Documentation Index
Fetch the complete documentation index at: https://docs.feral.sh/llms.txt
Use this file to discover all available pages before exploring further.
Overview
FERAL exposes operational metrics across all major subsystems. Metrics work in
two modes:
- In-memory counters (always available, zero dependencies)
- OpenTelemetry SDK (when
opentelemetry-sdk is installed) — exports to
any OTLP-compatible backend
Enable Prometheus Scraping
# Expose the /metrics endpoint
export FERAL_METRICS_ENDPOINT=1
# Start FERAL
feral serve
scrape_configs:
scrape_configs:
- job_name: feral
static_configs:
- targets: ["localhost:9090"]
metrics_path: /metrics
Export to OTLP (Grafana Cloud, Honeycomb, etc.)
Install the OpenTelemetry extras:
pip install feral-ai[observability]
export OTEL_EXPORTER_OTLP_ENDPOINT=https://otlp.example.com:4318
# Optional: also log metrics to console
export FERAL_METRICS_CONSOLE=1
Metrics Reference
LLM
| Metric | Type | Labels | Description |
|---|
feral.llm.calls_total | Counter | provider, model | Total LLM API calls |
feral.llm.errors_total | Counter | provider, model | Failed LLM API calls |
feral.llm.latency_ms | Histogram | provider, model | LLM call latency in ms |
Channels
| Metric | Type | Labels | Description |
|---|
feral.channel.message_total | Counter | channel, direction | Messages sent/received per channel |
Proactive Engine
| Metric | Type | Labels | Description |
|---|
feral.proactive.trigger_total | Counter | trigger | Proactive triggers fired |
Skills
| Metric | Type | Labels | Description |
|---|
feral.skill.invocations_total | Counter | skill, endpoint | Skill endpoint invocations |
feral.skill.exec_latency_ms | Histogram | skill, endpoint | Skill execution latency in ms |
Programmatic Access
from observability.metrics import increment, observe, measure, in_memory_snapshot
# Counter
increment("my_custom.counter", attributes={"env": "prod"})
# Histogram
observe("my_custom.latency_ms", 42.5)
# Context manager (auto-records duration)
with measure("my_custom.operation"):
do_work()
# Debug snapshot
print(in_memory_snapshot())
