AI Observability Templates & Checklists — 47 Templates & Checklists for Traces, Logs, Metrics, Dashboards, Alerting, Drift & AI Incident Response

## Your dashboards are green. Your product is rotting.

AI systems fail silently. No exception, no alert, no 500 — just a perfectly formatted wrong answer, a quality curve eroding a point a month, a token bill seeping upward, a retriever quietly citing last quarter's policy. Classical monitoring watches the machinery; AI failures happen in the meaning. **AI Observability Templates & Checklists** is the second observability layer, built for behavior: 47 working templates and checklists that record what the model saw and said, trace every request through its reasoning, score quality on live traffic, meter every token and millisecond, and page a human only when it actually matters.

Every template is copy-paste ready with the book's tested positions built in: a telemetry schema of seven field groups, a quality guardrail windowed at 500 outputs, budget governors that warn at 80% of spend, severity-weighted error budgets (critical 10 · major 3 · minor 1), an incident evidence rule of 50 failing examples plus 50 passing controls, and a capstone that carries the book's own 22-item production observability checklist with its quick-reference card of healthy ranges. Where the book gives an example — its SLO set, its rules of thumb — the template labels it as the book's example for you to tune. Bracketed fields are yours to fill; nothing here invents a threshold for your system.

### What's inside — 47 templates & checklists in 10 sections

**1. Silent Failures & the Observability Gap (5)** — Silent-Failure Classification & Detection Map · Observability Gap Audit · Four Pillars Coverage Checklist · Business Cost of Undetected Failure Worksheet · Quality Guardrail Baseline Sheet

**2. Structured Telemetry & Logging (5)** — Telemetry Event Schema Contract · Log / Never-Log Boundary & Redaction Checklist · Log Levels for AI Workloads · Sampling Strategy Design Sheet · Logging Wrapper Acceptance Checklist

**3. Tracing Agent Workflows (5)** — Trace & Span Modeling Checklist · Trace Context Propagation Checklist · OpenTelemetry Adoption Checklist · Tracing Platform Selection Scorecard · Tail Sampling & Trace-Reading Routine

**4. Prompt & Response Monitoring (5)** — Prompt Registry & Versioning Checklist · Prompt Performance Monitoring Sheet · Response Stream Monitoring Dashboard Specification · Prompt-Injection Detection & Response Ladder · Prompt A/B Test & Canary Rollout Plan

**5. Production Evaluation Monitoring (4)** — Production Eval Harness Operations Checklist · Judge Monitoring & Calibration Checklist · Human Review Queue Operations Sheet · Eval Score Time-Series & Alerting Sheet

**6. Cost & Token Tracking (5)** — Per-Request Cost Attribution Checklist · Cost Ledger Build & Reconciliation Sheet · Budget Governor & Circuit Breaker Configuration · Cost Anomaly Detection Checklist · Showback / Chargeback & Cost-Lever Worksheet

**7. Latency Profiling (4)** — Latency Stage Breakdown & Budget Sheet · Streaming & TTFT Instrumentation Checklist · Tool-Call & Agent Critical-Path Profiling Sheet · Latency Optimization Experiment Log

**8. Hallucination & Quality Drift Detection (5)** — Measurable Quality Definitions Worksheet · Reference-Free Faithfulness Check Sheet · User Feedback Signal Monitoring Sheet · Embedding & Corpus Drift Detection Sheet · Drift Response Playbook

**9. Alerting, SLOs & Incident Response (4)** — SLO Definition Worksheet · Error Budget Policy Sheet · Burn-Rate Alert Configuration Sheet · AI Incident Runbook & Contributing-Factors Postmortem Template

**10. Debugging Playbooks & the Production Stack (5)** — RAG Failure Triage & Debug Harness Checklist · Multi-Agent Failure Signature Detector Sheet · Reference Architecture & Build-vs-Buy Worksheet · 30-Day Rollout Plan & Minimum Viable Observability Sheet · Production Observability Readiness Capstone — the book's own Appendix A checklist (22 items in 5 groups) with the Appendix B quick-reference card, verified with evidence or the system is not declared production-ready

### Who this is for

AI engineers, platform engineers, and technical leads operating LLM applications, RAG pipelines, or agent systems in production — teams that have shipped at least one AI system and discovered that uptime is not the same as working. If your error rate is zero and your users are still unhappy, start at Template 1.

### What this pack is not

- **No vendor setup guides.** OpenTelemetry is covered as concepts, and tracing platforms are compared at capability level — the depth the source book itself works at. There are no install steps, configuration files, or queries for any named platform.

- **No importable dashboards or alert-rule files.** Dashboards are specified panel by panel and alert logic is defined precisely; nothing here is a platform file to import.

- **No code library.** The book's Python is illustrative — the pack ships the templates and checklists that specify, audit, and operate these components, not a runnable SDK or harness.

- **No judge prompts, rubrics, or dataset-building templates.** Section 5 runs and calibrates the judging operation in production; evaluation design lives in the companion Agent Evaluation Toolkit.

- **No guaranteed savings or universal thresholds.** The cost and latency levers carry the book's expected-impact ranges, labeled as the book's planning figures. The example SLOs and quick-reference ranges are the book's examples — starting points to tune to your workload, not promises.

- **No security templates and no compliance claims.** Injection appears as detection in traffic; security artifacts live in the companion AI Security pack. The maturity model in Template 47 is a self-assessment map, not a certification.

### Companion products

The **Agent Evaluation Toolkit** holds the evaluation design this pack's production loop consumes — datasets, judges, and gates. The **AI Security Templates & Checklists** pack holds the security artifacts and the security incident plan. The **RAG** and **MCP Architecture Templates** packs hold the build checklists for the systems this pack debugs. This pack is how all of them stay honest after launch.

*Note: the $99 Architecture Templates Bundle currently contains Products #1–#3 only. This pack launches standalone; no bundle inclusion is promised for this product.*

Built by the author of **AI Observability: Monitoring, Tracing, and Debugging AI Systems**, from the monitoring discipline behind production AI systems.

### About the author

Naveen Kumar Josyula is the author of 35 AI books on Amazon KDP and the CEO and founder of AISoltrics Technologies Inc. He is the author of the source book, *AI Observability: Monitoring, Tracing, and Debugging AI Systems*, from which every template in this pack is distilled.

### Support promise

If anything in this file is wrong or unclear, email support@aisoltrics.com before you judge it — we fix verified issues within one business day and send you the corrected file free. (You can also reach the founder's office at aadhya@aisoltrics.com.) Updates to this product are free to past buyers via your Payhip library. Sold by AISoltrics Technologies Inc.