v3.2 — Now with real-time streaming

Infrastructure metrics
at any scale

Collect, process, and visualize volumetric data across your entire stack. Sub-second latency, enterprise reliability.

2.4T
Data points / day
<12ms
P99 Latency
99.97%
Uptime SLA
180+
Integrations
Platform
Built for engineering teams
Everything you need to monitor, alert, and optimize — without the complexity of legacy tools.

Real-time ingestion

Stream millions of data points per second with our distributed collection pipeline. Automatic sharding, zero configuration.

Smart alerting

ML-powered anomaly detection with configurable thresholds. Route alerts to Slack, PagerDuty, or custom webhooks.

Query engine

VolQL — our purpose-built query language optimized for time-series aggregation. 100x faster than SQL on metric workloads.

Dashboards

Drag-and-drop dashboard builder with 40+ visualization types. Share with your team or embed in your own products.

Infrastructure agents

Lightweight agents for Linux, Kubernetes, Docker, and cloud platforms. One-line install, automatic discovery.

Enterprise controls

SSO, RBAC, audit logs, data retention policies, and VPC peering. SOC 2 Type II and GDPR compliant.

Ship metrics in minutes

Our REST API and client SDKs make it trivial to instrument any application. Available in Python, Go, Node.js, Rust, and Java.

✓  Batch or streaming ingestion
✓  Automatic retry with backoff
✓  End-to-end encryption (TLS 1.3)
✓  OpenTelemetry compatible

ingest.py
from fastaccess import Client

# Initialize with your API key
client = Client("vm_live_k8x2...")

# Send metrics from your application
client.gauge(
  name="api.request_duration",
  value=0.042,
  tags={
    "service": "checkout",
    "region": "eu-west-1"
  }
)

# Query with VolQL
result = client.query(
  "avg(api.request_duration)",
  interval="5m",
  last="1h"
)