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Observability in the AI-Native Era. AIOps: Building, Observing, and Operating Resilient Systems in the Artificial Intelligence Age Andreas Grabner, Hilliary Lipsig, Robert Rati

(ebook) (audiobook) (audiobook) Język publikacji: angielski
Observability in the AI-Native Era. AIOps: Building, Observing, and Operating Resilient Systems in the Artificial Intelligence Age Andreas Grabner, Hilliary Lipsig, Robert Rati - okladka książki

Observability in the AI-Native Era. AIOps: Building, Observing, and Operating Resilient Systems in the Artificial Intelligence Age Andreas Grabner, Hilliary Lipsig, Robert Rati - okladka książki

Observability in the AI-Native Era. AIOps: Building, Observing, and Operating Resilient Systems in the Artificial Intelligence Age Andreas Grabner, Hilliary Lipsig, Robert Rati - audiobook MP3

Observability in the AI-Native Era. AIOps: Building, Observing, and Operating Resilient Systems in the Artificial Intelligence Age Andreas Grabner, Hilliary Lipsig, Robert Rati - audiobook CD

Autorzy:
Andreas Grabner, Hilliary Lipsig, Robert Rati
Ocena:
With OpenTelemetry, observability has become central to building and operating cloud-native distributed systems. At the same time, advances in AI are transforming how we extract value from the growing volume of observability data. This book shows you how to implement scalable observability, improve engineering efficiency with AI, and extend observability practices from production into development through modern internal developer platforms.

You’ll begin with the fundamentals of observability, logs, metrics, and traces, then learn how AIOps enhances signal correlation, anomaly detection, and root-cause analysis. Through real-world examples and architectural guidance, the book demonstrates how to integrate AIOps into existing systems and build pipelines that proactively detect and resolve issues before users are affected.

You’ll also explore best practices for expanding observability across the software development lifecycle, enabling AI-powered observability as a self-service capability for engineers. Using tools such as OpenTelemetry, Prometheus, Elasticsearch, and Grafana alongside machine learning models, you’ll learn how to automate diagnostics and remediation.

By the end of this book, you’ll be able to design and implement AIOps-enabled observability solutions that make cloud-native systems more resilient and efficient.

O autorach książki

Andreas Grabner is a technical advocate for making distributed systems observable and making automated data-driven decisions across the software development lifecycle. In his capacity as a CNCF ambassador and a DevRel at Dynatrace, he connects and educates global software engineering communities on building and continuously validating digital services for resiliency, high availability, and security.
Since his early days, he has been passionate about software quality and performance engineering as it results in building excellent digital products. Andi uses his advocacy platforms to share best practices on topics such as observability, progressive delivery, DevOps, site reliability engineering, platform engineering, and digital business operations!
Hilliary Lipsig is an autodidact and start-up veteran who has frequently learned and applied technologies to get a job done. She's had her hand in every part of the application delivery process, honing her skills originally as a quality engineer. Hilliary is an IT polyglot, able to talk the lingo of both the Operations and Development teams. She's currently a Principal Site Reliability Engineer at Red Hat Inc., working on Kubernetes-based platforms. She's passionate about GitOps, continuous integration, scalable processes, consistency in tooling, and good developer documentation. Her open source activities include contributions to the CNCF Glossary and she's a member of the Code of Conduct Committee for Kubernetes.

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