
 
 - IMPROVEMENT: Increased high-cardinality inference scaling by optionally scattering periodic infer jobs to reduce contention on shared resources (e.g. datasource, CPU, RAM) when `settings.n_workers > 1` and `scheduler.infer_every` is smaller than the total time to fetch and process all queries. This is controlled by new `scatter_infer_jobs` boolean argument of [Periodic Scheduler](https://docs.victoriametrics.com/anomaly-detection/components/scheduler/#parameters-1) (default: `false`).
 
-- IMPROVEMENT: Optimized internal batching for reader post-fetch series processing, exposing reader processing queue depth (`vmanomaly_reader_processing_tasks_queued` [metric](https://docs.victoriametrics.com/anomaly-detection/components/monitoring/#reader-behaviour-metrics)), and clarifying inference skip logs after data fetch timeouts. See `series_processing_batch_size` argument of [VmReader](https://docs.victoriametrics.com/anomaly-detection/components/reader/#vm-reader) and [VLogsReader](https://docs.victoriametrics.com/anomaly-detection/components/reader/#victorialogs-reader) for details.
+- IMPROVEMENT: Optimized internal batching for reader post-fetch series processing, exposing reader processing queue depth, and clarifying inference skip logs after data fetch timeouts.
 
 - IMPROVEMENT: Refined `VmReader` and `VLogsReader` logging after datasource request failures by suppressing the follow-up generic "No data" or "No unseen data" warning for failed fetches. Failed requests now keep the original datasource error while empty successful responses still emit the no-data warning.
 

docs/anomaly-detection/components/reader.md

@@ -893,19 +893,6 @@ If a path to a CA bundle file (like `ca.crt`), it will verify the certificate us
 (Optional) Password for authentication. If set, it will be used to authenticate the request.
             </td>
         </tr>
-        <tr>
-            <td>
-
-<span style="white-space: nowrap;">`series_processing_batch_size`</span>
-            </td>
-            <td>
-
-`8`
-            </td>
-            <td>
-Optional argument {{% available_from "v1.29.7" anomaly %}}, allows specifying the number of time series to process together while preparing data for fit or infer stages. Defaults to `8`. Suggested values are 4-16 for high-cardinality queries.
-            </td>
-        </tr>
     </tbody>
 </table>
 
@@ -924,7 +911,6 @@ reader:
   # tenant_id: '0:0'  # for cluster version only
   sampling_period: '1m'
   max_points_per_query: 10000
-  series_processing_batch_size: 8
   data_range: [0, 'inf']  # reader-level
   offset: '0s'  # reader-level
   timeout: '30s'