afrexai-observability-engine

# Observability & Reliability Engineering

Complete system for building observable, reliable services — from structured logging to incident response to SLO-driven development.

---

## Quick Health Check (/16)

Score your current observability posture:

| Signal | Healthy (2) | Weak (1) | Missing (0) |
|--------|-------------|----------|-------------|
| Structured logging | JSON logs with trace_id correlation | Logs exist but unstructured | Console.log / print statements |
| Metrics collection | RED/USE metrics with dashboards | Some metrics, no dashboards | No metrics |
| Distributed tracing | Full request path with sampling | Partial traces, key services only | No tracing |
| Alerting | SLO-based alerts with runbooks | Threshold alerts, some runbooks | No alerts or all-noise |
| Incident response | Defined process with roles + post-mortems | Ad-hoc response, some docs | "Whoever notices fixes it" |
| SLOs defined | SLOs with error budgets tracked weekly | Informal availability targets | No reliability targets |
| On-call rotation | Structured rotation with escalation | Informal "call someone" | No on-call |
| Cost management | Observability budget tracked monthly | Some awareness of costs | No idea what you spend |

**12-16:** Production-grade. Focus on optimization.
**8-11:** Foundation exists. Fill the gaps systematically.
**4-7:** Significant risk. Prioritize alerting + incident response.
**0-3:** Flying blind. Start with Phase 1 immediately.

---

## Phase 1: Structured Logging

### Log Architecture

```
Application → Structured JSON → Log Router → Storage → Query Engine
                                    ↓
                              Alert Pipeline
```

### Required Fields (Every Log Line)

| Field | Type | Purpose | Example |
|-------|------|---------|---------|
| `timestamp` | ISO-8601 UTC | When | `2026-02-22T18:30:00.123Z` |
| `level` | enum | Severity | `info`, `warn`, `error`, `fatal` |
| `service` | string | Which service | `payment-api` |
| `versio...

# AfrexAI Observability Engine 🔭

Complete observability & reliability engineering system for AI agents. Covers structured logging, metrics, distributed tracing, SLOs, alerting, incident response, post-mortems, on-call, chaos engineering, and cost optimization.

## Install

```bash
clawhub install afrexai-observability-engine
```

## What's Inside

A 12-phase system covering the full observability lifecycle:

1. **Structured Logging** — JSON schema, PII scrubbing, log level decision tree, setup by language (Node/Python/Go)
2. **Metrics Collection** — RED + USE methods, naming conventions, label design, instrumentation checklist
3. **Distributed Tracing** — OpenTelemetry setup, sampling strategies, context propagation
4. **SLOs & Error Budgets** — SLI selection, target setting, burn-rate alerts, weekly tracking
5. **Alert Design** — Severity levels, anti-patterns, Prometheus templates, runbook templates
6. **Dashboard Architecture** — 4-level hierarchy (executive → infrastructure), panel specs
7. **Incident Response** — Severity classification, roles, step-by-step workflow, channel templates
8. **Post-Mortem Framework** — Blameless template, 5 Whys, meeting agenda
9. **On-Call Operations** — Rotation design, health metrics, weekly review
10. **Chaos Engineering** — Experiment templates, maturity levels, abort conditions
11. **Cost Optimization** — Cost driver ranking, reduction checklist, monthly review
12. **Advanced Patterns** — Correlation, synthetic monitoring, feature flag observability, maturity model

Plus: /16 health check, 100-point quality rubric, 10 commandments, 12 natural language commands.

## Quick Start

Tell your agent:
> "Audit our observability posture"

Or:
> "Design SLOs for our payment API"

## ⚡ Level Up

For industry-specific observability patterns, check out [AfrexAI Context Packs ($47)](https://afrexai-cto.github.io/context-packs/) — SaaS, Fintech, Healthcare, and 7 more verticals.

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