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Cyber Resiliency with Splunk Enterprise and IBM FlashSystem Storage Safeguarded Copy with IBM Copy Services Manager

The focus of this document is to highlight early threat detection by using Splunk Enterprise and proactively start a cyber resilience workflow in response to a cyberattack or malicious user action. The workflow uses IBM® Copy Services Manager (CSM) as orchestration software to invoke the IBM FlashSystem® storage Safeguarded Copy function, which creates an immutable copy of the data in an air-gapped form on the same IBM FlashSystem Storage for isolation and eventual quick recovery. This document explains the steps that are required to enable and forward IBM FlashSystem audit logs and set a Splunk forwarder configuration to forward local event logs to Splunk Enterprise. This document also describes how to create various alerts in Splunk Enterprise to determine a threat, and configure and invoke an appropriate response to the detected threat in Splunk Enterprise. This document explains the lab setup configuration steps that are involved in configuring various components like Splunk Enterprise, Splunk Enterprise config files for custom apps, IBM CSM, and IBM FlashSystem Storage. The last steps in the lab setup section demonstrate the automated Safeguarded Copy creation and validation steps. This document also describes brief steps for configuring various components and integrating them. This document demonstrates a use case for protecting a Microsoft SQL database (DB) volume that is created on IBM FlashSystem Storage. When a threat is detected on the Microsoft SQL DB volume, Safeguarded Copy starts on an IBM FlashSystem Storage volume. The Safeguarded Copy creates an immutable copy of the data, and the same data volume can be recovered or restored by using IBM CSM. This publication does not describe the installation procedures for Splunk Enterprise, Splunk Forwarder for IBM CSM, th Microsoft SQL server, or the IBM FlashSystem Storage setup. It is assumed that the reader of the book has a basic understanding of system, Windows, and DB administration; storage administration; and has access to the required software and documentation that is used in this document.

Apache Pulsar in Action

Deliver lightning fast and reliable messaging for your distributed applications with the flexible and resilient Apache Pulsar platform. In Apache Pulsar in Action you will learn how to: Publish from Apache Pulsar into third-party data repositories and platforms Design and develop Apache Pulsar functions Perform interactive SQL queries against data stored in Apache Pulsar Apache Pulsar in Action is a comprehensive and practical guide to building high-traffic applications with Pulsar. You’ll learn to use this mature and battle-tested platform to deliver extreme levels of speed and durability to your messaging. Apache Pulsar committer David Kjerrumgaard teaches you to apply Pulsar’s seamless scalability through hands-on case studies, including IOT analytics applications and a microservices app based on Pulsar functions. About the Technology Reliable server-to-server messaging is the heart of a distributed application. Apache Pulsar is a flexible real-time messaging platform built to run on Kubernetes and deliver the scalability and resilience required for cloud-based systems. Pulsar supports both streaming and message queuing, and unlike other solutions, it can communicate over multiple protocols including MQTT, AMQP, and Kafka’s binary protocol. About the Book Apache Pulsar in Action teaches you to build scalable streaming messaging systems using Pulsar. You’ll start with a rapid introduction to enterprise messaging and discover the unique benefits of Pulsar. Following crystal-clear explanations and engaging examples, you’ll use the Pulsar Functions framework to develop a microservices-based application. Real-world case studies illustrate how to implement the most important messaging design patterns. What's Inside Publish from Pulsar into third-party data repositories and platforms Design and develop Apache Pulsar functions Create an event-driven food delivery application About the Reader Written for experienced Java developers. No prior knowledge of Pulsar required. About the Author David Kjerrumgaard is a committer on the Apache Pulsar project. He currently serves as a Developer Advocate for StreamNative, where he develops Pulsar best practices and solutions. Quotes Apache Pulsar in Action is able to seamlessly mix the theory and abstract concepts with the clarity of practical step-by-step examples. I’d recommend to anyone! - Matteo Merli, co-creator of Apache Pulsar Gives readers insights into how the ‘magic’ works… Definitely recommended. - Henry Saputra, Splunk A complete, practical, fun-filled book. - Satej Kumar Sahu, Honeywell A definitive guide that will help you scale your applications. - Alessandro Campeis, Vimar The best book to start working with Pulsar. - Emanuele Piccinelli, Empirix

Understanding Log Analytics at Scale

If enabled, logging captures almost every system process, event, or message in your software or hardware. But once you have all that data, what do you do with it? This report shows you how to use log analytics—the process of gathering, correlating, and analyzing that information—to drive critical business insights and outcomes. Drawing on real-world use cases, Matt Gillespie outlines the opportunities for log analytics and the challenges you may face—along with approaches for meeting them. Data architects and IT and infrastructure leads will learn the mechanics of log analytics and key architectural considerations for data storage. The report also offers nine key guideposts that will help you plan and design your own solutions to obtain the full value from your log data. Learn the current state of log analytics and common challenges See how log analytics is helping organizations achieve better business outcomes in areas such as cybersecurity, IT operations, and industrial automation Explore tools for log analytics, including Splunk, the Elastic stack, and Sumo Logic Understand the role storage plays in ensuring successful outcomes

IBM Storage Solutions for Splunk Enterprise

This document is intended to facilitate the deployment of the Splunk Enterprise Solutions using IBM All Flash Array systems for the Hot and Warm tiers, and IBM Elastic Storage System for the Cold and Frozen tiers. This document provides the reference architecture and configuration guidelines for the IBM Storage systems. The information in this document is distributed on an "as is" basis without any warranty that is either expressed or implied. Support assistance for the use of this material is limited to situations where IBM Storage Systems are supported, entitled and where the issues are specific to a blueprint implementation.

Big Data Visualization

Dive into 'Big Data Visualization' and uncover how to tackle the challenges of visualizing vast quantities of complex data. With a focus on scalable and dynamic techniques, this guide explores the nuances of effective data analysis. You'll master tools and approaches to display, interpret, and communicate data in impactful ways. What this Book will help me do Understand the fundamentals of big data visualization, including unique challenges and solutions. Explore practical techniques for using D3 and Python to visualize and detect anomalies in big data. Learn to leverage dashboards like Tableau to present data insights effectively. Address and improve data quality issues to enhance analysis accuracy. Gain hands-on experience with real-world use cases for tools such as Hadoop and Splunk. Author(s) James D. Miller is an IBM-certified expert specializing in data analytics and visualization. With years of experience handling massive datasets and extracting actionable insights, he is dedicated to sharing his expertise. His practical approach is evident in how he combines tool mastery with a clear understanding of data complexities. Who is it for? This book is designed for data analysts, data scientists, and others involved in interpreting and presenting big datasets. Whether you are a beginner looking to understand big data visualization or an experienced professional seeking advanced tools and techniques, this guide suits your needs perfectly. A foundational knowledge in programming languages like R and big data platforms such as Hadoop is recommended to maximize your learning.