app/vminsert/netstorage: refactor snb rebuild

Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>

.gitignore

@@ -7,7 +7,6 @@
 .vscode
 *.test
 *.swp
-/vmdocs
 /gocache-for-docker
 /victoria-logs-data
 /victoria-metrics-data

Makefile

@@ -253,3 +253,34 @@ install-wwhrd:
 
 check-licenses: install-wwhrd
 	wwhrd check -f .wwhrd.yml
+
+copy-docs:
+# The 'printf' function is used instead of 'echo' or 'echo -e' to handle line breaks (e.g. '\n') in the same way on different operating systems (MacOS/Ubuntu Linux/Arch Linux) and their shells (bash/sh/zsh/fish).
+# For details, see https://github.com/VictoriaMetrics/VictoriaMetrics/pull/4548#issue-1782796419 and https://stackoverflow.com/questions/8467424/echo-newline-in-bash-prints-literal-n
+	echo "---" > ${DST}
+	@if [ ${ORDER} -ne 0 ]; then \
+		echo "sort: ${ORDER}" >> ${DST}; \
+		echo "weight: ${ORDER}" >> ${DST}; \
+		printf "menu:\n  docs:\n    parent: 'victoriametrics'\n    weight: ${ORDER}\n" >> ${DST}; \
+	fi
+
+	echo "title: ${TITLE}" >> ${DST}
+	@if [ ${OLD_URL} ]; then \
+		printf "aliases:\n  - ${OLD_URL}\n" >> ${DST}; \
+	fi
+	echo "---" >> ${DST}
+	cat ${SRC} >> ${DST}
+	sed -i='.tmp' 's/<img src=\"docs\//<img src=\"\//' ${DST}
+	sed -i='.tmp' 's/<source srcset=\"docs\//<source srcset=\"\//' ${DST}
+	sed -i='.tmp' 's/](docs\//](/' ${DST}
+	rm -rf docs/*.tmp
+
+# Copies docs for all components and adds the order/weight tag, title, menu position and alias with the backward compatible link for the old site.
+# For ORDER=0 it adds no order tag/weight tag.
+# FOR OLD_URL - relative link, used for backward compatibility with the link from documentation based on GitHub pages (old one)
+# FOR OLD_URL='' it adds no alias, it should be empty for every new page, don't change it for already existing links.
+# Images starting with <img src="docs/ are replaced with <img src="
+# Cluster docs are supposed to be ordered as 2nd.
+# The rest of docs is ordered manually.
+docs-sync:
+	SRC=README.md DST=docs/Cluster-VictoriaMetrics.md OLD_URL='/Cluster-VictoriaMetrics.html' ORDER=2 TITLE='Cluster version' $(MAKE) copy-docs

app/vminsert/clusternative/request_handler.go

@@ -5,6 +5,8 @@ import (
 	"fmt"
 	"net"
 
+	"github.com/VictoriaMetrics/metrics"
+
 	"github.com/VictoriaMetrics/VictoriaMetrics/app/vminsert/netstorage"
 	"github.com/VictoriaMetrics/VictoriaMetrics/app/vminsert/relabel"
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/auth"
@@ -12,7 +14,6 @@ import (
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/protoparser/clusternative/stream"
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/storage"
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/tenantmetrics"
-	"github.com/VictoriaMetrics/metrics"
 )
 
 var (
@@ -25,7 +26,7 @@ var (
 func InsertHandler(c net.Conn) error {
 	// There is no need in response compression, since
 	// lower-level vminsert sends only small packets to upper-level vminsert.
-	bc, err := handshake.VMInsertServer(c, 0)
+	bc, err := handshake.VMInsertServer(c, 0, netstorage.GetNodeID())
 	if err != nil {
 		if errors.Is(err, handshake.ErrIgnoreHealthcheck) {
 			return nil

app/vminsert/netstorage/consistent_hash.go

@@ -1,9 +1,5 @@
 package netstorage
 
-import (
-	"github.com/cespare/xxhash/v2"
-)
-
 // See the following docs:
 // - https://www.eecs.umich.edu/techreports/cse/96/CSE-TR-316-96.pdf
 // - https://github.com/dgryski/go-rendezvous
@@ -13,14 +9,10 @@ type consistentHash struct {
 	nodeHashes []uint64
 }
 
-func newConsistentHash(nodes []string, hashSeed uint64) *consistentHash {
-	nodeHashes := make([]uint64, len(nodes))
-	for i, node := range nodes {
-		nodeHashes[i] = xxhash.Sum64([]byte(node))
-	}
+func newConsistentHash(ids []uint64, hashSeed uint64) *consistentHash {
 	return &consistentHash{
 		hashSeed:   hashSeed,
-		nodeHashes: nodeHashes,
+		nodeHashes: ids,
 	}
 }
 

app/vminsert/netstorage/consistent_hash_test.go

@@ -4,16 +4,18 @@ import (
 	"math"
 	"math/rand"
 	"testing"
+
+	"github.com/cespare/xxhash/v2"
 )
 
 func TestConsistentHash(t *testing.T) {
 	r := rand.New(rand.NewSource(1))
 
-	nodes := []string{
-		"node1",
-		"node2",
-		"node3",
-		"node4",
+	nodes := []uint64{
+		xxhash.Sum64String("node1"),
+		xxhash.Sum64String("node2"),
+		xxhash.Sum64String("node3"),
+		xxhash.Sum64String("node4"),
 	}
 	rh := newConsistentHash(nodes, 0)
 

app/vminsert/netstorage/consistent_hash_timing_test.go

@@ -4,16 +4,19 @@ import (
 	"math/rand"
 	"sync/atomic"
 	"testing"
+
+	"github.com/cespare/xxhash/v2"
 )
 
 func BenchmarkConsistentHash(b *testing.B) {
-	nodes := []string{
-		"node1",
-		"node2",
-		"node3",
-		"node4",
+	nodes := []uint64{
+		xxhash.Sum64String("node1"),
+		xxhash.Sum64String("node2"),
+		xxhash.Sum64String("node3"),
+		xxhash.Sum64String("node4"),
 	}
 	rh := newConsistentHash(nodes, 0)
+
 	b.ReportAllocs()
 	b.SetBytes(int64(len(benchKeys)))
 	b.RunParallel(func(pb *testing.PB) {

app/vminsert/netstorage/insert_ctx.go

@@ -5,6 +5,8 @@ import (
 	"net/http"
 	"strconv"
 
+	"github.com/cespare/xxhash/v2"
+
 	"github.com/VictoriaMetrics/VictoriaMetrics/app/vminsert/relabel"
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/auth"
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/bytesutil"
@@ -12,7 +14,6 @@ import (
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/httpserver"
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/prompb"
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/storage"
-	"github.com/cespare/xxhash/v2"
 )
 
 // InsertCtx is a generic context for inserting data.

app/vminsert/netstorage/netstorage.go

@@ -6,10 +6,14 @@ import (
 	"fmt"
 	"io"
 	"net"
+	"slices"
 	"sync"
 	"sync/atomic"
 	"time"
 
+	"github.com/VictoriaMetrics/metrics"
+	"github.com/cespare/xxhash/v2"
+
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/bytesutil"
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/consts"
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/encoding"
@@ -21,8 +25,6 @@ import (
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/storage"
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/timerpool"
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/timeutil"
-	"github.com/VictoriaMetrics/metrics"
-	"github.com/cespare/xxhash/v2"
 )
 
 var (
@@ -43,6 +45,9 @@ var (
 		"On the other side, disabled re-routing minimizes the number of active time series in the cluster "+
 		"during rolling restarts and during spikes in series churn rate. "+
 		"See also -disableRerouting")
+	usePersistentStorageNodeID = flag.Bool("vmstorageUsePersistentID", false, "Whether to use persistent storage node ID for -storageNode instances. "+
+		"If set to false uses storage node address in order to generate an ID. "+
+		"Using persistent node ID is useful if vmstorage node address changes over time, e.g. due to dynamic IP addresses or DNS names. ")
 )
 
 var errStorageReadOnly = errors.New("storage node is read only")
@@ -278,7 +283,7 @@ func (sn *storageNode) checkHealth() {
 		}
 		return
 	}
-	logger.Infof("successfully dialed -storageNode=%q", sn.dialer.Addr())
+	logger.Infof("successfully dialed -storageNode=%q (node ID: %d)", sn.dialer.Addr(), sn.id.Load())
 	sn.lastDialErr = nil
 	sn.bc = bc
 	sn.isBroken.Store(false)
@@ -398,15 +403,24 @@ func (sn *storageNode) dial() (*handshake.BufferedConn, error) {
 	if *disableRPCCompression {
 		compressionLevel = 0
 	}
-	bc, err := handshake.VMInsertClient(c, compressionLevel)
+	bc, id, err := handshake.VMInsertClient(c, compressionLevel)
 	if err != nil {
 		_ = c.Close()
 		sn.handshakeErrors.Inc()
 		return nil, fmt.Errorf("handshake error: %w", err)
 	}
+	sn.id.CompareAndSwap(0, id)
 	return bc, nil
 }
 
+func (sn *storageNode) getID() uint64 {
+	// Ensure that the id is populated
+	if sn.id.Load() == 0 {
+		sn.checkHealth()
+	}
+	return sn.id.Load()
+}
+
 // storageNode is a client sending data to vmstorage node.
 type storageNode struct {
 	// isBroken is set to true if the given vmstorage node is temporarily unhealthy.
@@ -473,6 +487,9 @@ type storageNode struct {
 	// The total duration spent for sending data to vmstorage node.
 	// This metric is useful for determining the saturation of vminsert->vmstorage link.
 	sendDurationSeconds *metrics.FloatCounter
+
+	// id is a unique identifier for the storage node.
+	id atomic.Uint64
 }
 
 type storageNodesBucket struct {
@@ -515,14 +532,31 @@ func MustStop() {
 	mustStopStorageNodes(snb)
 }
 
+// GetNodeID returns unique identifier for underlying storage nodes.
+func GetNodeID() uint64 {
+	snb := getStorageNodesBucket()
+	snIDs := make([]uint64, 0, len(snb.sns))
+	for _, sn := range snb.sns {
+		snIDs = append(snIDs, sn.getID())
+	}
+	slices.Sort(snIDs)
+	idsM := make([]byte, 0)
+	for _, id := range snIDs {
+		idsM = encoding.MarshalUint64(idsM, id)
+	}
+
+	return xxhash.Sum64(idsM)
+}
+
 func initStorageNodes(addrs []string, hashSeed uint64) *storageNodesBucket {
 	if len(addrs) == 0 {
 		logger.Panicf("BUG: addrs must be non-empty")
 	}
 	ms := metrics.NewSet()
-	nodesHash := newConsistentHash(addrs, hashSeed)
 	sns := make([]*storageNode, 0, len(addrs))
+	brokenNodes := make([]*storageNode, 0)
 	stopCh := make(chan struct{})
+	nodeIDs := make([]uint64, 0, len(addrs))
 	for _, addr := range addrs {
 		if _, _, err := net.SplitHostPort(addr); err != nil {
 			// Automatically add missing port.
@@ -568,10 +602,22 @@ func initStorageNodes(addrs []string, hashSeed uint64) *storageNodesBucket {
 			}
 			return 0
 		})
+		var nodeID uint64
+		if *usePersistentStorageNodeID {
+			nodeID = sn.getID()
+			if nodeID == 0 {
+				brokenNodes = append(brokenNodes, sn)
+				continue
+			}
+		} else {
+			nodeID = xxhash.Sum64String(addr)
+		}
+		nodeIDs = append(nodeIDs, nodeID)
 		sns = append(sns, sn)
 	}
+	nodesHash := newConsistentHash(nodeIDs, hashSeed)
 
-	maxBufSizePerStorageNode = memory.Allowed() / 8 / len(sns)
+	maxBufSizePerStorageNode = memory.Allowed() / 8 / len(addrs)
 	if maxBufSizePerStorageNode > consts.MaxInsertPacketSizeForVMInsert {
 		maxBufSizePerStorageNode = consts.MaxInsertPacketSizeForVMInsert
 	}
@@ -586,7 +632,12 @@ func initStorageNodes(addrs []string, hashSeed uint64) *storageNodesBucket {
 		wg:        &wg,
 	}
 
-	for idx, sn := range sns {
+	// add broken nodes to the end of the list
+	// this is needed because consistent hash slots will be populated with IDs of available
+	// storage nodes (if there are any) and indexes of consistent hash must be linked to healthy storage nodes
+	snb.sns = append(snb.sns, brokenNodes...)
+
+	for idx, sn := range snb.sns {
 		wg.Add(1)
 		go func(sn *storageNode, idx int) {
 			sn.run(snb, idx)
@@ -594,6 +645,28 @@ func initStorageNodes(addrs []string, hashSeed uint64) *storageNodesBucket {
 		}(sn, idx)
 	}
 
+	// Watch for node become healthy and rebuild snb.
+	for _, sn := range brokenNodes {
+		wg.Add(1)
+		sn := sn
+		go watchStorageNodeHealthy(sn, func() {
+			defer wg.Done()
+			// rebuild snb in order to update consistent hash with an ID of the healthy storage node
+			for {
+				currentSnb := getStorageNodesBucket()
+				newSnb := initStorageNodes(addrs, hashSeed)
+				if !storageNodes.CompareAndSwap(currentSnb, newSnb) {
+					// snb has been changed, so we need to stop the newSnb and try again
+					mustStopStorageNodes(newSnb)
+					continue
+				}
+				// stop previous snb and exit
+				mustStopStorageNodes(currentSnb)
+				break
+			}
+		})
+	}
+
 	return snb
 }
 
@@ -606,6 +679,34 @@ func mustStopStorageNodes(snb *storageNodesBucket) {
 	metrics.UnregisterSet(snb.ms, true)
 }
 
+// watchStorageNodeHealthy watches for sn become healthy and calls cb once it is ready.
+func watchStorageNodeHealthy(sn *storageNode, cb func()) {
+	for {
+		sn.brLock.Lock()
+		for !sn.isReady() {
+			select {
+			case <-sn.stopCh:
+				sn.brLock.Unlock()
+				return
+			default:
+				sn.brCond.Wait()
+			}
+		}
+		sn.brLock.Unlock()
+
+		select {
+		case <-sn.stopCh:
+			return
+		default:
+		}
+
+		if sn.isReady() {
+			cb()
+			return
+		}
+	}
+}
+
 // rerouteRowsToReadyStorageNodes reroutes src from not ready snSource to ready storage nodes.
 //
 // The function blocks until src is fully re-routed.

app/vmselect/clusternative/vmselect.go

@@ -31,7 +31,9 @@ var (
 
 // NewVMSelectServer starts new server at the given addr, which serves vmselect requests from netstorage.
 func NewVMSelectServer(addr string) (*vmselectapi.Server, error) {
-	api := &vmstorageAPI{}
+	api := &vmstorageAPI{
+		nodeID: netstorage.GetNodeID(),
+	}
 	limits := vmselectapi.Limits{
 		MaxLabelNames:                 *maxTagKeys,
 		MaxLabelValues:                *maxTagValues,
@@ -45,7 +47,9 @@ func NewVMSelectServer(addr string) (*vmselectapi.Server, error) {
 }
 
 // vmstorageAPI impelements vmselectapi.API
-type vmstorageAPI struct{}
+type vmstorageAPI struct {
+	nodeID uint64
+}
 
 func (api *vmstorageAPI) InitSearch(qt *querytracer.Tracer, sq *storage.SearchQuery, deadline uint64) (vmselectapi.BlockIterator, error) {
 	denyPartialResponse := httputils.GetDenyPartialResponse(nil)
@@ -112,6 +116,10 @@ func (api *vmstorageAPI) RegisterMetricNames(qt *querytracer.Tracer, mrs []stora
 	return netstorage.RegisterMetricNames(qt, mrs, dl)
 }
 
+func (api *vmstorageAPI) GetID() uint64 {
+	return api.nodeID
+}
+
 // blockIterator implements vmselectapi.BlockIterator
 type blockIterator struct {
 	workCh chan workItem

app/vmselect/netstorage/netstorage.go

@@ -2107,6 +2107,9 @@ type storageNode struct {
 
 	// The number of list tenants errors to storageNode.
 	tenantsErrors *metrics.Counter
+
+	// id is the unique identifier for the storageNode.
+	id uint64
 }
 
 func (sn *storageNode) registerMetricNames(qt *querytracer.Tracer, mrs []storage.MetricRow, deadline searchutils.Deadline) error {
@@ -2954,6 +2957,12 @@ func getStorageNodes() []*storageNode {
 	return snb.sns
 }
 
+// GetNodeID returns unique identifier of vmselect
+func GetNodeID() uint64 {
+	// Returns a 0 as persistent IDs are not intended to use with multi-level setup
+	return 0
+}
+
 // Init initializes storage nodes' connections to the given addrs.
 //
 // MustStop must be called when the initialized connections are no longer needed.
@@ -3015,6 +3024,7 @@ func newStorageNode(ms *metrics.Set, group *storageNodesGroup, addr string) *sto
 	sn := &storageNode{
 		group:    group,
 		connPool: connPool,
+		id:       connPool.GetTargetNodeID(),
 
 		concurrentQueries: ms.NewCounter(fmt.Sprintf(`vm_concurrent_queries{name="vmselect", addr=%q}`, addr)),
 

app/vmselect/vmui/asset-manifest.json

@@ -1,13 +1,13 @@
 {
   "files": {
     "main.css": "./static/css/main.fce049bf.css",
-    "main.js": "./static/js/main.36501ae8.js",
+    "main.js": "./static/js/main.36983a8a.js",
     "static/js/685.bebe1265.chunk.js": "./static/js/685.bebe1265.chunk.js",
     "static/media/MetricsQL.md": "./static/media/MetricsQL.d46c42c8e891f06298c4.md",
     "index.html": "./index.html"
   },
   "entrypoints": [
     "static/css/main.fce049bf.css",
-    "static/js/main.36501ae8.js"
+    "static/js/main.36983a8a.js"
   ]
 }

app/vmselect/vmui/index.html

@@ -1 +1 @@
-<!doctype html><html lang="en"><head><meta charset="utf-8"/><link rel="icon" href="./favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1,maximum-scale=5"/><meta name="theme-color" content="#000000"/><meta name="description" content="UI for VictoriaMetrics"/><link rel="apple-touch-icon" href="./apple-touch-icon.png"/><link rel="icon" type="image/png" sizes="32x32" href="./favicon-32x32.png"><link rel="manifest" href="./manifest.json"/><title>VM UI</title><script src="./dashboards/index.js" type="module"></script><meta name="twitter:card" content="summary_large_image"><meta name="twitter:image" content="./preview.jpg"><meta name="twitter:title" content="UI for VictoriaMetrics"><meta name="twitter:description" content="Explore and troubleshoot your VictoriaMetrics data"><meta name="twitter:site" content="@VictoriaMetrics"><meta property="og:title" content="Metric explorer for VictoriaMetrics"><meta property="og:description" content="Explore and troubleshoot your VictoriaMetrics data"><meta property="og:image" content="./preview.jpg"><meta property="og:type" content="website"><script defer="defer" src="./static/js/main.36501ae8.js"></script><link href="./static/css/main.fce049bf.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>
+<!doctype html><html lang="en"><head><meta charset="utf-8"/><link rel="icon" href="./favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1,maximum-scale=5"/><meta name="theme-color" content="#000000"/><meta name="description" content="UI for VictoriaMetrics"/><link rel="apple-touch-icon" href="./apple-touch-icon.png"/><link rel="icon" type="image/png" sizes="32x32" href="./favicon-32x32.png"><link rel="manifest" href="./manifest.json"/><title>VM UI</title><script src="./dashboards/index.js" type="module"></script><meta name="twitter:card" content="summary_large_image"><meta name="twitter:image" content="./preview.jpg"><meta name="twitter:title" content="UI for VictoriaMetrics"><meta name="twitter:description" content="Explore and troubleshoot your VictoriaMetrics data"><meta name="twitter:site" content="@VictoriaMetrics"><meta property="og:title" content="Metric explorer for VictoriaMetrics"><meta property="og:description" content="Explore and troubleshoot your VictoriaMetrics data"><meta property="og:image" content="./preview.jpg"><meta property="og:type" content="website"><script defer="defer" src="./static/js/main.36983a8a.js"></script><link href="./static/css/main.fce049bf.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>

app/vmstorage/main.go

@@ -111,8 +111,8 @@ func main() {
 	blocksCount := tm.SmallBlocksCount + tm.BigBlocksCount
 	rowsCount := tm.SmallRowsCount + tm.BigRowsCount
 	sizeBytes := tm.SmallSizeBytes + tm.BigSizeBytes
-	logger.Infof("successfully opened storage %q in %.3f seconds; partsCount: %d; blocksCount: %d; rowsCount: %d; sizeBytes: %d",
-		*storageDataPath, time.Since(startTime).Seconds(), partsCount, blocksCount, rowsCount, sizeBytes)
+	logger.Infof("successfully opened storage %q (node ID: %d) in %.3f seconds; partsCount: %d; blocksCount: %d; rowsCount: %d; sizeBytes: %d",
+		*storageDataPath, strg.GetID(), time.Since(startTime).Seconds(), partsCount, blocksCount, rowsCount, sizeBytes)
 
 	// register storage metrics
 	storageMetrics := metrics.NewSet()

app/vmstorage/servers/vminsert.go

@@ -101,7 +101,7 @@ func (s *VMInsertServer) run() {
 			// There is no need in response compression, since
 			// vmstorage sends only small packets to vminsert.
 			compressionLevel := 0
-			bc, err := handshake.VMInsertServer(c, compressionLevel)
+			bc, err := handshake.VMInsertServer(c, compressionLevel, s.storage.GetID())
 			if err != nil {
 				if s.isStopping() {
 					// c is stopped inside VMInsertServer.MustStop

app/vmstorage/servers/vmselect.go

@@ -195,6 +195,10 @@ func (api *vmstorageAPI) setupTfss(qt *querytracer.Tracer, sq *storage.SearchQue
 	return tfss, nil
 }
 
+func (api *vmstorageAPI) GetID() uint64 {
+	return api.s.GetID()
+}
+
 // blockIterator implements vmselectapi.BlockIterator
 type blockIterator struct {
 	sr storage.Search

app/vmui/packages/vmui/src/components/Configurators/QueryEditor/QueryEditorAutocomplete.tsx

@@ -34,25 +34,14 @@ const QueryEditorAutocomplete: FC<QueryEditorAutocompleteProps> = ({
   }, [value, caretPosition]);
 
   const exprLastPart = useMemo(() => {
-    const regexpSplit = /\s(or|and|unless|default|ifnot|if|group_left|group_right)\s|}|\+|\|-|\*|\/|\^/i;
-    const parts = values.beforeCursor.split(regexpSplit);
+    const parts = values.beforeCursor.split("}");
     return parts[parts.length - 1];
   }, [values]);
 
   const metric = useMemo(() => {
-    const regex1 = /\w+\((?<metricName>[^)]+)\)\s+(by|without|on|ignoring)\s*\(\w*/gi;
-    const matchAlt = [...exprLastPart.matchAll(regex1)];
-    if (matchAlt.length > 0 && matchAlt[0].groups && matchAlt[0].groups.metricName) {
-      return matchAlt[0].groups.metricName;
-    }
-
-    const regex2 = /^\s*\b(?<metricName>[^{}(),\s]+)(?={|$)/g;
-    const match = [...exprLastPart.matchAll(regex2)];
-    if (match.length > 0 && match[0].groups && match[0].groups.metricName) {
-      return match[0].groups.metricName;
-    }
-
-    return "";
+    const regexp = /\b[^{}(),\s]+(?={|$)/g;
+    const match = exprLastPart.match(regexp);
+    return match ? match[0] : "";
   }, [exprLastPart]);
 
   const label = useMemo(() => {
@@ -62,7 +51,7 @@ const QueryEditorAutocomplete: FC<QueryEditorAutocompleteProps> = ({
   }, [exprLastPart]);
 
   const shouldSuppressAutoSuggestion = (value: string) => {
-    const pattern = /([{(),+\-*/^]|\b(?:or|and|unless|default|ifnot|if|group_left|group_right|by|without|on|ignoring)\b)/i;
+    const pattern = /([{(),+\-*/^]|\b(?:or|and|unless|default|ifnot|if|group_left|group_right)\b)/;
     const parts = value.split(/\s+/);
     const partsCount = parts.length;
     const lastPart = parts[partsCount - 1];
@@ -74,16 +63,12 @@ const QueryEditorAutocomplete: FC<QueryEditorAutocompleteProps> = ({
   };
 
   const context = useMemo(() => {
-    const valueBeforeCursor = values.beforeCursor.trim();
-    const endOfClosedBrackets = ["}", ")"].some(char => valueBeforeCursor.endsWith(char));
-    const endOfClosedQuotes = !hasUnclosedQuotes(valueBeforeCursor) && ["`", "'", "\""].some(char => valueBeforeCursor.endsWith(char));
-    if (!values.beforeCursor || endOfClosedBrackets || endOfClosedQuotes || shouldSuppressAutoSuggestion(values.beforeCursor)) {
+    if (!values.beforeCursor || values.beforeCursor.endsWith("}") || shouldSuppressAutoSuggestion(values.beforeCursor)) {
       return QueryContextType.empty;
     }
 
-    const labelRegexp = /(?:by|without|on|ignoring)\s*\(\s*[^)]*$|\{[^}]*$/i;
-    const patternLabelValue = `(${escapeRegexp(metric)})?{?.+${escapeRegexp(label)}(=|!=|=~|!~)"?([^"]*)$`;
-    const labelValueRegexp = new RegExp(patternLabelValue, "g");
+    const labelRegexp = /\{[^}]*$/;
+    const labelValueRegexp = new RegExp(`(${escapeRegexp(metric)})?{?.+${escapeRegexp(label)}(=|!=|=~|!~)"?([^"]*)$`, "g");
 
     switch (true) {
       case labelValueRegexp.test(values.beforeCursor):
@@ -96,7 +81,7 @@ const QueryEditorAutocomplete: FC<QueryEditorAutocompleteProps> = ({
   }, [values, metric, label]);
 
   const valueByContext = useMemo(() => {
-    const wordMatch = values.beforeCursor.match(/([\w_.:]+(?![},]))$/);
+    const wordMatch = values.beforeCursor.match(/([\w_\-.:/]+(?![},]))$/);
     return wordMatch ? wordMatch[0] : "";
   }, [values.beforeCursor]);
 
@@ -134,10 +119,9 @@ const QueryEditorAutocomplete: FC<QueryEditorAutocompleteProps> = ({
     // Add quotes around the value if the context is labelValue
     if (context === QueryContextType.labelValue) {
       const quote = "\"";
+      const needsQuote = /(?:=|!=|=~|!~)$/.test(beforeValueByContext);
       valueAfterCursor = valueAfterCursor.replace(/^[^\s"|},]*/, "");
-      const needsOpenQuote = /(?:=|!=|=~|!~)$/.test(beforeValueByContext);
-      const needsCloseQuote = valueAfterCursor.trim()[0] !== "\"";
-      insert = `${needsOpenQuote ? quote : ""}${insert}${needsCloseQuote ? quote : ""}`;
+      insert = `${needsQuote ? quote : ""}${insert}`;
     }
 
     if (context === QueryContextType.label) {

app/vmui/packages/vmui/src/hooks/useFetchQueryOptions.tsx

@@ -137,7 +137,7 @@ export const useFetchQueryOptions = ({ valueByContext, metric, label, context }:
 
   // fetch labels
   useEffect(() => {
-    if (!serverUrl || context !== QueryContextType.label) {
+    if (!serverUrl || !metric || context !== QueryContextType.label) {
       return;
     }
     setLabels([]);
@@ -149,7 +149,7 @@ export const useFetchQueryOptions = ({ valueByContext, metric, label, context }:
       urlSuffix: "labels",
       setter: setLabels,
       type: TypeData.label,
-      params: getQueryParams(metric ? { "match[]": `{__name__="${metricEscaped}"}` } : undefined)
+      params: getQueryParams({ "match[]": `{__name__="${metricEscaped}"}` })
     });
 
     return () => abortControllerRef.current?.abort();
@@ -157,23 +157,20 @@ export const useFetchQueryOptions = ({ valueByContext, metric, label, context }:
 
   // fetch labelValues
   useEffect(() => {
-    if (!serverUrl || !label || context !== QueryContextType.labelValue) {
+    if (!serverUrl || !metric || !label || context !== QueryContextType.labelValue) {
       return;
     }
     setLabelValues([]);
 
     const metricEscaped = escapeDoubleQuotes(metric);
     const valueReEscaped = escapeDoubleQuotes(escapeRegexp(value));
-    const matchMetric = metric ? `__name__="${metricEscaped}"` : "";
-    const matchLabel = `${label}=~".*${valueReEscaped}.*"`;
-    const matchValue = [matchMetric, matchLabel].filter(Boolean).join(",");
 
     fetchData({
       value,
       urlSuffix: `label/${label}/values`,
       setter: setLabelValues,
       type: TypeData.labelValue,
-      params: getQueryParams({ "match[]": `{${matchValue}}` })
+      params: getQueryParams({ "match[]": `{__name__="${metricEscaped}", ${label}=~".*${valueReEscaped}.*"}` })
     });
 
     return () => abortControllerRef.current?.abort();

app/vmui/packages/vmui/src/utils/regexp.ts

@@ -8,6 +8,6 @@ export const escapeDoubleQuotes = (s: string) => {
 };
 
 export const hasUnclosedQuotes = (str: string) => {
-  const matches = str.match(/["`']/g);
+  const matches = str.match(/"/g);
   return matches ? matches.length % 2 !== 0 : false;
 };

dashboards/vm/vmagent.json

@@ -3548,8 +3548,7 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green",
-                    "value": null
+                    "color": "green"
                   },
                   {
                     "color": "red",
@@ -3565,7 +3564,7 @@
             "h": 7,
             "w": 12,
             "x": 0,
-            "y": 37
+            "y": 13
           },
           "id": 48,
           "options": {
@@ -3655,8 +3654,7 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green",
-                    "value": null
+                    "color": "green"
                   },
                   {
                     "color": "red",
@@ -3672,7 +3670,7 @@
             "h": 7,
             "w": 12,
             "x": 12,
-            "y": 37
+            "y": 13
           },
           "id": 76,
           "options": {
@@ -3760,8 +3758,7 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green",
-                    "value": null
+                    "color": "green"
                   },
                   {
                     "color": "red",
@@ -3777,7 +3774,7 @@
             "h": 7,
             "w": 12,
             "x": 0,
-            "y": 44
+            "y": 20
           },
           "id": 132,
           "options": {
@@ -3867,8 +3864,7 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green",
-                    "value": null
+                    "color": "green"
                   },
                   {
                     "color": "red",
@@ -3884,7 +3880,7 @@
             "h": 7,
             "w": 12,
             "x": 12,
-            "y": 44
+            "y": 20
           },
           "id": 133,
           "options": {
@@ -3973,8 +3969,7 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green",
-                    "value": null
+                    "color": "green"
                   },
                   {
                     "color": "red",
@@ -3990,7 +3985,7 @@
             "h": 8,
             "w": 12,
             "x": 0,
-            "y": 51
+            "y": 27
           },
           "id": 20,
           "options": {
@@ -4078,8 +4073,7 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green",
-                    "value": null
+                    "color": "green"
                   },
                   {
                     "color": "red",
@@ -4095,7 +4089,7 @@
             "h": 8,
             "w": 12,
             "x": 12,
-            "y": 51
+            "y": 27
           },
           "id": 126,
           "options": {
@@ -4182,8 +4176,7 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green",
-                    "value": null
+                    "color": "green"
                   },
                   {
                     "color": "red",
@@ -4199,7 +4192,7 @@
             "h": 8,
             "w": 12,
             "x": 0,
-            "y": 59
+            "y": 35
           },
           "id": 46,
           "options": {
@@ -4237,110 +4230,6 @@
           "title": "Scrape response size 0.99 quantile ($instance)",
           "type": "timeseries"
         },
-        {
-          "datasource": {
-            "type": "victoriametrics-datasource",
-            "uid": "$ds"
-          },
-          "fieldConfig": {
-            "defaults": {
-              "color": {
-                "mode": "palette-classic"
-              },
-              "custom": {
-                "axisBorderShow": false,
-                "axisCenteredZero": false,
-                "axisColorMode": "text",
-                "axisLabel": "",
-                "axisPlacement": "auto",
-                "barAlignment": 0,
-                "drawStyle": "line",
-                "fillOpacity": 0,
-                "gradientMode": "none",
-                "hideFrom": {
-                  "legend": false,
-                  "tooltip": false,
-                  "viz": false
-                },
-                "insertNulls": false,
-                "lineInterpolation": "linear",
-                "lineWidth": 1,
-                "pointSize": 5,
-                "scaleDistribution": {
-                  "type": "linear"
-                },
-                "showPoints": "never",
-                "spanNulls": false,
-                "stacking": {
-                  "group": "A",
-                  "mode": "none"
-                },
-                "thresholdsStyle": {
-                  "mode": "off"
-                }
-              },
-              "links": [],
-              "mappings": [],
-              "min": 0,
-              "thresholds": {
-                "mode": "absolute",
-                "steps": [
-                  {
-                    "color": "green",
-                    "value": null
-                  },
-                  {
-                    "color": "red",
-                    "value": 80
-                  }
-                ]
-              },
-              "unit": "s"
-            },
-            "overrides": []
-          },
-          "gridPos": {
-            "h": 8,
-            "w": 12,
-            "x": 12,
-            "y": 59
-          },
-          "id": 148,
-          "options": {
-            "legend": {
-              "calcs": [
-                "mean",
-                "lastNotNull",
-                "max"
-              ],
-              "displayMode": "table",
-              "placement": "bottom",
-              "showLegend": true
-            },
-            "tooltip": {
-              "mode": "multi",
-              "sort": "desc"
-            }
-          },
-          "pluginVersion": "9.2.6",
-          "targets": [
-            {
-              "datasource": {
-                "type": "victoriametrics-datasource",
-                "uid": "$ds"
-              },
-              "editorMode": "code",
-              "expr": "max(histogram_quantile(0.99, sum(rate(vm_promscrape_scrape_duration_seconds_bucket{job=~\"$job\", instance=~\"$instance\"}[$__rate_interval])) by(job, vmrange))) by(job)",
-              "format": "time_series",
-              "interval": "",
-              "legendFormat": "__auto",
-              "range": true,
-              "refId": "A"
-            }
-          ],
-          "title": "Scrape duration 0.99 quantile ($instance)",
-          "type": "timeseries"
-        },
         {
           "datasource": {
             "type": "victoriametrics-datasource",
@@ -4390,8 +4279,7 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green",
-                    "value": null
+                    "color": "green"
                   },
                   {
                     "color": "red",
@@ -4407,7 +4295,7 @@
             "h": 8,
             "w": 12,
             "x": 12,
-            "y": 67
+            "y": 35
           },
           "id": 31,
           "options": {
@@ -4687,7 +4575,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -4791,7 +4680,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -4908,7 +4798,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -5043,7 +4934,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -5145,7 +5037,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -5241,7 +5134,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -5344,7 +5238,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -5454,7 +5349,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -5551,7 +5447,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -5648,7 +5545,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -5795,7 +5693,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -5899,7 +5798,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -6003,7 +5903,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -6107,7 +6008,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -6210,7 +6112,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "transparent"
+                    "color": "transparent",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -6412,7 +6315,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "transparent"
+                    "color": "transparent",
+                    "value": null
                   },
                   {
                     "color": "red",

dashboards/vmagent.json

@@ -3547,8 +3547,7 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green",
-                    "value": null
+                    "color": "green"
                   },
                   {
                     "color": "red",
@@ -3564,7 +3563,7 @@
             "h": 7,
             "w": 12,
             "x": 0,
-            "y": 37
+            "y": 13
           },
           "id": 48,
           "options": {
@@ -3654,8 +3653,7 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green",
-                    "value": null
+                    "color": "green"
                   },
                   {
                     "color": "red",
@@ -3671,7 +3669,7 @@
             "h": 7,
             "w": 12,
             "x": 12,
-            "y": 37
+            "y": 13
           },
           "id": 76,
           "options": {
@@ -3759,8 +3757,7 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green",
-                    "value": null
+                    "color": "green"
                   },
                   {
                     "color": "red",
@@ -3776,7 +3773,7 @@
             "h": 7,
             "w": 12,
             "x": 0,
-            "y": 44
+            "y": 20
           },
           "id": 132,
           "options": {
@@ -3866,8 +3863,7 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green",
-                    "value": null
+                    "color": "green"
                   },
                   {
                     "color": "red",
@@ -3883,7 +3879,7 @@
             "h": 7,
             "w": 12,
             "x": 12,
-            "y": 44
+            "y": 20
           },
           "id": 133,
           "options": {
@@ -3972,8 +3968,7 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green",
-                    "value": null
+                    "color": "green"
                   },
                   {
                     "color": "red",
@@ -3989,7 +3984,7 @@
             "h": 8,
             "w": 12,
             "x": 0,
-            "y": 51
+            "y": 27
           },
           "id": 20,
           "options": {
@@ -4077,8 +4072,7 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green",
-                    "value": null
+                    "color": "green"
                   },
                   {
                     "color": "red",
@@ -4094,7 +4088,7 @@
             "h": 8,
             "w": 12,
             "x": 12,
-            "y": 51
+            "y": 27
           },
           "id": 126,
           "options": {
@@ -4181,8 +4175,7 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green",
-                    "value": null
+                    "color": "green"
                   },
                   {
                     "color": "red",
@@ -4198,7 +4191,7 @@
             "h": 8,
             "w": 12,
             "x": 0,
-            "y": 59
+            "y": 35
           },
           "id": 46,
           "options": {
@@ -4236,110 +4229,6 @@
           "title": "Scrape response size 0.99 quantile ($instance)",
           "type": "timeseries"
         },
-        {
-          "datasource": {
-            "type": "prometheus",
-            "uid": "$ds"
-          },
-          "fieldConfig": {
-            "defaults": {
-              "color": {
-                "mode": "palette-classic"
-              },
-              "custom": {
-                "axisBorderShow": false,
-                "axisCenteredZero": false,
-                "axisColorMode": "text",
-                "axisLabel": "",
-                "axisPlacement": "auto",
-                "barAlignment": 0,
-                "drawStyle": "line",
-                "fillOpacity": 0,
-                "gradientMode": "none",
-                "hideFrom": {
-                  "legend": false,
-                  "tooltip": false,
-                  "viz": false
-                },
-                "insertNulls": false,
-                "lineInterpolation": "linear",
-                "lineWidth": 1,
-                "pointSize": 5,
-                "scaleDistribution": {
-                  "type": "linear"
-                },
-                "showPoints": "never",
-                "spanNulls": false,
-                "stacking": {
-                  "group": "A",
-                  "mode": "none"
-                },
-                "thresholdsStyle": {
-                  "mode": "off"
-                }
-              },
-              "links": [],
-              "mappings": [],
-              "min": 0,
-              "thresholds": {
-                "mode": "absolute",
-                "steps": [
-                  {
-                    "color": "green",
-                    "value": null
-                  },
-                  {
-                    "color": "red",
-                    "value": 80
-                  }
-                ]
-              },
-              "unit": "s"
-            },
-            "overrides": []
-          },
-          "gridPos": {
-            "h": 8,
-            "w": 12,
-            "x": 12,
-            "y": 59
-          },
-          "id": 148,
-          "options": {
-            "legend": {
-              "calcs": [
-                "mean",
-                "lastNotNull",
-                "max"
-              ],
-              "displayMode": "table",
-              "placement": "bottom",
-              "showLegend": true
-            },
-            "tooltip": {
-              "mode": "multi",
-              "sort": "desc"
-            }
-          },
-          "pluginVersion": "9.2.6",
-          "targets": [
-            {
-              "datasource": {
-                "type": "prometheus",
-                "uid": "$ds"
-              },
-              "editorMode": "code",
-              "expr": "max(histogram_quantile(0.99, sum(rate(vm_promscrape_scrape_duration_seconds_bucket{job=~\"$job\", instance=~\"$instance\"}[$__rate_interval])) by(job, vmrange))) by(job)",
-              "format": "time_series",
-              "interval": "",
-              "legendFormat": "__auto",
-              "range": true,
-              "refId": "A"
-            }
-          ],
-          "title": "Scrape duration 0.99 quantile ($instance)",
-          "type": "timeseries"
-        },
         {
           "datasource": {
             "type": "prometheus",
@@ -4389,8 +4278,7 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green",
-                    "value": null
+                    "color": "green"
                   },
                   {
                     "color": "red",
@@ -4406,7 +4294,7 @@
             "h": 8,
             "w": 12,
             "x": 12,
-            "y": 67
+            "y": 35
           },
           "id": 31,
           "options": {
@@ -4686,7 +4574,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -4790,7 +4679,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -4907,7 +4797,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -5042,7 +4933,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -5144,7 +5036,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -5240,7 +5133,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -5343,7 +5237,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -5453,7 +5348,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -5550,7 +5446,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -5647,7 +5544,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -5794,7 +5692,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -5898,7 +5797,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -6002,7 +5902,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -6106,7 +6007,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "green"
+                    "color": "green",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -6209,7 +6111,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "transparent"
+                    "color": "transparent",
+                    "value": null
                   },
                   {
                     "color": "red",
@@ -6411,7 +6314,8 @@
                 "mode": "absolute",
                 "steps": [
                   {
-                    "color": "transparent"
+                    "color": "transparent",
+                    "value": null
                   },
                   {
                     "color": "red",

docs/BestPractices.md

@@ -1,10 +1,9 @@
 ---
 sort: 32
 weight: 32
-title: Best practices
+title: VictoriaMetrics best practices
 menu:
   docs:
-    identifier: vm-best-practices
     parent: 'victoriametrics'
     weight: 32
 aliases:

docs/CHANGELOG.md

@@ -4,7 +4,6 @@ weight: 100
 title: CHANGELOG
 menu:
   docs:
-    identifier: vm-changelog
     parent: victoriametrics
     weight: 100
 aliases:
@@ -30,24 +29,18 @@ See also [LTS releases](https://docs.victoriametrics.com/lts-releases/).
 
 ## tip
 
-## [v1.102.1](https://github.com/VictoriaMetrics/VictoriaMetrics/releases/tag/v1.102.1)
+**Update note 1: [vmauth](https://docs.victoriametrics.com/vmauth/) HTTP response code has changed from 503 to 502 for a case when all upstream backends were not available. This was changed to align [vmauth](https://docs.victoriametrics.com/vmauth/) behaviour with other well-known reverse-proxies behaviour. **
 
-Released at 2024-08-01
-
-**Update note 1: [vmauth](https://docs.victoriametrics.com/vmauth/) HTTP response code has changed from 503 to 502 for a case when all upstream backends were not available. This was changed to align [vmauth](https://docs.victoriametrics.com/vmauth/) behaviour with other well-known reverse-proxies behaviour.**
+**Update note 2: release contains breaking change to inter-cluster communication. The `vmstorage` nodes with version lower than `tip` won't be able to communicate with `vmselect` and `vminsert` nodes with version lower than `tip`. See [this](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5438) issue for the details.**
 
 * SECURITY: upgrade base docker image (Alpine) from 3.20.1 to 3.20.2. See [alpine 3.20.2 release notes](https://alpinelinux.org/posts/Alpine-3.20.2-released.html).
 
 * FEATURE: [vmauth](./vmauth.md): add `keep_original_host` option, which can be used for proxying the original `Host` header from client request to the backend. By default the backend host is used as `Host` header when proxying requests to the configured backends. See [these docs](./vmauth.md#host-http-header).
 * FEATURE: [vmauth](./vmauth.md) now returns HTTP 502 status code when all upstream backends are not available. Previously, it returned HTTP 503 status code. This change aligns vmauth behavior with other well-known reverse-proxies behavior.
-* FEATURE: [vmagent dashboard](https://github.com/VictoriaMetrics/VictoriaMetrics/blob/master/dashboards/vmagent.json): add `Scrape duration 0.99 quantile` panel to show the 99th quantile of scrape duration in seconds. This should help identifying vmagent instances that experiences too high scraping durations.
+* FEATURE: [VictoriaMetrics cluster](https://docs.victoriametrics.com/cluster-victoriametrics/): use a persistent `vmstorage` node ID for consistent hashing at data write path. This allows to keep the same data distribution after `vmstorage` changes its IP address. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5438).
 
-* BUGFIX: [Single-node VictoriaMetrics](https://docs.victoriametrics.com/) and `vmselect` in [VictoriaMetrics cluster](https://docs.victoriametrics.com/cluster-victoriametrics/): Fixes panic if incorrect `metrisql` expression passed to the `prettify-query` API. See this [issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6736) for details.
-* BUGFIX: all VictoriaMetrics components: validate files specified via `-tlsKeyFile` and `-tlsCertFile` cmd-line flags on the process start-up. Previously, validation happened on the first connection accepted by HTTP server. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6608) for the details. Thanks to @yincongcyincong for the [pull request](https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6621).
 * BUGFIX: [vmauth](https://docs.victoriametrics.com/vmauth/): properly proxy requests to backend urls ending with `/` if the original request path equals to `/`. Previously the trailing `/` at the backend path was incorrectly removed. For example, if the request to `http://vmauth/` is configured to be proxied to `url_prefix=http://backend/foo/`, then it was proxied to `http://backend/foo`, while it should go to `http://backend/foo/`.
 * BUGFIX: [vmauth](https://docs.victoriametrics.com/vmauth/): fix `cannot read data after closing the reader` error when proxying HTTP requests without body (aka `GET` requests). The issue has been introduced in [v1.102.0](https://github.com/VictoriaMetrics/VictoriaMetrics/releases/tag/v1.102.0) in [this commit](https://github.com/VictoriaMetrics/VictoriaMetrics/commit/7ee57974935a662896f2de40fdf613156630617d).
-* BUGFIX: [vmui](https://docs.victoriametrics.com/#vmui): fix auto-completion triggers for metric and label names, and disable it after specific characters. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6153) and [these comments](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5866#issuecomment-2065273421).
-* BUGFIX: [vmui](https://docs.victoriametrics.com/#vmui): fix automatic addition of quotes when inserting label values from autocomplete suggestions. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6260).
 
 ## [v1.102.0](https://github.com/VictoriaMetrics/VictoriaMetrics/releases/tag/v1.102.0)
 

docs/CHANGELOG_2020.md

@@ -1,12 +1,11 @@
 ---
-sort: 6
-weight: 6
-title: Year 2020
+sort: 101
+weight: 101
+title: CHANGELOG for the year 2020
 menu:
   docs:
-    identifier: vm-changelog-2020
-    parent: vm-changelog
-    weight: 6
+    parent: 'victoriametrics'
+    weight: 101
 aliases:
 - /CHANGELOG_2020.html
 ---

docs/CHANGELOG_2021.md

@@ -1,12 +1,11 @@
 ---
-sort: 5
-weight: 5
-title: Year 2021
+sort: 102
+weight: 102
+title: CHANGELOG for the year 2021
 menu:
   docs:
-    identifier: vm-changelog-2021
-    parent: vm-changelog
-    weight: 5
+    parent: 'victoriametrics'
+    weight: 102
 aliases:
 - /CHANGELOG_2021.html
 ---

docs/CHANGELOG_2022.md

@@ -1,12 +1,11 @@
 ---
-sort: 4
-weight: 4
-title: Year 2022
+sort: 103
+weight: 103
+title: CHANGELOG for the year 2022
 menu:
   docs:
-    identifier: vm-changelog-2022
-    parent: vm-changelog
-    weight: 4
+    parent: 'victoriametrics'
+    weight: 103
 aliases:
 - /CHANGELOG_2022.html
 ---

docs/CHANGELOG_2023.md

@@ -1,12 +1,11 @@
 ---
-sort: 3
-weight: 3
-title: Year 2023
+sort: 104
+weight: 104
+title: CHANGELOG for the year 2023
 menu:
   docs:
-    identifier: vm-changelog-2023
-    parent: vm-changelog
-    weight: 3
+    parent: 'victoriametrics'
+    weight: 104
 aliases:
 - /CHANGELOG_2023.html
 ---

docs/CONTRIBUTING.md

@@ -1,11 +1,10 @@
 ---
 sort: 400
 weight: 400
-title: Contributing
+title: Contributing to VictoriaMetrics
 menu:
   docs:
-    identifier: vm-contributing
-    parent: victoriametrics
+    parent: 'victoriametrics'
     weight: 400
 aliases:
 - /CONTRIBUTING.html

docs/Cluster-VictoriaMetrics.md

@@ -3,13 +3,17 @@ sort: 2
 weight: 2
 menu:
   docs:
-    identifier: vm-cluster-version
     parent: 'victoriametrics'
     weight: 2
 title: Cluster version
 aliases:
   - /Cluster-VictoriaMetrics.html
 ---
+<picture>
+  <source srcset="/logo_white.webp" media="(prefers-color-scheme: dark)">
+  <source srcset="/logo.webp" media="(prefers-color-scheme: light)">
+  <img src="/logo.webp" width="300" alt="VictoriaMetrics logo">
+</picture>
 
 VictoriaMetrics is a fast, cost-effective and scalable time series database. It can be used as a long-term remote storage for Prometheus.
 
@@ -1297,6 +1301,8 @@ Below is the output for `/path/to/vminsert -help`:
      Show VictoriaMetrics version
   -vmstorageDialTimeout duration
      Timeout for establishing RPC connections from vminsert to vmstorage. See also -vmstorageUserTimeout (default 3s)
+  -vmstorageUsePersistentID
+     Whether to use persistent storage node ID for -storageNode instances. If set to false uses storage node address in order to generate an ID. Using persistent node ID is useful if vmstorage node address changes over time, e.g. due to dynamic IP addresses or DNS names. 
   -vmstorageUserTimeout duration
      Network timeout for RPC connections from vminsert to vmstorage (Linux only). Lower values speed up re-rerouting recovery when some of vmstorage nodes become unavailable because of networking issues. Read more about TCP_USER_TIMEOUT at https://blog.cloudflare.com/when-tcp-sockets-refuse-to-die/ . See also -vmstorageDialTimeout (default 3s)
 ```
@@ -1896,4 +1902,33 @@ Below is the output for `/path/to/vmstorage -help`:
      TCP address to accept connections from vminsert services (default ":8400")
   -vmselectAddr string
      TCP address to accept connections from vmselect services (default ":8401")
-```
+```
+
+## VictoriaMetrics Logo
+
+[Zip](https://github.com/VictoriaMetrics/VictoriaMetrics/blob/master/VM_logo.zip) contains three folders with different image orientation (main color and inverted version).
+
+Files included in each folder:
+
+- 2 JPEG Preview files
+- 2 PNG Preview files with transparent background
+- 2 EPS Adobe Illustrator EPS10 files
+
+### Logo Usage Guidelines
+
+#### Font used
+
+- Lato Black
+- Lato Regular
+
+#### Color Palette
+
+- HEX [#110f0f](https://www.color-hex.com/color/110f0f)
+- HEX [#ffffff](https://www.color-hex.com/color/ffffff)
+
+### We kindly ask
+
+- Please don't use any other font instead of suggested.
+- There should be sufficient clear space around the logo.
+- Do not change spacing, alignment, or relative locations of the design elements.
+- Do not change the proportions of any of the design elements or the design itself. You    may resize as needed but must retain all proportions.

docs/FAQ.md

@@ -215,10 +215,11 @@ We provide commercial support for both versions. [Contact us](mailto:info@victor
 
 The following commercial versions of VictoriaMetrics are available:
 
-* [VictoriaMetrics Cloud](https://cloud.victoriametrics.com/signUp?utm_source=website&utm_campaign=docs_vm_faq) – the most cost-efficient hosted monitoring platform, operated by VictoriaMetrics core team.
+* [Managed VictoriaMetrics at AWS](https://aws.amazon.com/marketplace/pp/prodview-4tbfq5icmbmyc) (aka managed Prometheus).
 
 The following commercial versions of VictoriaMetrics are planned:
 
+* Managed VictoriaMetrics at Google Cloud.
 * Cloud monitoring solution based on VictoriaMetrics.
 
 [Contact us](mailto:info@victoriametrics.com) for more information on our plans.

docs/PerTenantStatistic.md

@@ -1,11 +1,10 @@
 ---
 sort: 31
 weight: 31
-title: Cluster Per Tenant Statistic
+title: VictoriaMetrics Cluster Per Tenant Statistic
 menu:
   docs:
-    identifier: vm-cluster-per-tenant-statistic
-    parent: victoriametrics
+    parent: 'victoriametrics'
     weight: 31
 aliases:
   - /PerTenantStatistic.html

docs/Quick-Start.md

@@ -4,8 +4,7 @@ weight: 22
 title: Quick start
 menu:
   docs:
-    identifier: vm-quick-start
-    parent: victoriametrics
+    parent: 'victoriametrics'
     weight: 22
 aliases:
 - /Quick-Start.html
@@ -21,7 +20,7 @@ VictoriaMetrics is distributed in two forms:
 
 Single-server-VictoriaMetrics VictoriaMetrics is available as:
 
-* [VictoriaMetrics Cloud](https://cloud.victoriametrics.com/signUp?utm_source=website&utm_campaign=docs_vm_quickstart) – the most cost-efficient hosted monitoring platfor, operated by VictoriaMetrics core team.
+* [Managed VictoriaMetrics at AWS](https://aws.amazon.com/marketplace/pp/prodview-4tbfq5icmbmyc)
 * [Docker images](https://hub.docker.com/r/victoriametrics/victoria-metrics/)
 * [Helm Charts](https://github.com/VictoriaMetrics/helm-charts#list-of-charts)
 * [Binary releases](https://github.com/VictoriaMetrics/VictoriaMetrics/releases/latest)

docs/README.md

@@ -6,6 +6,12 @@
 [![Build Status](https://github.com/VictoriaMetrics/VictoriaMetrics/workflows/main/badge.svg)](https://github.com/VictoriaMetrics/VictoriaMetrics/actions)
 [![codecov](https://codecov.io/gh/VictoriaMetrics/VictoriaMetrics/branch/master/graph/badge.svg)](https://codecov.io/gh/VictoriaMetrics/VictoriaMetrics)
 
+<picture>
+  <source srcset="/logo_white.webp" media="(prefers-color-scheme: dark)">
+  <source srcset="/logo.webp" media="(prefers-color-scheme: light)">
+  <img src="/logo.webp" width="300" alt="VictoriaMetrics logo">
+</picture>
+
 VictoriaMetrics is a fast, cost-effective and scalable monitoring solution and time series database.
 See [case studies for VictoriaMetrics](https://docs.victoriametrics.com/casestudies/).
 
@@ -492,7 +498,7 @@ via ["submit metrics" API](https://docs.datadoghq.com/api/latest/metrics/#submit
 DataDog agent allows configuring destinations for metrics sending via ENV variable `DD_DD_URL` 
 or via [configuration file](https://docs.datadoghq.com/agent/guide/agent-configuration-files/) in section `dd_url`.
 
-![DD to VM](README_sending_DD_metrics_to_VM.webp)
+![DD to VM](Single-server-VictoriaMetrics-sending_DD_metrics_to_VM.webp)
 
 To configure DataDog agent via ENV variable add the following prefix:
 
@@ -519,7 +525,7 @@ pick [single-node or cluster URL](https://docs.victoriametrics.com/url-examples/
 DataDog allows configuring [Dual Shipping](https://docs.datadoghq.com/agent/guide/dual-shipping/) for metrics 
 sending via ENV variable `DD_ADDITIONAL_ENDPOINTS` or via configuration file `additional_endpoints`.
  
-![DD to VM](README_sending_DD_metrics_to_VM_and_DD.webp)
+![DD to VM](Single-server-VictoriaMetrics-sending_DD_metrics_to_VM_and_DD.webp)
  
 Run DataDog using the following ENV variable with VictoriaMetrics as additional metrics receiver:
 
@@ -1003,18 +1009,6 @@ at `/render` endpoint, which is used by [Graphite datasource in Grafana](https:/
 When configuring Graphite datasource in Grafana, the `Storage-Step` http request header must be set to a step between Graphite data points
 stored in VictoriaMetrics. For example, `Storage-Step: 10s` would mean 10 seconds distance between Graphite datapoints stored in VictoriaMetrics.
 
-#### Known Incompatibilities with `graphite-web`
-
-- **Timestamp Shifting**: VictoriaMetrics does not support shifting response timestamps outside the request time range as `graphite-web` does. This limitation impacts chained functions with time modifiers, such as `timeShift(summarize)`. For more details, refer to this [issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/2969).
-
-- **Non-deterministic series order**: due to the distributed nature of metrics processing, functions within the `seriesLists` family can produce non-deterministic results. To ensure consistent results, arguments for these functions must be wrapped with a sorting function. For instance, the function `divideSeriesLists(series_list_1, series_list_2)` should be modified to `divideSeriesLists(sortByName(series_list_1), sortByName(series_list_2))`.  See this [issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5810) for details.
-
-  The affected functions include:
-  - `aggregateSeriesLists`
-  - `diffSeriesLists`
-  - `multiplySeriesLists`
-  - `divideSeriesLists`
-
 ### Graphite Metrics API usage
 
 VictoriaMetrics supports the following handlers from [Graphite Metrics API](https://graphite-api.readthedocs.io/en/latest/api.html#the-metrics-api):
@@ -2648,9 +2642,15 @@ and gets automatically updated once changes are merged to [master](https://githu
 To update the documentation follow the steps below:
 - [Fork](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/about-forks) 
   VictoriaMetrics repo and apply changes to the docs:
-  - To update [the main page](https://docs.victoriametrics.com/) modify [this file](https://github.com/VictoriaMetrics/VictoriaMetrics/blob/master/docs/README.md).
+  - To update [the main page](https://docs.victoriametrics.com/) modify [this file](https://github.com/VictoriaMetrics/VictoriaMetrics/blob/master/README.md).
   - To update other pages, apply changes to the corresponding file in [docs folder](https://github.com/VictoriaMetrics/VictoriaMetrics/tree/master/docs).
 - If your changes contain an image then see [images in documentation](https://docs.victoriametrics.com/#images-in-documentation).
+- Once changes are made, execute the command below to finalize and sync the changes:
+
+  ```sh
+  make docs-sync
+  ```
+
 - Create [a pull request](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request)
   with proposed changes and wait for it to be merged.
 
@@ -2663,7 +2663,7 @@ Requirements for changes to docs:
 - Prefer improving the existing docs instead of adding new ones.
 - Use absolute links. This simplifies moving docs between different files.
 
-Periodically run `make spellcheck` - this command detects spelling errors at `docs/` folder. Please fix the found spelling errors
+Priodically run `make spellcheck` - this command detects spelling errors at `docs/` folder. Please fix the found spelling errors
 and commit the fixes in a separate commit.
 
 ### Images in documentation

docs/VictoriaLogs/CHANGELOG.md

@@ -1,7 +1,7 @@
 ---
 sort: 7
 weight: 7
-title: CHANGELOG
+title: VictoriaLogs changelog
 menu:
   docs:
     identifier: "victorialogs-changelog"

docs/VictoriaLogs/FAQ.md

@@ -1,7 +1,7 @@
 ---
 sort: 6
 weight: 6
-title: FAQ
+title: VictoriaLogs FAQ
 menu:
   docs:
     identifier: "victorialogs-faq"

docs/VictoriaLogs/QuickStart.md

@@ -1,11 +1,10 @@
 ---
 sort: 1
 weight: 1
-title: Quick Start
+title: VictoriaLogs Quick Start
 menu:
   docs:
-    parent: victorialogs
-    identifier: vl-quick-start
+    parent: "victorialogs"
     weight: 1
     title: Quick Start
 aliases:

docs/VictoriaLogs/Roadmap.md

@@ -1,7 +1,7 @@
 ---
 sort: 8
 weight: 8
-title: Roadmap
+title: VictoriaLogs roadmap
 disableToc: true
 menu:
   docs:

docs/VictoriaLogs/keyConcepts.md

@@ -1,11 +1,10 @@
 ---
 sort: 2
 weight: 2
-title: Key concepts
+title: VictoriaLogs key concepts
 menu:
   docs:
-    identifier: vl-key-concepts
-    parent: victorialogs
+    parent: "victorialogs"
     weight: 2
     title: Key concepts
 aliases:

docs/anomaly-detection/CHANGELOG.md

@@ -13,16 +13,6 @@ aliases:
 Please find the changelog for VictoriaMetrics Anomaly Detection below.
 
 > **Important note: Users are strongly encouraged to upgrade to `vmanomaly` [v1.9.2](https://hub.docker.com/repository/docker/victoriametrics/vmanomaly/tags?page=1&ordering=name) or newer for optimal performance and accuracy. <br><br> This recommendation is crucial for configurations with a low `infer_every` parameter [in your scheduler](./components/scheduler.md#parameters-1), and in scenarios where data exhibits significant high-order seasonality patterns (such as hourly or daily cycles). Previous versions from v1.5.1 to v1.8.0 were identified to contain a critical issue impacting model training, where models were inadvertently trained on limited data subsets, leading to suboptimal fits, affecting the accuracy of anomaly detection. <br><br> Upgrading to v1.9.2 addresses this issue, ensuring proper model training and enhanced reliability. For users utilizing Helm charts, it is recommended to upgrade to version [1.0.0](https://github.com/VictoriaMetrics/helm-charts/blob/master/charts/victoria-metrics-anomaly/CHANGELOG.md#100) or newer.**
-## v1.14.2
-Released: 2024-07-26
-- FIX: Patch a bug introduced in [v1.14.1](#v1141), causing `vmanomaly` to crash in `preset` [mode](/anomaly-detection/presets/).
-
-## v1.14.1
-Released: 2024-07-26
-- FEATURE: Allow to process larger data chunks in [VmReader](/anomaly-detection/components/reader#vm-reader) that exceed `-search.maxPointsPerTimeseries` [constraint in VictoriaMetrics](https://docs.victoriametrics.com/?highlight=search.maxPointsPerTimeseries#resource-usage-limits) by splitting the range and sending multiple requests. A warning is printed in logs, suggesting reducing the range or step, or increasing `search.maxPointsPerTimeseries` constraint in VictoriaMetrics, which is still a recommended option.
-- FEATURE: Backward-compatible redesign of [`queries`](/anomaly-detection/components/reader?highlight=queries#vm-reader) arg of [VmReader](/anomaly-detection/components/reader#vm-reader). Old format of `{q_alias1: q_expr1, q_alias2: q_expr2, ...}` will be implicitly converted to a new one with a warning raised in logs. New format allows to specify per-query parameters, like `step` to reduce amount of data read from VictoriaMetrics TSDB and to allow config flexibility. Find out more in [Per-query parameters section of VmReader](/anomaly-detection/components/reader/#per-query-parameters).
-
-- IMPROVEMENT: Added multi-platform builds for `linux/amd64` and `linux/arm64` architectures.
 
 ## v1.13.3
 Released: 2024-07-17

docs/anomaly-detection/FAQ.md

@@ -11,21 +11,21 @@ aliases:
 - /anomaly-detection/FAQ.html
 ---
 ## What is VictoriaMetrics Anomaly Detection (vmanomaly)?
-VictoriaMetrics Anomaly Detection, also known as `vmanomaly`, is a service for detecting unexpected changes in time series data. Utilizing machine learning models, it computes and pushes back an ["anomaly score"](/anomaly-detection/components/models#vmanomaly-output) for user-specified metrics. This hands-off approach to anomaly detection reduces the need for manual alert setup and can adapt to various metrics, improving your observability experience.
+VictoriaMetrics Anomaly Detection, also known as `vmanomaly`, is a service for detecting unexpected changes in time series data. Utilizing machine learning models, it computes and pushes back an ["anomaly score"](./components/models.md#vmanomaly-output) for user-specified metrics. This hands-off approach to anomaly detection reduces the need for manual alert setup and can adapt to various metrics, improving your observability experience.
 
-Please refer to [our QuickStart section](/anomaly-detection/#practical-guides-and-installation) to find out more.
+Please refer to [our guide section](./README.md#practical-guides-and-installation) to find out more.
 
 > **Note: `vmanomaly` is a part of [enterprise package](../enterprise.md). You need to get a [free trial license](https://victoriametrics.com/products/enterprise/trial/) for evaluation.**
 
 ## What is anomaly score?
-Among the metrics produced by `vmanomaly` (as detailed in [vmanomaly output metrics](/anomaly-detection/components/models#vmanomaly-output)), `anomaly_score` is a pivotal one. It is **a continuous score > 0**, calculated in such a way that **scores ranging from 0.0 to 1.0 usually represent normal data**, while **scores exceeding 1.0 are typically classified as anomalous**. However, it's important to note that the threshold for anomaly detection can be customized in the alert configuration settings.
+Among the metrics produced by `vmanomaly` (as detailed in [vmanomaly output metrics](./components/models.md#vmanomaly-output)), `anomaly_score` is a pivotal one. It is **a continuous score > 0**, calculated in such a way that **scores ranging from 0.0 to 1.0 usually represent normal data**, while **scores exceeding 1.0 are typically classified as anomalous**. However, it's important to note that the threshold for anomaly detection can be customized in the alert configuration settings.
 
 The decision to set the changepoint at `1.0` is made to ensure consistency across various models and alerting configurations, such that a score above `1.0` consistently signifies an anomaly, thus, alerting rules are maintained more easily.
 
-> Note: `anomaly_score` is a metric itself, which preserves all labels found in input data and (optionally) appends [custom labels, specified in writer](/anomaly-detection/components/writer#metrics-formatting) - follow the link for detailed output example.
+> Note: `anomaly_score` is a metric itself, which preserves all labels found in input data and (optionally) appends [custom labels, specified in writer](./components/writer.md#metrics-formatting) - follow the link for detailed output example.
 
 ## How is anomaly score calculated?
-For most of the [univariate models](/anomaly-detection/components/models#univariate-models) that can generate `yhat`, `yhat_lower`, and `yhat_upper` time series in [their output](/anomaly-detection/components/models#vmanomaly-output) (such as [Prophet](/anomaly-detection/components/models#prophet) or [Z-score](/anomaly-detection/components/models#z-score)), the anomaly score is calculated as follows:
+For most of the [univariate models](./components/models.md#univariate-models) that can generate `yhat`, `yhat_lower`, and `yhat_upper` time series in [their output](./components/models.md#vmanomaly-output) (such as [Prophet](./components/models.md#prophet) or [Z-score](./components/models.md#z-score)), the anomaly score is calculated as follows:
 - If `yhat` (expected series behavior) equals `y` (actual value observed), then the anomaly score is 0.
 - If `y` (actual value observed) falls within the `[yhat_lower, yhat_upper]` confidence interval, the anomaly score will gradually approach 1, the closer `y` is to the boundary.
 - If `y` (actual value observed) strictly exceeds the `[yhat_lower, yhat_upper]` interval, the anomaly score will be greater than 1, increasing as the margin between the actual value and the expected range grows.
@@ -36,43 +36,39 @@ Please see example graph illustrating this logic below:
 
 
 ## How does vmanomaly work?
-`vmanomaly` applies built-in (or custom) [anomaly detection algorithms](/anomaly-detection/components/models), specified in a config file. 
-
-- All the models generate a metric called [anomaly_score](#what-is-anomaly-score)
-- All produced anomaly scores are unified in a way that values lower than 1.0 mean “likely normal”, while values over 1.0 mean “likely anomalous”
-- Simple rules for alerting: start with `anomaly_score{“key”=”value”} > 1`
-- Models are retrained continuously, based on `schedulers` section in a config, so that threshold=1.0 remains actual
-- Produced scores are stored back to VictoriaMetrics TSDB and can be used for various observability tasks (alerting, visualization, debugging).
+`vmanomaly` applies built-in (or custom) [anomaly detection algorithms](./components/models.md), specified in a config file. Although a single config file supports one model, running multiple instances of `vmanomaly` with different configs is possible and encouraged for parallel processing or better support for your use case (i.e. simpler model for simple metrics, more sophisticated one for metrics with trends and seasonalities).
 
+1. For more detailed information, please visit the [overview section](./Overview.md#about).
+2. To view a diagram illustrating the interaction of components, please explore the [components section](./components/README.md).
 
 ## What data does vmanomaly operate on?
-`vmanomaly` operates on data fetched from VictoriaMetrics, where you can leverage full power of [MetricsQL](/metricsql) for data selection, sampling, and processing. Users can also [apply global filters](/#prometheus-querying-api-enhancements) for more targeted data analysis, enhancing scope limitation and tenant visibility.
+`vmanomaly` operates on data fetched from VictoriaMetrics, where you can leverage full power of [MetricsQL](../MetricsQL.md) for data selection, sampling, and processing. Users can also [apply global filters](../README.md#prometheus-querying-api-enhancements) for more targeted data analysis, enhancing scope limitation and tenant visibility.
 
-Respective config is defined in a [`reader`](/anomaly-detection/components/reader#vm-reader) section.
+Respective config is defined in a [`reader`](./components/reader.md#vm-reader) section.
 
 ## Handling noisy input data
-`vmanomaly` operates on data fetched from VictoriaMetrics using [MetricsQL](/metricsql) queries, so the initial data quality can be fine-tuned with aggregation, grouping, and filtering to reduce noise and improve anomaly detection accuracy.
+`vmanomaly` operates on data fetched from VictoriaMetrics using [MetricsQL](../MetricsQL.md) queries, so the initial data quality can be fine-tuned with aggregation, grouping, and filtering to reduce noise and improve anomaly detection accuracy.
 
 ## Output produced by vmanomaly
-`vmanomaly` models generate [metrics](/anomaly-detection/components/models#vmanomaly-output) like `anomaly_score`, `yhat`, `yhat_lower`, `yhat_upper`, and `y`. These metrics provide a comprehensive view of the detected anomalies. The service also produces [health check metrics](/anomaly-detection/components/monitoring#metrics-generated-by-vmanomaly) for monitoring its performance.
+`vmanomaly` models generate [metrics](./components/models.md#vmanomaly-output) like `anomaly_score`, `yhat`, `yhat_lower`, `yhat_upper`, and `y`. These metrics provide a comprehensive view of the detected anomalies. The service also produces [health check metrics](./components/monitoring.md#metrics-generated-by-vmanomaly) for monitoring its performance.
 
 ## Choosing the right model for vmanomaly
-Selecting the best model for `vmanomaly` depends on the data's nature and the [types of anomalies](https://victoriametrics.com/blog/victoriametrics-anomaly-detection-handbook-chapter-2/#categories-of-anomalies) to detect. For instance, [Z-score](/anomaly-detection/components/models#z-score) is suitable for data without trends or seasonality, while more complex patterns might require models like [Prophet](/anomaly-detection/components/models#prophet).
+Selecting the best model for `vmanomaly` depends on the data's nature and the [types of anomalies](https://victoriametrics.com/blog/victoriametrics-anomaly-detection-handbook-chapter-2/#categories-of-anomalies) to detect. For instance, [Z-score](./components/models.md#z-score) is suitable for data without trends or seasonality, while more complex patterns might require models like [Prophet](./components/models.md#prophet).
 
-Also, starting from [v1.12.0](/anomaly-detection/changelog/#v1120) it's possible to auto-tune the most important params of selected model class, find [the details here](/anomaly-detection/components/models#autotuned).
+Also, starting from [v1.12.0](./CHANGELOG.md#v1120) it's possible to auto-tune the most important params of selected model class, find [the details here](./components/models.md#autotuned).
 
 Please refer to [respective blogpost on anomaly types and alerting heuristics](https://victoriametrics.com/blog/victoriametrics-anomaly-detection-handbook-chapter-2/) for more details.
 
-Still not 100% sure what to use? We are [here to help](/anomaly-detection/#get-in-touch).
+Still not 100% sure what to use? We are [here to help](./README.md#get-in-touch).
 
 ## Alert generation in vmanomaly
-While `vmanomaly` detects anomalies and produces scores, it *does not directly generate alerts*. The anomaly scores are written back to VictoriaMetrics, where an external alerting tool, like [`vmalert`](/vmalert), can be used to create alerts based on these scores for integrating it with your alerting management system.
+While `vmanomaly` detects anomalies and produces scores, it *does not directly generate alerts*. The anomaly scores are written back to VictoriaMetrics, where an external alerting tool, like [`vmalert`](../vmalert.md), can be used to create alerts based on these scores for integrating it with your alerting management system.
 
 ## Preventing alert fatigue
-Produced anomaly scores are designed in such a way that values from 0.0 to 1.0 indicate non-anomalous data, while a value greater than 1.0 is generally classified as an anomaly. However, there are no perfect models for anomaly detection, that's why reasonable defaults expressions like `anomaly_score > 1` may not work 100% of the time. However, anomaly scores, produced by `vmanomaly` are written back as metrics to VictoriaMetrics, where tools like [`vmalert`](/vmalert) can use [MetricsQL](/MetricsQL) expressions to fine-tune alerting thresholds and conditions, balancing between avoiding [false negatives](https://victoriametrics.com/blog/victoriametrics-anomaly-detection-handbook-chapter-1/#false-negative) and reducing [false positives](https://victoriametrics.com/blog/victoriametrics-anomaly-detection-handbook-chapter-1/#false-positive).
+Produced anomaly scores are designed in such a way that values from 0.0 to 1.0 indicate non-anomalous data, while a value greater than 1.0 is generally classified as an anomaly. However, there are no perfect models for anomaly detection, that's why reasonable defaults expressions like `anomaly_score > 1` may not work 100% of the time. However, anomaly scores, produced by `vmanomaly` are written back as metrics to VictoriaMetrics, where tools like [`vmalert`](../vmalert.md) can use [MetricsQL](../MetricsQL.md) expressions to fine-tune alerting thresholds and conditions, balancing between avoiding [false negatives](https://victoriametrics.com/blog/victoriametrics-anomaly-detection-handbook-chapter-1/#false-negative) and reducing [false positives](https://victoriametrics.com/blog/victoriametrics-anomaly-detection-handbook-chapter-1/#false-positive).
 
 ## How to backtest particular configuration on historical data?
-Starting from [v1.7.2](/anomaly-detection/changelog#v172) you can produce (and write back to VictoriaMetrics TSDB) anomaly scores for historical (backtesting) period, using `BacktestingScheduler` [component](/anomaly-detection/components/scheduler#backtesting-scheduler) to imitate consecutive "production runs" of `PeriodicScheduler` [component](/anomaly-detection/components/scheduler#periodic-scheduler). Please find an example config below:
+Starting from [v1.7.2](./CHANGELOG.md#v172) you can produce (and write back to VictoriaMetrics TSDB) anomaly scores for historical (backtesting) period, using `BacktestingScheduler` [component](./components/scheduler.md#backtesting-scheduler) to imitate consecutive "production runs" of `PeriodicScheduler` [component](./components/scheduler.md#periodic-scheduler). Please find an example config below:
 
 ```yaml
 schedulers:
@@ -85,8 +81,6 @@ schedulers:
     # copy these from your PeriodicScheduler args
     fit_window: 'P14D'
     fit_every: 'PT1H'
-    # number of parallel jobs to run. Default is 1, each job is a separate OneOffScheduler fit/inference run.
-    n_jobs: 1
 
 models:
   model_alias1:
@@ -114,12 +108,12 @@ writer:
 # https://docs.victoriametrics.com/anomaly-detection/components/monitoring/
 ```
 
-Configuration above will produce N intervals of full length (`fit_window`=14d + `fit_every`=1h) until `to_iso` timestamp is reached to run N consecutive `fit` calls to train models; Then these models will be used to produce `M = [fit_every / sampling_frequency]` infer datapoints for `fit_every` range at the end of each such interval, imitating M consecutive calls of `infer_every` in `PeriodicScheduler` [config](/anomaly-detection/components/scheduler#periodic-scheduler). These datapoints then will be written back to VictoriaMetrics TSDB, defined in `writer` [section](/anomaly-detection/components/writer#vm-writer) for further visualization (i.e. in VMUI or Grafana)
+Configuration above will produce N intervals of full length (`fit_window`=14d + `fit_every`=1h) until `to_iso` timestamp is reached to run N consecutive `fit` calls to train models; Then these models will be used to produce `M = [fit_every / sampling_frequency]` infer datapoints for `fit_every` range at the end of each such interval, imitating M consecutive calls of `infer_every` in `PeriodicScheduler` [config](./components/scheduler.md#periodic-scheduler). These datapoints then will be written back to VictoriaMetrics TSDB, defined in `writer` [section](./components/writer.md#vm-writer) for further visualization (i.e. in VMUI or Grafana)
 
 ## Resource consumption of vmanomaly
-`vmanomaly` itself is a lightweight service, resource usage is primarily dependent on [scheduling](/anomaly-detection/components/scheduler) (how often and on what data to fit/infer your models), [# and size of timeseries returned by your queries](./components/reader.md#vm-reader), and the complexity of the employed [models](/anomaly-detection/components/models). Its resource usage is directly related to these factors, making it adaptable to various operational scales.
+`vmanomaly` itself is a lightweight service, resource usage is primarily dependent on [scheduling](./components/scheduler.md) (how often and on what data to fit/infer your models), [# and size of timeseries returned by your queries](./components/reader.md#vm-reader), and the complexity of the employed [models](./components/models.md). Its resource usage is directly related to these factors, making it adaptable to various operational scales.
 
-> **Note**: Starting from [v1.13.0](/anomaly-detection/changelog#v1130), there is a mode to save anomaly detection models on host filesystem after `fit` stage (instead of keeping them in-memory by default). **Resource-intensive setups** (many models, many metrics, bigger [`fit_window` arg](/anomaly-detection/components/scheduler#periodic-scheduler-config-example)) and/or 3rd-party models that store fit data (like [ProphetModel](/anomaly-detection/components/models#prophet) or [HoltWinters](/anomaly-detection/components/models#holt-winters)) will have RAM consumption greatly reduced at a cost of slightly slower `infer` stage. To enable it, you need to set environment variable `VMANOMALY_MODEL_DUMPS_DIR` to desired location. [Helm charts](https://github.com/VictoriaMetrics/helm-charts/blob/master/charts/victoria-metrics-anomaly/README.md) are being updated accordingly ([`StatefulSet`](https://kubernetes.io/docs/concepts/workloads/controllers/statefulset/) for persistent storage starting from chart version `1.3.0`).
+> **Note**: Starting from [v1.13.0](./CHANGELOG.md#v1130), there is a mode to save anomaly detection models on host filesystem after `fit` stage (instead of keeping them in-memory by default). **Resource-intensive setups** (many models, many metrics, bigger [`fit_window` arg](./components/scheduler.md#periodic-scheduler-config-example)) and/or 3rd-party models that store fit data (like [ProphetModel](./components/models.md#prophet) or [HoltWinters](./components/models.md#holt-winters)) will have RAM consumption greatly reduced at a cost of slightly slower `infer` stage. To enable it, you need to set environment variable `VMANOMALY_MODEL_DUMPS_DIR` to desired location. [Helm charts](https://github.com/VictoriaMetrics/helm-charts/blob/master/charts/victoria-metrics-anomaly/README.md) are being updated accordingly ([`StatefulSet`](https://kubernetes.io/docs/concepts/workloads/controllers/statefulset/) for persistent storage starting from chart version `1.3.0`).
 
 Here's an example of how to set it up in docker-compose using volumes:
 ```yaml
@@ -153,16 +147,16 @@ volumes:
 ## Scaling vmanomaly
 > **Note:** As of latest release we don't support cluster or auto-scaled version yet (though, it's in our roadmap for - better backends, more parallelization, etc.), so proposed workarounds should be addressed manually.
 
-`vmanomaly` can be scaled horizontally by launching multiple independent instances, each with its own [MetricsQL](/MetricsQL) queries and [configurations](/anomaly-detection/components/):
+`vmanomaly` can be scaled horizontally by launching multiple independent instances, each with its own [MetricsQL](../MetricsQL.md) queries and [configurations](./components/README.md):
 
-- By splitting **queries**, [defined in reader section](/anomaly-detection/components/reader#vm-reader) and spawn separate service around it. Also in case you have *only 1 query returning huge amount of timeseries*, you can further split it by applying MetricsQL filters, i.e. using "extra_filters" [param in reader](/anomaly-detection/components/reader?highlight=extra_filters#vm-reader)
+- By splitting **queries**, [defined in reader section](./components/reader.md#vm-reader) and spawn separate service around it. Also in case you have *only 1 query returning huge amount of timeseries*, you can further split it by applying MetricsQL filters, i.e. using "extra_filters" [param in reader](./components/reader.md#vm-reader)
 
-- or **models** (in case you decide to run several models for each timeseries received i.e. for averaging anomaly scores in your alerting rules of `vmalert` or using a vote approach to reduce false positives) - see `queries` arg in [model config](/anomaly-detection/components/models#queries)
+- or **models** (in case you decide to run several models for each timeseries received i.e. for averaging anomaly scores in your alerting rules of `vmalert` or using a vote approach to reduce false positives) - see `queries` arg in [model config](./components/models.md#queries)
 
-- or **schedulers** (in case you want the same models to be trained under several schedules) - see `schedulers` arg [model section](/anomaly-detection/components/models#schedulers) and `scheduler` [component itself](/anomaly-detection/components/scheduler)
+- or **schedulers** (in case you want the same models to be trained under several schedules) - see `schedulers` arg [model section](./components/models.md#schedulers) and `scheduler` [component itself](./components/scheduler.md)
 
 
-Here's an example of how to split on `extra_filters`, based on `extra_filters` reader's arg
+Here's an example of how to split on `extra_filters` param
 ```yaml
 # config file #1, for 1st vmanomaly instance
 # ...

docs/anomaly-detection/Presets.md

@@ -23,14 +23,17 @@ Additionally, **preset mode** minimizes user input needed to run the service. Yo
 Available presets:
 - [Node-Exporter](#node-exporter)
 
-To enable preset mode, `preset` arg should be set to particular preset name:
+Here is an example config file to enable [Node-Exporter](#node-exporter) preset:
 
 ```yaml
-preset: "chosen_preset_name"  # i.e. "node-exporter"
+preset: "node-exporter"
+reader:
+  datasource_url: "http://victoriametrics:8428/" # your datasource url
+  # tenant_id: '0:0'  # specify for cluster version
+writer:
+  datasource_url: "http://victoriametrics:8428/" # your datasource url
+  # tenant_id: '0:0'  # specify for cluster version
 ```
-
-Also, additional minimal set of arguments may be required from user to run the preset. See corresponding preset sections below for the details.
-
 Run a service using config file with one of the [available options](./QuickStart.md#how-to-install-and-run-vmanomaly).
 
 After you run `vmanomaly` with `preset` arg specified, available assets can be viewed, copied and downloaded at `http://localhost:8490/presets/` endpoint.
@@ -40,24 +43,13 @@ After you run `vmanomaly` with `preset` arg specified, available assets can be v
 
 ## Node-Exporter
 
-The Node-Exporter preset simplifies the monitoring and anomaly detection of key system metrics collected by [`node_exporter`](https://github.com/prometheus/node_exporter). This preset reduces the need for manual configuration and detects anomalies in metrics such as CPU usage, network errors, and disk latency, ensuring timely identification of potential issues. Below are detailed instructions on enabling and using the Node-Exporter preset, along with a list of included assets like alerting rules and Grafana dashboard.
-
-> **Note: Node-Exporter preset assets can be also found [here](https://github.com/VictoriaMetrics/VictoriaMetrics/tree/master/deployment/docker/vmanomaly/vmanomaly-node-exporter-preset/)**
-
-For enabling Node-Exporter in config file set the `preset` arg accordingly. Also, include at least `datasource_url`-s (and `tenant_id` if using cluster version of VictoriaMetrics) in reader and writer sections, like that:
+> **Note: Preset assets can be also found [here](https://github.com/VictoriaMetrics/VictoriaMetrics/tree/master/deployment/docker/vmanomaly/vmanomaly-node-exporter-preset/)**
 
+For enabling Node-Exporter in config file use `preset` parameter:
 ```yaml
 preset: "node-exporter"
-reader:
-  datasource_url: "http://victoriametrics:8428/" # source victoriametrics/prometheus
-  # tenant_id: '0:0'  # specify for cluster version
-writer:
-  datasource_url: "http://victoriametrics:8428/" # destination victoriametrics/prometheus
-  # tenant_id: '0:0'  # specify for cluster version
 ```
 
-Run a service using such config file with one of the [available options](./QuickStart.md#how-to-install-and-run-vmanomaly).
-
 ### Generated anomaly scores
 Machine learning models will be fit for each timeseries, returned by underlying [MetricsQL](../MetricsQL.md) queries.
 Anomaly score metric labels will also contain [model classes](./components/models.md) and [schedulers](./components/scheduler.md) for labelset uniqueness.

docs/anomaly-detection/components/reader.md

@@ -20,61 +20,6 @@ Future updates will introduce additional readers, expanding the range of data so
 
 ## VM reader
 
-> **Note**: Starting from [v1.13.0](/anomaly-detection/changelog/v1130) there is backward-compatible change of [`queries`](/anomaly-detection/components/reader?highlight=queries#vm-reader) arg of [VmReader](#vm-reader). New format allows to specify per-query parameters, like `step` to reduce amount of data read from VictoriaMetrics TSDB and to allow config flexibility. Please see [per-query parameters](#per-query-parameters) section for the details.
-
-Old format like
-
-```yaml
-# other config sections ...
-reader:
-  class: 'vm'
-  datasource_url: 'http://localhost:8428'  # source victoriametrics/prometheus
-  sampling_period: "10s"  # set it <= min(infer_every) in schedulers section
-  queries:
-    # old format {query_alias: query_expr}, prior to 1.13, will be converted to a new format automatically
-    vmb: 'avg(vm_blocks)'
-```
-
-will be converted to a new one with a warning raised in logs:
-
-```yaml
-# other config sections ...
-reader:
-  class: 'vm'
-  datasource_url: 'http://localhost:8428'  # source victoriametrics/prometheus
-  sampling_period: '10s'
-  queries:
-    # old format {query_alias: query_expr}, prior to 1.13, will be converted to a new format automatically
-    vmb:
-      expr: 'avg(vm_blocks)'  # initial MetricsQL expression
-      step: '10s'  # individual step for this query, will be filled with `sampling_period` from the root level
-      # new query-level arguments will be added in backward-compatible way in future releases
-```
-
-### Per-query parameters
-
-Starting from [v1.13.0](/anomaly-detection/changelog/v1130) there is change of [`queries`](/anomaly-detection/components/reader?highlight=queries#vm-reader) arg format. Now each query alias supports the next (sub)fields:
-
-- `expr` (string): MetricsQL/PromQL expression that defines an input for VmReader. As accepted by `/query_range?query=%s`. i.e. `avg(vm_blocks)`
-
-- `step` (string): query-level frequency of the points returned, i.e. `30s`. Will be converted to `/query_range?step=%s` param (in seconds). Useful to optimize total amount of data read from VictoriaMetrics, where different queries may have **different frequencies for different [machine learning models](/anomaly-detection/components/models)** to run on.
-
-    > **Note**: if not set explicitly (or if older config style prior to [v1.13.0](/anomaly-detection/changelog/v1130)) is used, then it is set to reader-level `sampling_period` arg.
-
-    > **Note**: having **different** individual `step` args for queries (i.e. `30s` for `q1` and `2m` for `q2`) is not yet supported for [multivariate model](/anomaly-detection/components/models/index.html#multivariate-models) if you want to run it on several queries simultaneously (i.e. setting [`queries`](/anomaly-detection/components/models/#queries) arg of a model to [`q1`, `q2`]).
-
-### Per-query config example
-```yaml
-reader:
-  class: 'vm'
-  sampling_period: '1m'
-  # other reader params ...
-  queries:
-    ingestion_rate:
-      expr: 'sum(rate(vm_rows_inserted_total[5m])) by (type) > 0'
-      step: '2m'  # overrides global `sampling_period` of 1m
-```
-
 ### Config parameters
 
 <table class="params">
@@ -106,12 +51,12 @@ Name of the class needed to enable reading from VictoriaMetrics or Prometheus. V
 `queries`
             </td>
             <td>
-                See [per-query config example](#per-query-config-example) above
+
+`ingestion_rate: 'sum(rate(vm_rows_inserted_total[5m])) by (type) > 0'`
             </td>
+            <td>
 
-<td>
-
-See [per-query config section](#per-query-parameters) above
+PromQL/MetricsQL query to select data in format: `QUERY_ALIAS: "QUERY"`. As accepted by `/query_range?query=%s`.
             </td>
         </tr>
         <tr>

docs/data-ingestion/Proxmox.md

@@ -16,7 +16,7 @@ Since Proxmox Virtual Environment(PVE) and Proxmox Backup Server(PBS) support se
 Currently PVE and PBS only support using an Authorization Token for authentication and does not support basic auth or a username and password.
 
 ## Proxmox Virtual Environment (PVE)
-If want help Sending your data to VictoriaMetrics Cloud check out [our blog](https://victoriametrics.com/blog/proxmox-monitoring-with-dbaas/).
+If want help Sending your data to Managed VictoriaMetrics check out [our blog](https://victoriametrics.com/blog/proxmox-monitoring-with-dbaas/).
 
 1. Login to PVE as an administrator
 2. Go to DataCenter > MetricServer > Add > InfluxDB
@@ -65,4 +65,4 @@ You should see 1 time series per node in your PVE cluster.
 
 
 # References
-- [Blog Post for configuring VictoriaMetrics Cloud and Proxmox VE](https://victoriametrics.com/blog/proxmox-monitoring-with-dbaas/)
+- [Blog Post for configuring Managed VictoriaMetrics and Proxmox VE](https://victoriametrics.com/blog/proxmox-monitoring-with-dbaas/)

docs/enterprise.md

@@ -1,10 +1,9 @@
 ---
 sort: 99
 weight: 99
-title: Enterprise
+title: VictoriaMetrics Enterprise
 menu:
   docs:
-    identifier: vm-enterprise
     parent: 'victoriametrics'
     weight: 99
 aliases:
@@ -29,7 +28,7 @@ The use of VictoriaMetrics Enterprise components is permitted in the following c
 - Production use if you have a valid enterprise contract or valid permit from VictoriaMetrics company.
   Please contact us via [this page](https://victoriametrics.com/products/enterprise/) if you are intereseted in such a contract.
 
-- [VictoriaMetrics Cloud](https://docs.victoriametrics.com/victoriametrics-cloud/) is built on top of VictoriaMetrics Enterprise.
+- [Managed VictoriaMetrics](https://docs.victoriametrics.com/managed-victoriametrics/) is built on top of VictoriaMetrics Enterprise.
 
 See [these docs](#running-victoriametrics-enterprise) for details on how to run VictoriaMetrics enterprise.
 

docs/goals.md

@@ -1,7 +1,7 @@
 ---
 sort: 500
 weight: 500
-title: Development goals
+title: VictoriaMetrics development goals
 menu:
   docs:
     parent: 'victoriametrics'

docs/guides/README.md

@@ -0,0 +1,11 @@
+1. [K8s monitoring via VM Single](k8s-monitoring-via-vm-single.html)
+1. [K8s monitoring via VM Cluster](k8s-monitoring-via-vm-cluster.html)
+1. [HA monitoring setup in K8s via VM Cluster](k8s-ha-monitoring-via-vm-cluster.html)
+1. [Getting started with VM Operator](getting-started-with-vm-operator.html)
+1. [Multi Retention Setup within VictoriaMetrics Cluster](guide-vmcluster-multiple-retention-setup.html)
+1. [Migrate from InfluxDB to VictoriaMetrics](migrate-from-influx.html)
+1. [Multi-regional setup with VictoriaMetrics: Dedicated regions for monitoring](multi-regional-setup-dedicated-regions.html)
+1. [How to delete or replace metrics in VictoriaMetrics](guide-delete-or-replace-metrics.html)
+1. [How to monitor kubernetes cluster using Managed VictoriaMetrics](/managed-victoriametrics/how-to-monitor-k8s.html)
+1. [How to configure vmgateway for multi-tenant access using Grafana and OpenID Connect](grafana-vmgateway-openid-configuration.html)
+1. [How to setup vmanomaly together with vmalert](/anomaly-detection/guides/guide-vmanomaly-vmalert/README.md)

docs/guides/_index.md

@@ -2,5 +2,4 @@
 weight: 0
 title: Guides
 disableToc: true
----
-{{% section %}}
+---

docs/guides/understand-your-setup-size.md

@@ -8,7 +8,7 @@ menu:
 aliases:
 - /guides/understand-your-setup-size.html
 ---
-The docs provide a simple and high-level overview of Ingestion Rate, Active Time Series, and Query per Second. These terms are a part of capacity planning ([Single-Node](https://docs.victoriametrics.com/single-server-victoriametrics/#capacity-planning), [Cluster](https://docs.victoriametrics.com/cluster-victoriametrics/#capacity-planning)) and [VictoriaMetrics Cloud](https://docs.victoriametrics.com/victoriametrics-cloud/) pricing.
+The docs provide a simple and high-level overview of Ingestion Rate, Active Time Series, and Query per Second. These terms are a part of capacity planning ([Single-Node](https://docs.victoriametrics.com/single-server-victoriametrics/#capacity-planning), [Cluster](https://docs.victoriametrics.com/cluster-victoriametrics/#capacity-planning)) and [Managed VictoriaMetrics](https://docs.victoriametrics.com/managed-victoriametrics/) pricing.
 
 ## Terminology
 
@@ -101,12 +101,12 @@ You have a Kubernetes environment that produces 5k time series per second with 1
 VictoriaMetrics requires additional disk space for the index. The lower Churn Rate means lower disk space usage for the index because of better compression.
 Usually, the index takes about 20% of the disk space for storing data. High cardinality setups may use >50% of datapoints storage size for index.
 
-You can significantly reduce the amount of disk usage by specifying [Downsampling](https://docs.victoriametrics.com/#downsampling) and [Retention Filters](https://docs.victoriametrics.com/#retention-filters) that are lower than the Retention Period. Both two settings are available in VictoriaMetrics Cloud and Enterprise.
+You can significantly reduce the amount of disk usage by specifying [Downsampling](https://docs.victoriametrics.com/#downsampling) and [Retention Filters](https://docs.victoriametrics.com/#retention-filters) that are lower than the Retention Period. Both two settings are available in Managed VictoriaMetrics and Enterprise.
 
 
 ## Align Terms with VictoriaMetrics setups
 
-### VictoriaMetrics Cloud
+### Managed VictoriaMetrics
 
 Every deployment (Single-Node or Cluster) contains the expected load in Ingestion Rate and Active Time Series. We assume that the Churn Rate is no more than 30%. You may need to choose a more extensive deployment if you have a higher Churn Rate.
 

docs/keyConcepts.md

@@ -4,8 +4,7 @@ weight: 34
 title: Key concepts
 menu:
   docs:
-    identifier: vm-key-concepts
-    parent: victoriametrics
+    parent: 'victoriametrics'
     weight: 34
 aliases:
 - /keyConcepts.html

docs/managed-victoriametrics/README.md

@@ -0,0 +1,14 @@
+* [Overview of Managed VictoriaMetrics](/managed-victoriametrics/overview/)
+* [Quick Start](/managed-victoriametrics/quickstart/)
+
+## Guides
+* [Understand Your Setup Size](/guides/understand-your-setup-size/)
+* [Alerting & recording rules with Alertmanager configuration for Managed VictoriaMetrics deployment](/managed-victoriametrics/alertmanager-setup-for-deployment/)
+* [Kubernetes Monitoring with Managed VictoriaMetrics](/managed-victoriametrics/how-to-monitor-k8s/)
+* [Setup Notifications](/managed-victoriametrics/setup-notifications/)
+* [User Management](/managed-victoriametrics/user-managment/)
+
+Learn more about Managed VictoriaMetrics:
+* [Managed VictoriaMetrics announcement](https://victoriametrics.com/blog/managed-victoriametrics-announcement)
+* [Pricing comparison for Managed Prometheus](https://victoriametrics.com/blog/managed-prometheus-pricing/)
+* [Monitoring Proxmox VE via Managed VictoriaMetrics and vmagent](https://victoriametrics.com/blog/proxmox-monitoring-with-dbaas/)

docs/managed-victoriametrics/_index.md

@@ -0,0 +1,7 @@
+---
+sort: 28
+title: Managed VictoriaMetrics
+weight: 01
+disableToc: true
+---
+{{% content "README.md" %}}

docs/managed-victoriametrics/alerting-vmalert-managed-victoria-metrics.md

@@ -1,25 +1,23 @@
 ---
 sort: 5
 weight: 5
-title: Alerting with vmalert and VictoriaMetrics Cloud
+title: Alerting with vmalert and Managed VictoriaMetrics
 menu:
   docs:
-    parent: "cloud"
+    parent: "managed"
     weight: 5
 aliases:
-  - /victoriametrics-cloud/alerting-vmalert-victoria-metrics-cloud/index.html
-  - /managed-victoriametrics/alerting-vmalert-victoria-metrics-cloud/index.html
+- /managed-victoriametrics/alerting-vmalert-managed-victoria-metrics.html
 ---
+This guide explains the different ways in which you can use vmalert in conjunction with Managed VictoriaMetrics
 
-This guide explains the different ways in which you can use vmalert in conjunction with VictoriaMetrics Cloud
-
-![Metrics setup](alerting-vmalert-victoria-metrics-cloud_setup.webp)
+![Metrics setup](alerting-vmalert-managed-victoria-metrics_setup.webp)
 
 ## Preconditions 
 
 * [vmalert](https://docs.victoriametrics.com/vmalert/) is installed. You can obtain it by building it from [source](https://docs.victoriametrics.com/vmalert/#quickstart), downloading it from the [GitHub releases page](https://github.com/VictoriaMetrics/VictoriaMetrics/releases/latest), or using the [docker image](https://hub.docker.com/r/victoriametrics/vmalert) for the container ecosystem (such as docker, k8s, etc.).
 * [Alertmanager](https://prometheus.io/docs/alerting/latest/alertmanager/) is installed.
-* You have a [single or cluster](https://docs.victoriametrics.com/victoriametrics-cloud/quickstart.html#creating-deployment) deployment in [VictoriaMetrics Cloud](https://docs.victoriametrics.com/victoriametrics-cloud/overview.html).
+* You have a [single or cluster](https://docs.victoriametrics.com/managed-victoriametrics/quickstart.html#creating-deployment) deployment in [Managed VictoriaMetrics](https://docs.victoriametrics.com/managed-victoriametrics/overview.html).
 * If you are using helm, add the [VictoriaMetrics helm chart](https://github.com/VictoriaMetrics/helm-charts/tree/master/charts/victoria-metrics-alert#how-to-install) repository to your helm repositories. This step is optional.
 * If you are using [vmoperator](https://docs.victoriametrics.com/operator/quick-start.html#quick-start), make sure that it and its CRDs are installed. This step is also optional.
 
@@ -47,22 +45,22 @@ groups:
         description: "Job {{ $labels.job }}  instance: {{$labels.instance }} is not up for the last 1 minute"
 ```
 
-### VictoriaMetrics Cloud access token and deployment endpoint
+### Managed VictoriaMetrics access token and deployment endpoint
 
-To use vmalert with VictoriaMetrics Cloud, you must create a read/write token, or use an existing one. The token must have write access to ingest recording rules, ALERTS and ALERTS_FOR_STATE metrics, and read access for rules evaluation.
+To use vmalert with Managed VictoriaMetrics, you must create a read/write token, or use an existing one. The token must have write access to ingest recording rules, ALERTS and ALERTS_FOR_STATE metrics, and read access for rules evaluation.
 
-For instructions on how to create tokens, please refer to this section of the [documentation](https://docs.victoriametrics.com/victoriametrics-cloud/quickstart.html#deployment-access).
+For instructions on how to create tokens, please refer to this section of the [documentation](https://docs.victoriametrics.com/managed-victoriametrics/quickstart.html#deployment-access).
 
 #### Single-Node
 
-![Token created single](alerting-vmalert-victoria-metrics-cloud_token_created_single.webp)
-![Copy datasource single](alerting-vmalert-victoria-metrics-cloud_copy_datasource_single.webp)
+![Token created single](alerting-vmalert-managed-victoria-metrics_token_created_single.webp)
+![Copy datasource single](alerting-vmalert-managed-victoria-metrics_copy_datasource_single.webp)
 
 #### Cluster
 
-![Token created cluster](alerting-vmalert-victoria-metrics-cloud_token_created_cluster.webp)
-![Reading datasource cluster](alerting-vmalert-victoria-metrics-cloud_copy_reading_datasource_cluster.webp)
-![Writing atasource cluster](alerting-vmalert-victoria-metrics-cloud_copy_writing_datasource_cluster.webp)
+![Token created cluster](alerting-vmalert-managed-victoria-metrics_token_created_cluster.webp)
+![Reading datasource cluster](alerting-vmalert-managed-victoria-metrics_copy_reading_datasource_cluster.webp)
+![Writing atasource cluster](alerting-vmalert-managed-victoria-metrics_copy_writing_datasource_cluster.webp)
 
 ### vmalert configuration 
 

docs/managed-victoriametrics/alertmanager-setup-for-deployment.md

@@ -1,16 +1,15 @@
 ---
 sort: 4
 weight: 4
-title: Alertmanager and VMAlert configuration for VictoriaMetrics Cloud deployment
+title: Alertmanager and VMAlert configuration for Managed VictoriaMetrics deployment
 menu:
   docs:
-    parent: "cloud"
+    parent: "managed"
     weight: 4
 aliases:
-  - /victoriametrics-cloud/alertmanager-setup-for-deployment/index.html
-  - /managed-victoriametrics/alertmanager-setup-for-deployment/index.html
+  - /managed-victoriametrics/alertmanager-setup-for-deployment.html
 ---
-VictoriaMetrics Cloud supports configuring alerting rules, powered by vmalert, and sending notifications with hosted Alertmanager.
+Managed VictoriaMetrics supports configuring alerting rules, powered by vmalert, and sending notifications with hosted Alertmanager.
 
 ## Configure Alertmanager
 
@@ -38,7 +37,7 @@ Alertmanager is now set up for your deployment, and you be able to get notificat
 
 ### Alertmanager config specification
 
-VictoriaMetrics Cloud supports Alertmanager with standard [configuration specification](https://prometheus.io/docs/alerting/latest/configuration/).
+Managed VictoriaMetrics supports Alertmanager with standard [configuration specification](https://prometheus.io/docs/alerting/latest/configuration/).
 
 But with respect to the specification, there are the following limitations:
 
@@ -123,7 +122,7 @@ receivers:
 
 ### Custom Alertmanager
 
-If for some reason Cloud Alertmanager is not suitable for you, you can use VictoriaMetrics Cloud with any external Alertmanager hosted in your infrastructure.
+If for some reason Cloud Alertmanager is not suitable for you, you can use Managed VictoriaMetrics with any external Alertmanager hosted in your infrastructure.
 
 For that select Custom Alertmanager instead of Cloud Alertmanager when [creating the Alertmanager](#configure-alertmanager):
 

docs/managed-victoriametrics/how-to-monitor-k8s.md

@@ -1,14 +1,13 @@
 ---
 sort: 3
 weight: 3
-title: Kubernetes Monitoring with VictoriaMetrics Cloud
+title: Kubernetes Monitoring with Managed VictoriaMetrics
 menu:
   docs:
-    parent: "cloud"
+    parent: "managed"
     weight: 3
 aliases:
-  - /victoriametrics-cloud/how-to-monitor-k8s/index.html
-  - /managed-victoriametrics/how-to-monitor-k8s/index.html
+- /managed-victoriametrics/how-to-monitor-k8s.html
 ---
 Monitoring kubernetes cluster is necessary to build SLO/SLI, to analyze performance and cost-efficiency of your workloads. 
 
@@ -25,8 +24,7 @@ This chart will install `VMOperator`, `VMAgent`, `NodeExporter`, `kube-state-met
 
 ## Prerequisites
 
-
-- Active VictoriaMetrics Cloud instance. You can learn how to sign up for VictoriaMetrics Cloud [here](https://docs.victoriametrics.com/victoriametrics-cloud/quickstart.html#how-to-register).
+- Active Managed VictoriaMetrics instance. You can learn how to sign up for Managed VictoriaMetrics [here](https://docs.victoriametrics.com/managed-victoriametrics/quickstart.html#how-to-register). 
 - Access to your kubernetes cluster
 - Helm binary. You can find installation [here](https://helm.sh/docs/intro/install/)