VictoriaMetrics

Versiones compatibles: VictoriaMetrics 1.x Última actualización: February 20, 2026

Tabla de contenidos

Introducción
Opciones de arquitectura
Modo de nodo único
Modo de clúster
vmagent
vmalert
MetricsQL
Instalación con Helm
Configuración de almacenamiento a largo plazo
Downsampling
Optimización del rendimiento
Prácticas recomendadas
Solución de problemas

Introducción

VictoriaMetrics es una base de datos de series temporales y una solución de monitoreo de alto rendimiento y rentable. Aunque es totalmente compatible con Prometheus, ofrece mejores tasas de compresión, rendimiento de consultas y escalabilidad.

Características principales

Característica	Descripción
Alta compresión	Compresión de datos hasta 7 veces más eficiente que Prometheus
Rendimiento rápido de consultas	Rendimiento hasta 20 veces más rápido en consultas complejas
Escalado horizontal	Escalado ilimitado en modo de clúster
Baja sobrecarga operativa	Despliegue de un único binario y configuración mínima
Compatible con Prometheus	Compatibilidad completa con PromQL y la API de Remote Write/Read
Multi-tenancy	Entornos aislados para múltiples equipos/proyectos
Almacenamiento a largo plazo	Almacenamiento eficiente de métricas a largo plazo y downsampling

VictoriaMetrics frente a Prometheus

Elemento	Prometheus	VictoriaMetrics
Arquitectura	Nodo único	Único/Clúster
Escalado horizontal	Requiere Thanos/Cortex	Compatibilidad nativa
Uso de disco	Referencia	~70 % de reducción
Velocidad de consulta	Referencia	2-20 veces más rápida
Uso de memoria	Alto	Bajo
Límite de cardinalidad	~10 M de series temporales	~100 M+ de series temporales
Lenguaje de consulta	PromQL	MetricsQL (superconjunto)

Opciones de arquitectura

VictoriaMetrics ofrece dos modos de despliegue:

Guía de selección

Modo de nodo único

El modo de nodo único (vmsingle) es adecuado para entornos pequeños y medianos.

Características

Un único binario proporciona toda la funcionalidad
Configuración y operación sencillas
Capaz de procesar millones de muestras por segundo
Compatible con miles de millones de series temporales activas

Despliegue de StatefulSet

yaml

apiVersion: apps/v1
kind: StatefulSet
metadata:
  name: vmsingle
  namespace: monitoring
spec:
  serviceName: "vmsingle"
  replicas: 1
  selector:
    matchLabels:
      app: vmsingle
  template:
    metadata:
      labels:
        app: vmsingle
    spec:
      containers:
      - name: vmsingle
        image: victoriametrics/victoria-metrics:v1.96.0
        args:
          - "--storageDataPath=/storage"
          - "--httpListenAddr=:8428"
          - "--retentionPeriod=1y"
          - "--search.latencyOffset=30s"
          - "--search.maxUniqueTimeseries=1000000"
          - "--search.maxSamplesPerQuery=1000000000"
          # Memory optimization
          - "--memory.allowedPercent=60"
          # Compression settings
          - "--dedup.minScrapeInterval=30s"
        ports:
        - containerPort: 8428
          name: http
        resources:
          requests:
            cpu: 500m
            memory: 2Gi
          limits:
            cpu: 2000m
            memory: 8Gi
        volumeMounts:
        - name: storage
          mountPath: /storage
        livenessProbe:
          httpGet:
            path: /health
            port: 8428
          initialDelaySeconds: 30
          periodSeconds: 30
        readinessProbe:
          httpGet:
            path: /health
            port: 8428
          initialDelaySeconds: 5
          periodSeconds: 15
      securityContext:
        fsGroup: 65534
        runAsNonRoot: true
        runAsUser: 65534
  volumeClaimTemplates:
  - metadata:
      name: storage
    spec:
      accessModes: ["ReadWriteOnce"]
      storageClassName: gp3
      resources:
        requests:
          storage: 100Gi
---
apiVersion: v1
kind: Service
metadata:
  name: vmsingle
  namespace: monitoring
spec:
  selector:
    app: vmsingle
  ports:
  - port: 8428
    targetPort: 8428
    name: http
  type: ClusterIP

Endpoints principales

Endpoint	Descripción
`/api/v1/write`	Prometheus Remote Write
`/api/v1/query`	Consulta instantánea
`/api/v1/query_range`	Consulta de rango
`/api/v1/series`	Metadatos de series
`/api/v1/labels`	Lista de labels
`/api/v1/label/{name}/values`	Lista de valores de labels
`/vmui`	UI integrada
`/metrics`	Métricas propias

Modo de clúster

Configuración de clúster escalable para entornos a gran escala.

Arquitectura

Componentes

Componente	Función	Método de escalado
vminsert	Enrutamiento de solicitudes de escritura	Escalado horizontal (Deployment)
vmstorage	Almacenamiento de datos	Escalado horizontal (StatefulSet)
vmselect	Procesamiento de consultas	Escalado horizontal (Deployment)

Despliegue de vmstorage

yaml

apiVersion: apps/v1
kind: StatefulSet
metadata:
  name: vmstorage
  namespace: monitoring
spec:
  serviceName: "vmstorage"
  replicas: 3
  selector:
    matchLabels:
      app: vmstorage
  template:
    metadata:
      labels:
        app: vmstorage
    spec:
      containers:
      - name: vmstorage
        image: victoriametrics/vmstorage:v1.96.0-cluster
        args:
          - "--storageDataPath=/storage"
          - "--httpListenAddr=:8482"
          - "--vminsertAddr=:8400"
          - "--vmselectAddr=:8401"
          - "--retentionPeriod=1y"
          - "--dedup.minScrapeInterval=30s"
        ports:
        - containerPort: 8482
          name: http
        - containerPort: 8400
          name: vminsert
        - containerPort: 8401
          name: vmselect
        resources:
          requests:
            cpu: 500m
            memory: 2Gi
          limits:
            cpu: 2000m
            memory: 8Gi
        volumeMounts:
        - name: storage
          mountPath: /storage
        livenessProbe:
          httpGet:
            path: /health
            port: 8482
          initialDelaySeconds: 30
          periodSeconds: 30
      affinity:
        podAntiAffinity:
          requiredDuringSchedulingIgnoredDuringExecution:
          - labelSelector:
              matchLabels:
                app: vmstorage
            topologyKey: kubernetes.io/hostname
  volumeClaimTemplates:
  - metadata:
      name: storage
    spec:
      accessModes: ["ReadWriteOnce"]
      storageClassName: gp3
      resources:
        requests:
          storage: 100Gi
---
apiVersion: v1
kind: Service
metadata:
  name: vmstorage
  namespace: monitoring
spec:
  selector:
    app: vmstorage
  clusterIP: None
  ports:
  - port: 8482
    name: http
  - port: 8400
    name: vminsert
  - port: 8401
    name: vmselect

Despliegue de vminsert

yaml

apiVersion: apps/v1
kind: Deployment
metadata:
  name: vminsert
  namespace: monitoring
spec:
  replicas: 3
  selector:
    matchLabels:
      app: vminsert
  template:
    metadata:
      labels:
        app: vminsert
    spec:
      containers:
      - name: vminsert
        image: victoriametrics/vminsert:v1.96.0-cluster
        args:
          - "--httpListenAddr=:8480"
          - "--storageNode=vmstorage-0.vmstorage:8400"
          - "--storageNode=vmstorage-1.vmstorage:8400"
          - "--storageNode=vmstorage-2.vmstorage:8400"
          - "--replicationFactor=2"
        ports:
        - containerPort: 8480
          name: http
        resources:
          requests:
            cpu: 200m
            memory: 256Mi
          limits:
            cpu: 1000m
            memory: 1Gi
        livenessProbe:
          httpGet:
            path: /health
            port: 8480
          initialDelaySeconds: 10
          periodSeconds: 30
---
apiVersion: v1
kind: Service
metadata:
  name: vminsert
  namespace: monitoring
spec:
  selector:
    app: vminsert
  ports:
  - port: 8480
    targetPort: 8480
    name: http
  type: ClusterIP

Despliegue de vmselect

yaml

apiVersion: apps/v1
kind: Deployment
metadata:
  name: vmselect
  namespace: monitoring
spec:
  replicas: 3
  selector:
    matchLabels:
      app: vmselect
  template:
    metadata:
      labels:
        app: vmselect
    spec:
      containers:
      - name: vmselect
        image: victoriametrics/vmselect:v1.96.0-cluster
        args:
          - "--httpListenAddr=:8481"
          - "--storageNode=vmstorage-0.vmstorage:8401"
          - "--storageNode=vmstorage-1.vmstorage:8401"
          - "--storageNode=vmstorage-2.vmstorage:8401"
          - "--search.maxUniqueTimeseries=1000000"
          - "--search.maxSamplesPerQuery=1000000000"
        ports:
        - containerPort: 8481
          name: http
        resources:
          requests:
            cpu: 200m
            memory: 512Mi
          limits:
            cpu: 1000m
            memory: 2Gi
        livenessProbe:
          httpGet:
            path: /health
            port: 8481
          initialDelaySeconds: 10
          periodSeconds: 30
---
apiVersion: v1
kind: Service
metadata:
  name: vmselect
  namespace: monitoring
spec:
  selector:
    app: vmselect
  ports:
  - port: 8481
    targetPort: 8481
    name: http
  type: ClusterIP

vmagent

vmagent es un agente ligero para la recopilación y el reenvío de métricas.

Características principales

Compatible con la configuración de scrape de Prometheus
Compatible con múltiples destinos de Remote Write
Búfer y retransmisión de datos
Bajo uso de recursos
Reescritura y filtrado de labels

Despliegue

yaml

apiVersion: apps/v1
kind: Deployment
metadata:
  name: vmagent
  namespace: monitoring
spec:
  replicas: 2
  selector:
    matchLabels:
      app: vmagent
  template:
    metadata:
      labels:
        app: vmagent
    spec:
      serviceAccountName: vmagent
      containers:
      - name: vmagent
        image: victoriametrics/vmagent:v1.96.0
        args:
          - "--promscrape.config=/etc/vmagent/prometheus.yml"
          - "--remoteWrite.url=http://vminsert:8480/insert/0/prometheus/api/v1/write"
          - "--remoteWrite.tmpDataPath=/tmp/vmagent-remotewrite-data"
          - "--remoteWrite.maxDiskUsagePerURL=1GB"
          - "--promscrape.cluster.membersCount=2"
          - "--promscrape.cluster.memberNum=$(POD_INDEX)"
        env:
        - name: POD_INDEX
          valueFrom:
            fieldRef:
              fieldPath: metadata.name
        ports:
        - containerPort: 8429
          name: http
        resources:
          requests:
            cpu: 100m
            memory: 256Mi
          limits:
            cpu: 500m
            memory: 1Gi
        volumeMounts:
        - name: config
          mountPath: /etc/vmagent
        - name: tmpdata
          mountPath: /tmp/vmagent-remotewrite-data
      volumes:
      - name: config
        configMap:
          name: vmagent-config
      - name: tmpdata
        emptyDir: {}
---
apiVersion: v1
kind: ConfigMap
metadata:
  name: vmagent-config
  namespace: monitoring
data:
  prometheus.yml: |
    global:
      scrape_interval: 30s
      scrape_timeout: 10s

    scrape_configs:
      - job_name: 'kubernetes-pods'
        kubernetes_sd_configs:
          - role: pod
        relabel_configs:
          - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]
            action: keep
            regex: true
          - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_path]
            action: replace
            target_label: __metrics_path__
            regex: (.+)
          - source_labels: [__address__, __meta_kubernetes_pod_annotation_prometheus_io_port]
            action: replace
            regex: ([^:]+)(?::\d+)?;(\d+)
            replacement: $1:$2
            target_label: __address__
          - source_labels: [__meta_kubernetes_namespace]
            target_label: namespace
          - source_labels: [__meta_kubernetes_pod_name]
            target_label: pod

      - job_name: 'kubernetes-nodes'
        kubernetes_sd_configs:
          - role: node
        scheme: https
        tls_config:
          ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
          insecure_skip_verify: true
        bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
        relabel_configs:
          - action: labelmap
            regex: __meta_kubernetes_node_label_(.+)
---
apiVersion: v1
kind: ServiceAccount
metadata:
  name: vmagent
  namespace: monitoring
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: vmagent
rules:
- apiGroups: [""]
  resources: ["nodes", "nodes/proxy", "nodes/metrics", "services", "endpoints", "pods"]
  verbs: ["get", "list", "watch"]
- apiGroups: ["networking.k8s.io"]
  resources: ["ingresses"]
  verbs: ["get", "list", "watch"]
- nonResourceURLs: ["/metrics", "/metrics/cadvisor"]
  verbs: ["get"]
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  name: vmagent
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: ClusterRole
  name: vmagent
subjects:
- kind: ServiceAccount
  name: vmagent
  namespace: monitoring

Sharding de vmagent

Distribuye los destinos de scrape entre instancias de vmagent en entornos a gran escala:

yaml

args:
  - "--promscrape.cluster.membersCount=3"    # Total number of vmagents
  - "--promscrape.cluster.memberNum=0"       # Current instance number (0, 1, 2)
  - "--promscrape.cluster.replicationFactor=2"  # How many instances scrape each target

vmalert

vmalert es un componente que evalúa reglas de alertas y genera alertas.

Despliegue

yaml

apiVersion: apps/v1
kind: Deployment
metadata:
  name: vmalert
  namespace: monitoring
spec:
  replicas: 2
  selector:
    matchLabels:
      app: vmalert
  template:
    metadata:
      labels:
        app: vmalert
    spec:
      containers:
      - name: vmalert
        image: victoriametrics/vmalert:v1.96.0
        args:
          - "--datasource.url=http://vmselect:8481/select/0/prometheus"
          - "--remoteRead.url=http://vmselect:8481/select/0/prometheus"
          - "--remoteWrite.url=http://vminsert:8480/insert/0/prometheus"
          - "--notifier.url=http://alertmanager:9093"
          - "--rule=/etc/vmalert/rules/*.yaml"
          - "--evaluationInterval=30s"
          - "--external.url=http://vmalert:8880"
          - "--external.label=cluster=production"
        ports:
        - containerPort: 8880
          name: http
        resources:
          requests:
            cpu: 100m
            memory: 128Mi
          limits:
            cpu: 500m
            memory: 512Mi
        volumeMounts:
        - name: rules
          mountPath: /etc/vmalert/rules
        livenessProbe:
          httpGet:
            path: /health
            port: 8880
          initialDelaySeconds: 10
          periodSeconds: 30
      volumes:
      - name: rules
        configMap:
          name: vmalert-rules
---
apiVersion: v1
kind: ConfigMap
metadata:
  name: vmalert-rules
  namespace: monitoring
data:
  kubernetes.yaml: |
    groups:
    - name: kubernetes
      interval: 30s
      rules:
      - alert: NodeMemoryHigh
        expr: |
          (node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes)
          / node_memory_MemTotal_bytes * 100 > 90
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "High memory usage on {{ $labels.instance }}"
          description: "Memory usage is {{ printf \"%.2f\" $value }}%"

      - alert: PodCrashLooping
        expr: increase(kube_pod_container_status_restarts_total[1h]) > 5
        for: 10m
        labels:
          severity: warning
        annotations:
          summary: "Pod {{ $labels.namespace }}/{{ $labels.pod }} is crash looping"
          description: "Pod has restarted {{ $value }} times in the last hour"

    - name: recording-rules
      interval: 30s
      rules:
      - record: instance:node_cpu_utilization:rate5m
        expr: |
          100 - (avg by (instance)(irate(node_cpu_seconds_total{mode="idle"}[5m])) * 100)

      - record: instance:node_memory_utilization:ratio
        expr: |
          1 - node_memory_MemAvailable_bytes / node_memory_MemTotal_bytes

MetricsQL

MetricsQL es el lenguaje de consulta de VictoriaMetrics y un superconjunto de PromQL.

Compatibilidad con PromQL

Todas las consultas de PromQL funcionan en MetricsQL:

promql

# Basic PromQL queries (also work in MetricsQL)
rate(http_requests_total[5m])
histogram_quantile(0.95, rate(http_request_duration_seconds_bucket[5m]))

Extensiones de MetricsQL

promql

# Range function defaults
# PromQL: range specification required
rate(http_requests_total[5m])

# MetricsQL: range can be omitted (uses default)
rate(http_requests_total)

# keep_last_value: retain last value (gap filling)
keep_last_value(up)

# default: set default value
http_requests_total default 0

# label_set: set labels
label_set(up, "env", "production")

# label_del: delete labels
label_del(up, "instance")

# label_copy: copy labels
label_copy(up, "instance", "node")

# label_move: move labels
label_move(up, "instance", "node")

# label_join: join labels
label_join(up, "dst", "-", "job", "instance")

# label_transform: transform labels (regex)
label_transform(up, "instance", "([^:]+):.*", "$1")

# union: combine multiple series
union(up{job="api"}, up{job="web"})

# lag: time difference from previous value
lag(up)

# lifetime: series lifetime
lifetime(up)

# scrape_interval: estimate scrape interval
scrape_interval(up)

# range_* functions: usable without range vector
range_avg(http_requests_total)        # Average over entire range
range_max(http_requests_total)        # Maximum over entire range
range_min(http_requests_total)        # Minimum over entire range
range_sum(http_requests_total)        # Sum over entire range
range_first(http_requests_total)      # First value
range_last(http_requests_total)       # Last value

# rollup_* functions: advanced aggregation
rollup(http_requests_total[5m])       # Returns min, max, avg
rollup_rate(http_requests_total[5m])  # Rate min, max, avg
rollup_delta(gauge_metric[5m])        # Delta min, max, avg

# Anomaly detection functions
anomaly_score(http_requests_total[1h])  # Anomaly score (0-1)

# histogram_share: ratio below specific value in histogram
histogram_share(0.1, http_request_duration_seconds_bucket)  # Ratio below 100ms

Consultas útiles de MetricsQL

promql

# Time series count (cardinality)
count(up)

# Time series count by label
count by (job)(up)

# Fill gaps in data
keep_last_value(up)

# Multiple conditions OR combined
up{job="api"} or up{job="web"}

# MetricsQL: simpler syntax
union(up{job="api"}, up{job="web"})

# Rate calculation (safe division)
rate(http_requests_total{status=~"5.."}[5m])
/ (rate(http_requests_total[5m]) > 0)

# MetricsQL: simple with default
rate(http_requests_total{status=~"5.."}[5m])
/ rate(http_requests_total[5m]) default 0

# Histogram bucket ratio
histogram_share(0.5, http_request_duration_seconds_bucket)  # Ratio below 500ms

Instalación con Helm

victoria-metrics-k8s-stack

bash

# Add Helm repository
helm repo add vm https://victoriametrics.github.io/helm-charts/
helm repo update

# Install
helm install victoria-metrics vm/victoria-metrics-k8s-stack \
  --namespace monitoring \
  --create-namespace \
  -f values.yaml

values.yaml (nodo único)

yaml

# VictoriaMetrics Single
victoria-metrics-single:
  enabled: true
  server:
    retentionPeriod: 1y
    resources:
      requests:
        cpu: 500m
        memory: 2Gi
      limits:
        cpu: 2000m
        memory: 8Gi
    persistentVolume:
      enabled: true
      storageClassName: gp3
      size: 100Gi
    extraArgs:
      dedup.minScrapeInterval: 30s
      search.maxUniqueTimeseries: 1000000

# vmagent
vmagent:
  enabled: true
  spec:
    replicaCount: 2
    resources:
      requests:
        cpu: 100m
        memory: 256Mi
      limits:
        cpu: 500m
        memory: 1Gi
    extraArgs:
      promscrape.maxScrapeSize: 64MB
      promscrape.cluster.membersCount: "2"

# vmalert
vmalert:
  enabled: true
  spec:
    replicaCount: 2
    resources:
      requests:
        cpu: 100m
        memory: 128Mi
      limits:
        cpu: 500m
        memory: 512Mi

# Grafana
grafana:
  enabled: true
  persistence:
    enabled: true
    storageClassName: gp3
    size: 10Gi

# Alertmanager
alertmanager:
  enabled: true
  spec:
    replicaCount: 3
    storage:
      volumeClaimTemplate:
        spec:
          storageClassName: gp3
          resources:
            requests:
              storage: 10Gi

# kube-state-metrics
kube-state-metrics:
  enabled: true

# node-exporter
prometheus-node-exporter:
  enabled: true

values.yaml (clúster)

yaml

# VictoriaMetrics Cluster
victoria-metrics-cluster:
  enabled: true

  vmselect:
    replicaCount: 3
    resources:
      requests:
        cpu: 200m
        memory: 512Mi
      limits:
        cpu: 1000m
        memory: 2Gi
    extraArgs:
      search.maxUniqueTimeseries: "1000000"

  vminsert:
    replicaCount: 3
    resources:
      requests:
        cpu: 200m
        memory: 256Mi
      limits:
        cpu: 1000m
        memory: 1Gi
    extraArgs:
      replicationFactor: "2"

  vmstorage:
    replicaCount: 3
    resources:
      requests:
        cpu: 500m
        memory: 2Gi
      limits:
        cpu: 2000m
        memory: 8Gi
    persistentVolume:
      enabled: true
      storageClassName: gp3
      size: 100Gi
    extraArgs:
      retentionPeriod: "1y"
      dedup.minScrapeInterval: "30s"

# Disable single node
victoria-metrics-single:
  enabled: false

Configuración de almacenamiento a largo plazo

Configuración del período de retención

yaml

# vmsingle
args:
  - "--retentionPeriod=1y"         # 1 year retention
  - "--retentionPeriod=365d"       # 365 days retention
  - "--retentionPeriod=8760h"      # 8760 hours retention

# Size-based retention
args:
  - "--retentionPeriod=1y"
  - "--storage.maxDiskSpace=500GB"  # Maximum disk usage

Backup en almacenamiento de objetos

yaml

# S3 backup using vmbackup
apiVersion: batch/v1
kind: CronJob
metadata:
  name: vmbackup
  namespace: monitoring
spec:
  schedule: "0 2 * * *"  # Daily at 02:00
  jobTemplate:
    spec:
      template:
        spec:
          containers:
          - name: vmbackup
            image: victoriametrics/vmbackup:v1.96.0
            args:
              - "--storageDataPath=/storage"
              - "--snapshot.createURL=http://vmsingle:8428/snapshot/create"
              - "--dst=s3://my-bucket/vmbackup"
            env:
            - name: AWS_ACCESS_KEY_ID
              valueFrom:
                secretKeyRef:
                  name: aws-credentials
                  key: access-key-id
            - name: AWS_SECRET_ACCESS_KEY
              valueFrom:
                secretKeyRef:
                  name: aws-credentials
                  key: secret-access-key
            volumeMounts:
            - name: storage
              mountPath: /storage
              readOnly: true
          volumes:
          - name: storage
            persistentVolumeClaim:
              claimName: vmsingle-storage-vmsingle-0
          restartPolicy: OnFailure

Downsampling

VictoriaMetrics Enterprise es compatible con el downsampling. Para código abierto, use reglas de registro.

Downsampling con reglas de registro

yaml

# vmalert rules
groups:
- name: downsampling
  interval: 5m
  rules:
  # 5-minute average CPU usage
  - record: cpu_usage:5m_avg
    expr: avg_over_time(node_cpu_seconds_total[5m])

  # 1-hour average (calculated every 5 minutes)
  - record: cpu_usage:1h_avg
    expr: avg_over_time(cpu_usage:5m_avg[1h])

  # Histogram downsampling
  - record: http_request_duration:5m
    expr: |
      histogram_quantile(0.50, sum(rate(http_request_duration_seconds_bucket[5m])) by (le, service))
      or
      histogram_quantile(0.90, sum(rate(http_request_duration_seconds_bucket[5m])) by (le, service))
      or
      histogram_quantile(0.99, sum(rate(http_request_duration_seconds_bucket[5m])) by (le, service))

Optimización del rendimiento

Optimización de memoria

yaml

args:
  # Memory usage limit (60% of available memory)
  - "--memory.allowedPercent=60"

  # Search cache size
  - "--search.maxMemoryPerQuery=512MB"

  # Index cache
  - "--storage.cacheSizeIndexDBDataBlocks=256MB"
  - "--storage.cacheSizeIndexDBIndexBlocks=128MB"

Optimización de consultas

yaml

args:
  # Maximum unique time series
  - "--search.maxUniqueTimeseries=1000000"

  # Maximum samples per query
  - "--search.maxSamplesPerQuery=1000000000"

  # Query timeout
  - "--search.maxQueryDuration=60s"

  # Maximum points per time series
  - "--search.maxPointsPerTimeseries=30000"

Optimización de escritura

yaml

args:
  # Deduplication (smaller than scrape interval)
  - "--dedup.minScrapeInterval=30s"

  # Maximum labels
  - "--maxLabelsPerTimeseries=30"

  # Maximum label value length
  - "--maxLabelValueLen=1024"

Prácticas recomendadas

Lista de verificación para producción

Asignación de recursos

yaml

resources:
  requests:
    cpu: 500m
    memory: 2Gi
  limits:
    cpu: 2000m
    memory: 8Gi

Alta disponibilidad
- Configure replicationFactor=2 en modo de clúster
- Mínimo 2 réplicas de vmselect y vminsert
- Mínimo 3 réplicas de vmstorage

Monitoreo

promql

# Monitor VictoriaMetrics self metrics
vm_app_version{job="vmsingle"}
vm_rows_inserted_total
vm_slow_queries_total
process_resident_memory_bytes{job=~"vm.*"}

Backup
- Backups regulares con vmbackup
- Use la funcionalidad de snapshot

Guía de migración

Migración de Prometheus a VictoriaMetrics:

yaml

# Step 1: Add remote_write to Prometheus
# prometheus.yml
remote_write:
  - url: http://victoriametrics:8428/api/v1/write

# Step 2: Add VictoriaMetrics data source to Grafana
# Operate both data sources in parallel for comparison

# Step 3: Migrate existing data (optional)
vmctl prometheus --prometheus.snapshot-path=/prometheus/snapshots/xxx \
  --vm-url=http://victoriametrics:8428

# Step 4: Complete transition
# Remove Prometheus remote_write, change Grafana default data source

Solución de problemas

Problemas comunes

1. Uso elevado de memoria

bash

# Check memory usage
curl http://vmsingle:8428/api/v1/status/tsdb

# Solution: Set memory limit
args:
  - "--memory.allowedPercent=60"

2. Consultas lentas

bash

# Check slow query log
curl http://vmsingle:8428/api/v1/status/top_queries

# Solution: Query optimization
# - Reduce time range
# - Add label filters
# - Increase step

3. Espacio en disco lleno

bash

# Check disk usage
curl http://vmsingle:8428/api/v1/status/tsdb | jq .

# Solutions
# - Reduce retention period
# - Delete unnecessary metrics
curl -X POST "http://vmsingle:8428/api/v1/admin/tsdb/delete_series?match[]=go_.*"

Comandos de depuración

bash

# Check status
curl http://vmsingle:8428/api/v1/status/tsdb
curl http://vmsingle:8428/api/v1/status/active_queries
curl http://vmsingle:8428/api/v1/status/top_queries

# Check metrics
curl http://vmsingle:8428/metrics

# Create snapshot
curl http://vmsingle:8428/snapshot/create

# Force merge (reclaim disk space)
curl http://vmsingle:8428/internal/force_merge

Referencias

Cuestionario

Para comprobar su comprensión de este capítulo, pruebe el cuestionario de VictoriaMetrics.

Laboratorios integrales de observabilidad

Cuestionario de ArgoCD en detalle

Cuestionario de Istio detallado

Cuestionario de Linkerd detallado

Cuestionario de Cilium Service Mesh detallado

Profundización en Cilium

Profundización en Calico

Métricas

Registro

Trazado

Alertas

Laboratorios de observabilidad

ArgoCD

Gestión del tráfico

Seguridad

Observabilidad

Resiliencia

Avanzado

Guía comparativa

Métricas

Registro

Trazado

Alertas

VictoriaMetrics ​

Tabla de contenidos ​

Introducción ​

Características principales ​

VictoriaMetrics frente a Prometheus ​

Opciones de arquitectura ​

Guía de selección ​

Modo de nodo único ​

Características ​

Despliegue de StatefulSet ​

Endpoints principales ​

Modo de clúster ​

Arquitectura ​

Componentes ​

Despliegue de vmstorage ​

Despliegue de vminsert ​

Despliegue de vmselect ​

vmagent ​

Características principales ​

Despliegue ​

Sharding de vmagent ​

vmalert ​

Despliegue ​

MetricsQL ​

Compatibilidad con PromQL ​

Extensiones de MetricsQL ​

Consultas útiles de MetricsQL ​

Instalación con Helm ​

victoria-metrics-k8s-stack ​

values.yaml (nodo único) ​

values.yaml (clúster) ​

Configuración de almacenamiento a largo plazo ​

Configuración del período de retención ​

Backup en almacenamiento de objetos ​

Downsampling ​

Downsampling con reglas de registro ​

Optimización del rendimiento ​

Optimización de memoria ​

Optimización de consultas ​

Optimización de escritura ​

Prácticas recomendadas ​

Lista de verificación para producción ​

Guía de migración ​

Solución de problemas ​

Problemas comunes ​

1. Uso elevado de memoria ​

2. Consultas lentas ​

3. Espacio en disco lleno ​

Comandos de depuración ​

Referencias ​

Cuestionario ​

VictoriaMetrics

Tabla de contenidos

Introducción

Características principales

VictoriaMetrics frente a Prometheus

Opciones de arquitectura

Guía de selección

Modo de nodo único

Características

Despliegue de StatefulSet

Endpoints principales

Modo de clúster

Arquitectura

Componentes

Despliegue de vmstorage

Despliegue de vminsert

Despliegue de vmselect

vmagent

Características principales

Despliegue

Sharding de vmagent

vmalert

Despliegue

MetricsQL

Compatibilidad con PromQL

Extensiones de MetricsQL

Consultas útiles de MetricsQL

Instalación con Helm

victoria-metrics-k8s-stack

values.yaml (nodo único)

values.yaml (clúster)

Configuración de almacenamiento a largo plazo

Configuración del período de retención

Backup en almacenamiento de objetos

Downsampling

Downsampling con reglas de registro

Optimización del rendimiento

Optimización de memoria

Optimización de consultas

Optimización de escritura

Prácticas recomendadas

Lista de verificación para producción

Guía de migración

Solución de problemas

Problemas comunes

1. Uso elevado de memoria

2. Consultas lentas

3. Espacio en disco lleno

Comandos de depuración

Referencias

Cuestionario