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Cloud Observability with Azure Monitor

You're reading from   Cloud Observability with Azure Monitor A practical guide to monitoring your Azure infrastructure and applications using industry best practices

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Product type Paperback
Published in Nov 2024
Publisher Packt
ISBN-13 9781835881187
Length 368 pages
Edition 1st Edition
Languages
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Authors (2):
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Manuel Lázaro Ramírez Manuel Lázaro Ramírez
Author Profile Icon Manuel Lázaro Ramírez
Manuel Lázaro Ramírez
José Ángel Fernández José Ángel Fernández
Author Profile Icon José Ángel Fernández
José Ángel Fernández
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Toc

Table of Contents (19) Chapters Close

Preface 1. Part 1:Fundamentals of Observability and Azure Monitor
2. Chapter 1: Introduction to Observability with Azure Monitor FREE CHAPTER 3. Chapter 2: Understanding Azure Monitor Components and Functions 4. Chapter 3: Exploring Azure Monitor Data Sources and the Ingestion Pipeline 5. Part 2: Working with Azure Monitor
6. Chapter 4: Analyzing Your Data Using Logs and Metrics 7. Chapter 5: Responding to Monitoring Events 8. Chapter 6: Visualizing Your Logs and Metrics 9. Chapter 7: Application Observability and Performance Monitoring with Application Insights 10. Part 3: The Road Ahead with Azure Observability
11. Chapter 8: Hybrid and Multi-Cloud Monitoring 12. Chapter 9: Integrating with Third-Party Tools 13. Chapter 10: Building Your Monitoring Strategy 14. Chapter 11: Cost Management and Optimization 15. Chapter 12: Future Trends and Looking Ahead 16. Index 17. Other Books You May Enjoy Appendix

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

A

action groups 136

configuring 136-142

actions

configuring 136-142

activity log alert rules 129

actions 134

condition 130-134

details 134, 135

scope 130

activity log alerts 29

activity logs

exporting 261, 262

Administrative Activity log 129

AI-driven analytics, with Azure Monitor

AI, for forecasting and anomaly detection 311

data collection and aggregation 310

machine learning models 310

AI-powered assistants

for observability 311, 312

alert processing rules 142

details 146, 147

rule settings 144

scheduling 144-146

scope 142

alert rule 28, 29

alerts 24, 295

consolidate alerts 295

flow 114

pricing structure 297, 298

Amazon Web Services (AWS) 15

analytics log querying 294

Analytics Logs 82

characteristics...

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