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Fireflies Observability

ASecurity

Set up comprehensive observability for Fireflies.ai integrations with metrics, traces, and alerts. Use when implementing monitoring for Fireflies.ai operations, setting up dashboards, or configuring alerting for Fireflies.ai integration health. Trigger with phrases like "fireflies monitoring", "fireflies metrics", "fireflies observability", "monitor fireflies", "fireflies alerts", "fireflies tracing".

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  • Added September 1, 2026
developmenttypescriptapibackenddocumentation

Works with

  • cli
  • api

Security analysis

A100/100

Scanned September 1, 2026

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SKILL.md
---
name: fireflies-observability
description: |
  Set up comprehensive observability for Fireflies.ai integrations with metrics, traces, and alerts.
  Use when implementing monitoring for Fireflies.ai operations, setting up dashboards,
  or configuring alerting for Fireflies.ai integration health.
  Trigger with phrases like "fireflies monitoring", "fireflies metrics",
  "fireflies observability", "monitor fireflies", "fireflies alerts", "fireflies tracing".
allowed-tools: Read, Write, Edit
version: 1.0.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
---

# Fireflies.ai Observability

## Overview
Set up comprehensive observability for Fireflies.ai integrations.

## Prerequisites
- Prometheus or compatible metrics backend
- OpenTelemetry SDK installed
- Grafana or similar dashboarding tool
- AlertManager configured

## Metrics Collection

### Key Metrics
| Metric | Type | Description |
|--------|------|-------------|
| `fireflies_requests_total` | Counter | Total API requests |
| `fireflies_request_duration_seconds` | Histogram | Request latency |
| `fireflies_errors_total` | Counter | Error count by type |
| `fireflies_rate_limit_remaining` | Gauge | Rate limit headroom |

### Prometheus Metrics

```typescript
import { Registry, Counter, Histogram, Gauge } from 'prom-client';

const registry = new Registry();

const requestCounter = new Counter({
  name: 'fireflies_requests_total',
  help: 'Total Fireflies.ai API requests',
  labelNames: ['method', 'status'],
  registers: [registry],
});

const requestDuration = new Histogram({
  name: 'fireflies_request_duration_seconds',
  help: 'Fireflies.ai request duration',
  labelNames: ['method'],
  buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5],
  registers: [registry],
});

const errorCounter = new Counter({
  name: 'fireflies_errors_total',
  help: 'Fireflies.ai errors by type',
  labelNames: ['error_type'],
  registers: [registry],
});
```

### Instrumented Client

```typescript
async function instrumentedRequest<T>(
  method: string,
  operation: () => Promise<T>
): Promise<T> {
  const timer = requestDuration.startTimer({ method });

  try {
    const result = await operation();
    requestCounter.inc({ method, status: 'success' });
    return result;
  } catch (error: any) {
    requestCounter.inc({ method, status: 'error' });
    errorCounter.inc({ error_type: error.code || 'unknown' });
    throw error;
  } finally {
    timer();
  }
}
```

## Distributed Tracing

### OpenTelemetry Setup

```typescript
import { trace, SpanStatusCode } from '@opentelemetry/api';

const tracer = trace.getTracer('fireflies-client');

async function tracedFireflies.aiCall<T>(
  operationName: string,
  operation: () => Promise<T>
): Promise<T> {
  return tracer.startActiveSpan(`fireflies.${operationName}`, async (span) => {
    try {
      const result = await operation();
      span.setStatus({ code: SpanStatusCode.OK });
      return result;
    } catch (error: any) {
      span.setStatus({ code: SpanStatusCode.ERROR, message: error.message });
      span.recordException(error);
      throw error;
    } finally {
      span.end();
    }
  });
}
```

## Logging Strategy

### Structured Logging

```typescript
import pino from 'pino';

const logger = pino({
  name: 'fireflies',
  level: process.env.LOG_LEVEL || 'info',
});

function logFireflies.aiOperation(
  operation: string,
  data: Record<string, any>,
  duration: number
) {
  logger.info({
    service: 'fireflies',
    operation,
    duration_ms: duration,
    ...data,
  });
}
```

## Alert Configuration

### Prometheus AlertManager Rules

```yaml
# fireflies_alerts.yaml
groups:
  - name: fireflies_alerts
    rules:
      - alert: Fireflies.aiHighErrorRate
        expr: |
          rate(fireflies_errors_total[5m]) /
          rate(fireflies_requests_total[5m]) > 0.05
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "Fireflies.ai error rate > 5%"

      - alert: Fireflies.aiHighLatency
        expr: |
          histogram_quantile(0.95,
            rate(fireflies_request_duration_seconds_bucket[5m])
          ) > 2
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "Fireflies.ai P95 latency > 2s"

      - alert: Fireflies.aiDown
        expr: up{job="fireflies"} == 0
        for: 1m
        labels:
          severity: critical
        annotations:
          summary: "Fireflies.ai integration is down"
```

## Dashboard

### Grafana Panel Queries

```json
{
  "panels": [
    {
      "title": "Fireflies.ai Request Rate",
      "targets": [{
        "expr": "rate(fireflies_requests_total[5m])"
      }]
    },
    {
      "title": "Fireflies.ai Latency P50/P95/P99",
      "targets": [{
        "expr": "histogram_quantile(0.5, rate(fireflies_request_duration_seconds_bucket[5m]))"
      }]
    }
  ]
}
```

## Instructions

### Step 1: Set Up Metrics Collection
Implement Prometheus counters, histograms, and gauges for key operations.

### Step 2: Add Distributed Tracing
Integrate OpenTelemetry for end-to-end request tracing.

### Step 3: Configure Structured Logging
Set up JSON logging with consistent field names.

### Step 4: Create Alert Rules
Define Prometheus alerting rules for error rates and latency.

## Output
- Metrics collection enabled
- Distributed tracing configured
- Structured logging implemented
- Alert rules deployed

## Error Handling
| Issue | Cause | Solution |
|-------|-------|----------|
| Missing metrics | No instrumentation | Wrap client calls |
| Trace gaps | Missing propagation | Check context headers |
| Alert storms | Wrong thresholds | Tune alert rules |
| High cardinality | Too many labels | Reduce label values |

## Examples

### Quick Metrics Endpoint
```typescript
app.get('/metrics', async (req, res) => {
  res.set('Content-Type', registry.contentType);
  res.send(await registry.metrics());
});
```

## Resources
- [Prometheus Best Practices](https://prometheus.io/docs/practices/naming/)
- [OpenTelemetry Documentation](https://opentelemetry.io/docs/)
- [Fireflies.ai Observability Guide](https://docs.fireflies.com/observability)

## Next Steps
For incident response, see `fireflies-incident-runbook`.

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