vmetrics-js

vmetrics-js

A high-performance TypeScript/JavaScript client for VictoriaMetrics, optimized for IoT and high-throughput time-series data ingestion.

⚠️ EARLY STAGE PROJECT - NOT PRODUCTION READY

This project is in very early development and should NOT be used in production environments yet. Currently, only a rudimentary push API is implemented. Many features are missing, and the API may change significantly. Use at your own risk!

Project Focus: We are concentrating on the push API (actively sending metrics to VictoriaMetrics). For exposing a /metrics endpoint that VictoriaMetrics can scrape (pull API), use prom-client instead.

Contributions and feedback are welcome to help make this library production-ready.

Features

• Automatic Batching: Efficiently groups data points into batches to minimize network overhead
• Smart Buffering: Configurable buffer with automatic flushing based on size or time intervals
• Type-Safe: Full TypeScript support with comprehensive type definitions
• InfluxDB Line Protocol: Uses the standard InfluxDB line protocol format
• Thread-Safe: Built-in mutex protection for concurrent write operations
• Zero Dependencies: Only one lightweight dependency (async-mutex)
• Error Resilient: Automatic retry mechanism with buffer re-queueing on failures
• Easy Integration: Simple, intuitive API for quick adoption

Installation

npm install vmetrics-js

yarn add vmetrics-js

pnpm add vmetrics-js

Quick Start

import { VictoriaMetricsClient } from 'vmetrics-js'

// Create a client instance
const client = new VictoriaMetricsClient({
    url: 'http://0.0.0.0:8428',
    batchSize: 1000, // Flush after 1000 points
    flushInterval: 5000, // Flush every 5 seconds
})

// Write data points
client.writePoint({
    measurement: 'temperature',
    tags: {
        sensor_id: 'sensor-001',
        location: 'warehouse-a',
    },
    fields: {
        value: 23.5,
        humidity: 65.2,
    },
    timestamp: new Date(), // Optional, uses server time if omitted
})

// Graceful shutdown (flushes remaining buffer)
await client.shutdown()

Multiple Field Types

client.writePoint({
    measurement: 'system_stats',
    tags: {
        host: 'server-01',
        region: 'us-east-1',
    },
    fields: {
        cpu_usage: 45.2, // number
        memory_used: 8589934592, // number (bytes)
        disk_full: false, // boolean
        status: 'healthy', // string
    },
})

Configuration Guide

Choosing batchSize

• High-frequency data (IoT, sensors): Use larger batches (1000-5000) to reduce network overhead
• Low-frequency data (application metrics): Use smaller batches (100-500) for more frequent updates
• Rule of thumb: Set to expected points per flushInterval

Choosing flushInterval

• Real-time monitoring: 1000-5000ms (1-5 seconds)
• Background analytics: 10000-60000ms (10-60 seconds)
• Trade-off: Shorter intervals = fresher data but more network requests

Architecture

How It Works

┌─────────────┐
│ Application │
└──────┬──────┘
       │ writePoint()
       ▼
┌─────────────────┐
│  Write Buffer   │◄─── Mutex Protected
└──────┬──────────┘
       │
       ├─► Batch Size Reached? ──► Flush ───┐
       └─► Time Interval? ───────► Flush ───┐
                                            │
                                            ▼
                                     ┌─────────────────┐
                                     │ VictoriaMetrics │
                                     └─────────────────┘

• Write: writePoint() adds data to an in-memory buffer (instant return)
• Trigger: Flush happens when buffer reaches batchSize OR flushInterval expires
• Send: All buffered points are sent in a single HTTP POST request
• Retry: On failure, data is re-queued to the buffer

VictoriaMetrics Setup

For local development, you can run VictoriaMetrics with Podman/Docker:

docker run -d --name victoriametrics \
  -p 8428:8428 \
  victoriametrics/victoria-metrics:latest

Access the UI at: http://0.0.0.0:8428

Troubleshooting

Data Not Appearing in VictoriaMetrics

• Verify VictoriaMetrics is running: curl http://0.0.0.0:8428/health
• Check for errors: Look for [VMClient] error logs in your console
• Force a flush: Call await client.flush() to send data immediately

Performance Issues

• Increase batch size: Larger batches = fewer HTTP requests
• Increase flush interval: Less frequent network I/O
• Use tags wisely: Too many unique tag combinations = high cardinality = slow queries

Authentication Errors

Ensure you're using the correct authentication method:

const client = new VictoriaMetricsClient({
    url: 'http://0.0.0.0:8428',
    auth: { bearer: 'your-token-here' },
})

Testing

Run the test suite:

npm test

Run the example:

npm run example

Contributing

Contributions are welcome! Please see CONTRIBUTING.md for guidelines.

Development Setup

# Clone the repository
git clone [e-mail]:zimmerling/vmetrics-js.git

cd vmetrics-js

# Install dependencies
npm install

# Run tests
npm test

# Build
npm run build

# Lint
npm run lint

# Format code
npm run format

Current Limitations

This library is in early development and currently provides only basic functionality:

What's implemented:

• ✅ Basic push API using InfluxDB Line Protocol (client pushes metrics to VictoriaMetrics)
• ✅ Buffering and batching
• ✅ Basic error handling and retry (re-queue on failure)
• ✅ Bearer token authentication

What's missing:

• ❌ Pull API (/metrics endpoint) - Use prom-client for this
• ❌ Compression support
• ❌ Circuit breaker / exponential backoff
• ❌ Connection pooling
• ❌ Prometheus remote write protocol
• ❌ Comprehensive error handling
• ❌ Browser support
• ❌ Production-grade reliability features
• ❌ Performance metrics and observability

Scope & Focus

This library focuses exclusively on the push API - actively sending metrics from your application to VictoriaMetrics.

For pull-based metrics (exposing a /metrics endpoint that VictoriaMetrics scrapes), use:

• prom-client - The standard library for exposing Prometheus-compatible metrics endpoints

Roadmap

Push API improvements:

• Compression support (gzip)
• Circuit breaker for failed endpoints
• Retry with exponential backoff
• Connection pooling and keep-alive
• Prometheus remote write protocol support
• Metrics about client performance (points buffered, flush duration, etc.)
• Browser support (via fetch API)
• Comprehensive test coverage
• Production hardening

Not planned (use other tools):

• Pull API / /metrics endpoint → Use prom-client
• Query API for reading data → Use VictoriaMetrics HTTP API directly

Links

• VictoriaMetrics Documentation
• InfluxDB Line Protocol
• Report Issues
• NPM Package

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