Chaos Engineering for AI Infrastructure (Paperback)
Language: English
Published by Gitforgits, 2026
- Softcover
- New
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
AbeBooks seller since October 12, 2005
Condition: New
£ 47.90
Quantity: 1 available
Add to basketItem description from seller
Paperback. How long do you think it would take you to notice if your AI system started giving worse answers?Honestly, for most teams, it's weeks, and the news comes from a customer. Chaos engineering answers that question for infrastructure in about thirty seconds, because if a server goes down, it either reroutes or it doesn't. And language models completely shatter all those assumptions. Their output varies for real, their decay builds up instead of happening straight away, and those failures are confident, plausible, and wrong while latency, error rate, and pod health stay exactly where they should be.This book sets out the new framework for AI infrastructure. You'll find that, working through one support-assistant application across twelve chapters, everything moves from defining steady state for probabilistic systems to injecting faults at every layer, including accelerators, inference servers, model artefacts, retrieval pipelines, model APIs, autonomous agents, distributed training and the monitoring stack itself.Just to be clear, the toolchain is intentionally kept small. The LitmusChaos orchestrates, the Chaos Mesh reaches the kernel and filesystem, and the mitmproxy handles the content-level faults that neither can touch, extended with custom injectors where nothing suitable exists. So, every experiment comes to one of these four conclusions, and then the last chapter sums them all up as a programme scorecard.Key LearningsWrite down what "working correctly" means when your system's output legitimately varies.Break GPUs and inference servers on purpose, with a restore path that always runs.Spot the failures that keep every dashboard green and every alert silent.Check model weights for damage before loading them, not after serving starts.Catch the model release that scores better overall while getting worse where it matters.Find out whether your RAG pipeline is helping, or quietly making answers worse.Corrupt what the model returns, then watch whether your agent notices.Stop your remediation agent from making an incident worse than it was.Prove your training checkpoints actually resume the run they claim to continue.Catch slow decay in hours instead of days by changing how you alert.Table of ContentWhy AI Systems Fail Differently?Steady State for Probabilistic SystemLab and the ToolchainAccelerator and Compute ChaosInference Serving ChaosModel Artifacts, Registries, and Version SkewRetrieval and Context ChaosModel-Boundary ChaosAgentic and Multi-Agent ChaosDistributed Training and Choas Fine-TuningObserving Probabilistic DegradationOperationalizing Chaos This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…
Seller Inventory # 9789349174771
- Title
- Chaos Engineering for AI Infrastructure (Paperback)
- Author
- Neel Trove
- Publisher
- Gitforgits
- Publication year
- 2026
- Condition
- new
- Binding
- Paperback
- Language
- English
- ISBN 10
- 9349174774
- ISBN 13
- 9789349174771
How long do you think it would take you to notice if your AI system started giving worse answers?
Honestly, for most teams, it's weeks, and the news comes from a customer. Chaos engineering answers that question for infrastructure in about thirty seconds, because if a server goes down, it either reroutes or it doesn't. And language models completely shatter all those assumptions. Their output varies for real, their decay builds up instead of happening straight away, and those failures are confident, plausible, and wrong while latency, error rate, and pod health stay exactly where they should be.
This book sets out the new framework for AI infrastructure. You'll find that, working through one support-assistant application across twelve chapters, everything moves from defining steady state for probabilistic systems to injecting faults at every layer, including accelerators, inference servers, model artefacts, retrieval pipelines, model APIs, autonomous agents, distributed training and the monitoring stack itself.
Just to be clear, the toolchain is intentionally kept small. The LitmusChaos orchestrates, the Chaos Mesh reaches the kernel and filesystem, and the mitmproxy handles the content-level faults that neither can touch, extended with custom injectors where nothing suitable exists. So, every experiment comes to one of these four conclusions, and then the last chapter sums them all up as a programme scorecard.
Key Learnings
- Write down what "working correctly" means when your system's output legitimately varies.
- Break GPUs and inference servers on purpose, with a restore path that always runs.
- Spot the failures that keep every dashboard green and every alert silent.
- Check model weights for damage before loading them, not after serving starts.
- Catch the model release that scores better overall while getting worse where it matters.
- Find out whether your RAG pipeline is helping, or quietly making answers worse.
- Corrupt what the model returns, then watch whether your agent notices.
- Stop your remediation agent from making an incident worse than it was.
- Prove your training checkpoints actually resume the run they claim to continue.
- Catch slow decay in hours instead of days by changing how you alert.
Table of Content
- Why AI Systems Fail Differently?
- Steady State for Probabilistic System
- Lab and the Toolchain
- Accelerator and Compute Chaos
- Inference Serving Chaos
- Model Artifacts, Registries, and Version Skew
- Retrieval and Context Chaos
- Model-Boundary Chaos
- Agentic and Multi-Agent Chaos
- Distributed Training and Choas Fine-Tuning
- Observing Probabilistic Degradation
- Operationalizing Chaos
"Synopsis" may belong to another edition of this title.
Grand Eagle Retail
Bensenville, IL, U.S.A.
AbeBooks seller since October 12, 2005
Shipping rates within U.S.A.
| Item | 6 to 14 business days | 6 to 16 business days |
|---|---|---|
| First item | £ 0.00 | £ 0.00 |
Payment methods
Seller's business information
APOLLO ONLINE CORP.
605 Geddes Street
Wilmington, DE U.S.A. 19805
Terms of sale
We guarantee the condition of every book as it¿s described on the Abebooks web sites. If you¿ve changed
your mind about a book that you¿ve ordered, please use the Ask bookseller a question link to contact us
and we¿ll respond within 2 business days.
Books ship from California and Michigan.
Right of withdrawal
If you are a consumer you can withdraw from the contract in accordance with the following. Consumer means any natural person who is acting for purposes which are outside his trade, business, craft or profession.
Information regarding the right of withdrawal
Statutory right to withdraw
You have the right to withdraw from this contract within 14 days without giving any reason.
The withdrawal period will expire after 14 days from the day on which you acquire, or a third party other than the carrier and indicated by you acquires, physical possession of the last good or the last lot or piece.
To exercise the right of withdrawal, electronically fill in and submit a clear statement on our website, under "My Purchases" in "My Account". We will communicate to you an acknowledgement of receipt of such a withdrawal on a durable medium (e.g. by e-mail) without delay.
To meet the withdrawal deadline, it is sufficient for you to send your communication concerning your exercise of the right of withdrawal before the withdrawal period has expired.
Effects of withdrawal
If you withdraw from this contract, we will reimburse to you all payments received from you, including the costs of delivery (except for the supplementary costs arising if you chose a type of delivery other than the least expensive type of standard delivery offered by us).
We may make a deduction from the reimbursement for loss in value of any goods supplied, if the loss is the result of unnecessary handling by you.
We will make the reimbursement without undue delay, and not later than 14 days after the day on which we are informed about your decision to withdraw from this contract.
We will make the reimbursement using the same means of payment as you used for the initial transaction, unless you have expressly agreed otherwise; in any event, you will not incur any fees as a result of such reimbursement.
We may withhold reimbursement until we have received the goods back, or you have supplied evidence of having sent back the goods, whichever is the earliest.
You shall send back the goods or hand them over to Grand Eagle Retail, Bensenville, Illinois, U.S.A., without undue delay and in any event not later than 14 days from the day on which you communicate your withdrawal from this contract to us. The deadline is met if you send back the goods before the period of 14 days has expired. You will have to bear the direct cost of returning the goods. You are only liable for any diminished value of the goods resulting from the handling other than what is necessary to establish the nature, characteristics and functioning of the goods.
Exceptions to the right of withdrawal
The right of withdrawal does not apply to:
- The delivery of newspapers, journals or magazines with the exception of subscription contracts; and
- The supply of digital content which is not supplied on a tangible medium (e.g. on a CD or DVD) if you accepted when you placed your order that we could start to deliver it, and that you could not withdraw once delivery had started.
Shipping terms
Orders usually ship within 2 business days. All books within the US ship free of charge. Delivery is 4-14 business days anywhere in the United States.
Books ship from California and Michigan.
If your book order is heavy or oversized, we may contact you to let you know extra shipping is required.