Book Image

Microsoft Sentinel in Action - Second Edition

By : Richard Diver, Gary Bushey, John Perkins
Book Image

Microsoft Sentinel in Action - Second Edition

By: Richard Diver, Gary Bushey, John Perkins

Overview of this book

Microsoft Sentinel is a security information and event management (SIEM) tool developed by Microsoft that helps you integrate cloud security and artificial intelligence (AI). This book will teach you how to implement Microsoft Sentinel and understand how it can help detect security incidents in your environment with integrated AI, threat analysis, and built-in and community-driven logic. The first part of this book will introduce you to Microsoft Sentinel and Log Analytics, then move on to understanding data collection and management, as well as how to create effective Microsoft Sentinel queries to detect anomalous behaviors and activity patterns. The next part will focus on useful features, such as entity behavior analytics and Microsoft Sentinel playbooks, along with exploring the new bi-directional connector for ServiceNow. In the next part, you’ll be learning how to develop solutions that automate responses needed to handle security incidents and find out more about the latest developments in security, techniques to enhance your cloud security architecture, and explore how you can contribute to the security community. By the end of this book, you’ll have learned how to implement Microsoft Sentinel to fit your needs and protect your environment from cyber threats and other security issues.
Table of Contents (23 chapters)
1
Section 1: Design and Implementation
4
Section 2: Data Connectors, Management, and Queries
9
Section 3: Security Threat Hunting
15
Section 4: Integration and Automation
18
Section 5: Operational Guidance

Reviewing alternative storage options

The benefit of retaining data within Log Analytics is the speed of access to search the data when needed, without having to write new queries. However, many organizations require specific log data to be retained for long periods of time, usually to meet internal governance controls, external compliance requirements, or local laws. Currently, there is a limitation to retaining data within Log Analytics, as it only supports storage for up to 2 years.

The following solutions may be considered as an alternative for long-term storage, outside of Log Analytics:

  • Azure Blob Storage: You can create a query in Azure Monitor to select the data you want to move from the Log Analytics workspace and point it to the appropriate Azure storage account. This allows for filtering of the information by type (or select everything), and only moving data that is about to come to the end of its life, which is the limit you have set for data retention in the...