Unified Observability

VictoriaMetrics: The High-Performance Alternative

A cost-efficient, rock-solid observability stack for metrics, logs, and traces. Designed to handle massive cardinality with significantly lower resource overhead than Prometheus or Loki.

The Three Pillars of Victoria

One ecosystem, zero complexity. Replace fragmented tools with a cohesive, high-density storage engine.

VictoriaMetrics

The TSDB powerhouse. Drop-in Prometheus replacement with superior horizontal scalability.

VictoriaLogs

Scalable logs with LogsQL. High-speed full-text search designed for low-cost retention.

VictoriaTraces

Distributed tracing simplified. High-throughput ingestion with minimal overhead.

// vmagent: Edge Relabeling

metric_relabel_configs:
  # Drop high-cardinality temporary labels
  - action: labeldrop
    regex: (pod_template_hash|controller_revision_hash)
  
  # Drop specific expensive metrics
  - source_labels: [__name__]
    regex: 'container_tasks_state|go_gc_.*'
    action: drop

vmagent: Smart Edge Relabeling

Filter out noisy labels and "trash" metrics at the source before they consume your storage budget.

Cost Protection: Drop high-cardinality metrics instantly.
Disk Buffering: Safe data replay after network outages.

vmauth: Secure Multi-Tenancy

A lightweight security proxy for Basic Auth, Bearer tokens, or mTLS while ensuring strict tenant isolation.

Tenant Isolation

Route requests to specific account IDs based on user credentials.

Unified Entry Point

One URL for Grafana; intelligent routing for all telemetry types.

// vmauth: User Routing

users:
  - username: "grafana"
    password: "safe-password"
    url_prefix: "http://vmselect:8481/select/0/prometheus"

Cluster Topology


          graph TD
            Sources[Data Sources: vmagent/Prom] --> LB1[Load Balancer]
            LB1 --> vminsert[vminsert layer]
            vminsert --> S1[vmstorage Node A]
            vminsert --> S2[vmstorage Node B]
            S1 -. Replication .- S2
            
            Grafana[Grafana/API] --> LB2[Load Balancer]
            LB2 --> vmselect[vmselect layer]
            vmselect --> S1
            vmselect --> S2
            
            style S1 fill:#10b981,stroke:#065f46,color:#fff
            style S2 fill:#10b981,stroke:#065f46,color:#fff
            style vminsert fill:#3b82f6,stroke:#1e3a8a,color:#fff
            style vmselect fill:#3b82f6,stroke:#1e3a8a,color:#fff

Data flows through independent ingestion (insert) and query (select) layers to a replicated storage backend.

High-Availability Architecture

Designed for 99.99% availability by separating ingestion from storage nodes.

Replication

Mirror data across multiple storage nodes for instant failover.

Independent Scaling

Scale ingestion and query capacity separately to match usage patterns.

Storage Economics

Victoria Stack vs. Standard TSDB (per 1 billion points).

Efficiency Metric	Standard (Prom/Loki)	Victoria Stack
Metrics Density	~1.5 - 2.0 bytes / sample	~0.4 - 0.6 bytes / sample
Disk Req. (1B points)	~1.8 GB	~0.5 GB
RAM Usage	High (Index-heavy)	Low (Index-less architecture)
CPU Overhead	Variable spikes	Stable (Optimized Go)

vmanomaly: AI-Powered Insights

Identify performance regressions before they trigger manual alerts using built-in machine learning models.

// Detection Config

schedulers:
  - name: "billing_errors"
    query: "sum(rate(errors_total[5m]))"
    model: "zscore"
    alias: "error_anomaly"

Auto-tuning Z-Score and Prophet models
Reduces alert fatigue by suppressing normal noise

Anomaly Detection Engine

Expected Range

Anomaly Detected

Unified Grafana Experience

Stop switching data sources. Visualize metrics, logs, and traces through a single backend.

Native Logs: Query VictoriaLogs directly within Grafana panels.
Correlation: Jump from a metric spike to traces with one click.

Single Pane of Glass

// LogsQL Query

_msg: "error" 
AND service: "billing" 
AND duration: >500ms 
| stats count(*) by status_code

VictoriaLogs: LogsQL

A human-readable language for high-speed search without the indexing overhead of Elasticsearch.

High Compression: Store logs with 10x better density than traditional engines.

Distributed Tracing

gateway-api : /checkout

auth-service : validate

payment-svc : timeout

High-throughput OTLP Ingestion

VictoriaTraces: Trace Simplified

A high-throughput backend for OTLP and Jaeger that correlates tracing data for root cause analysis.

Native OTLP and Jaeger ingestion
Simplified architecture with minimal components

The OTel Gateway

Standardize your data collection. Use the OpenTelemetry Collector to receive, process, and export all telemetry to VictoriaMetrics without vendor lock-in.

Unified Pipeline: Process metrics, logs, and traces through a single agent.
Attribute Filtering: Drop sensitive data or add cloud metadata at the edge.

// otel-collector-config.yaml

exporters:
  prometheusremotewrite:
    endpoint: "http://vminsert:8480/insert/0/prometheus/api/v1/write"
  otlp/logs:
    endpoint: "http://vmlogs:9428/insert/jsonline"
  otlp/traces:
    endpoint: "http://vmtraces:4317"

Sources

OTel Collector

Metrics

Logs

Traces

The collector acts as a "traffic controller," ensuring clean data arrives at your cluster.

Scale Without the Headache

Moving from Prometheus or Loki? We specialize in seamless migrations that slash your cloud bill by up to 50%.

Get a Performance Audit