Map a request
Represent important operations with correlated spans and bounded attributes.
Practical AI · EDITION 1.0.0
Trace and Triage AI Application Failures
Turn synthetic spans into a reproducible triage report, separate transport success from answer quality, and design telemetry that supports incident decisions without copying every prompt.
By Sanjaay Gowda T S · For developers and operators maintaining ai-powered applications.
You need: Read basic JSON and Python; Understand a request and response; Run Python unittest
Runtime and hardware details
Python 3.10 or later and a terminal. The supplied project runs locally and uses the Python standard library.
No model, API key, cloud account or network calls are used by the companion.
Read basic JSON and Python; Understand a request and response; Run Python unittest.
Full setup and scope ↓$2.99USD · one-time purchase
Prepared with AI assistance. Independent human technical, editorial and assistive-technology reader review remains pending. Automated checks and agent review are not certification.
PDF + EPUB + companion project. Any applicable tax is shown at checkout. Single-reader ebook terms; companion code is MIT licensed.
TRY THE FREE SAMPLE
See how the guide teaches.
Read 6 sample pages to explore the introduction, first chapter and teaching approach before you choose the complete edition.
Read free sample PDF · No checkout required
WHAT YOU WILL LEARN
Understand each part.
Inspect every boundary.
Triage precisely
Separate transport errors, quality failures and latency symptoms.
Build useful evidence
Design incident packets, sampling rules and outcome denominators.
INSIDE THE BOOK
9 focused chapters.
- Start with the failure question
- Map requests into spans
- Keep transport and quality separate
- Choose attributes with restraint
- Measure latency without double counting
- Sample with an explicit denominator
- Triage a synthetic incident
- Turn incidents into regression cases
- Operate a telemetry contract
Your download includes
- 21-page tagged PDF with linked contents
- Reflowable EPUB for ebook readers
- Local Python project, fictional input, recorded expected JSON output and 11 companion tests
- 3 explanatory diagrams
- 9 chapters with exercises and worked answers
Before you begin
Python 3.10 or later and a terminal. The supplied project runs locally and uses the Python standard library.
No model, API key, cloud account or network calls are used by the companion.
Learning prerequisites: Read basic JSON and Python; Understand a request and response; Run Python unittest.
Prepared with AI assistance. Independent human technical, editorial and assistive-technology reader review is pending.
The included examples are synthetic teaching material. Model access, software subscriptions, hosting, ongoing updates and consulting are not included.
CLEAR EXPECTATIONS
Before you buy.
What will I build?
Turn synthetic spans into a reproducible triage report, separate transport success from answer quality, and design telemetry that supports incident decisions without copying every prompt. The local companion uses fictional teaching fixtures. Project limits: Synthetic spans use a simplified schema; not OTLP or an OpenTelemetry SDK integration. Durations are supplied fixtures; no wall-clock instrumentation or causal root-cause proof. Routing is a transparent heuristic; no production SLO, sampled population estimate or actual model quality claim.
What was tested?
The 11 companion tests passed on the packaged project. The supplied fictional fixture produced its recorded expected JSON output. EPUBCheck reported no errors or warnings; DAISY Ace and PDF/UA automated checks passed. These local teaching checks are not production accuracy claims or certification. Independent human technical, editorial and assistive-technology reader review remains pending.
How do I get the files?
Complete the secure Lemon Squeezy checkout to access the PDF, EPUB and companion ZIP. Keep your receipt and download access private. This is a one-time purchase of edition 1.0.0; ongoing updates and consulting are not included.
Can I share the book or the companion code?
The full ebook is licensed to one reader. The labelled free sample may be shared unchanged. The companion project is MIT licensed and may be adapted or shared with its licence notice. See the exact ebook terms.
Connect request paths, operational signals, and answer-quality evidence
One book. A complete learning project. Evidence you can inspect.
AI-assisted · Independent human review pending
$2.99USDBuy ebook