Book Image

Building a Next-Gen SOC with IBM QRadar

By : Ashish M Kothekar
Book Image

Building a Next-Gen SOC with IBM QRadar

By: Ashish M Kothekar

Overview of this book

This comprehensive guide to QRadar will help you build an efficient security operations center (SOC) for threat hunting and need-to-know software updates, as well as understand compliance and reporting and how IBM QRadar stores network data in real time. The book begins with a quick introduction to QRadar components and architecture, teaching you the different ways of deploying QRadar. You’ll grasp the importance of being aware of the major and minor upgrades in software and learn how to scale, upgrade, and maintain QRadar. Once you gain a detailed understanding of QRadar and how its environment is built, the chapters will take you through the features and how they can be tailored to meet specifi c business requirements. You’ll also explore events, flows, and searches with the help of examples. As you advance, you’ll familiarize yourself with predefined QRadar applications and extensions that successfully mine data and find out how to integrate AI in threat management with confidence. Toward the end of this book, you’ll create different types of apps in QRadar, troubleshoot and maintain them, and recognize the current security challenges and address them through QRadar XDR. By the end of this book, you’ll be able to apply IBM QRadar SOC’s prescriptive practices and leverage its capabilities to build a very efficient SOC in your enterprise.
Table of Contents (18 chapters)
Part 1: Understanding Different QRadar Components and Architecture
Part 2: QRadar Features and Deployment
Part 3: Understanding QRadar Apps, Extensions, and Their Deployment

Distributed deployment

In all-in-one deployment, the heavy lifting work in terms of data processing and storage was done by the Console. Once processors are added, we add more processing power and more storage. This helps the Console to free up resources for other important tasks.

In huge customer deployments where terabytes of data are processed daily, using all-in-one deployment will not suffice. We need more processors to correlate data and store it. Each processor comes with individual storage capacity. For example, for one of the biggest deployments of QRadar, which processes around 2 TB of data on a daily basis, we have 3 Event Processors. These Event Processors are in high availability, which means that for each primary Event Processor, we have a corresponding secondary Event Processor present. Each of these three processors shares the load of correlating the incoming events to that particular processor. So, on average, each event’s average size could be around 500...