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Ansible Quick Start Guide. Control and monitor infrastructures of any size, physical or virtual
Mohamed Alibi
Configuration Management (CM) tools help administrators reduce their workload. Ansible is one of the best Configuration Management tools, and can act as an orchestrator for managing other CMs. This book is the easiest way to learn how to use Ansible as an orchestrator and a Configuration Management tool. With this book, you will learn how to control and monitor computer and network infrastructures of any size,physical or virtual. You will begin by learning about the Ansible client-server architecture. To get started, you will set up and configure an Ansible server. You will then go through the major features of Ansible: Playbook and Inventory. Then, we will look at Ansible systems and network modules. You will then use Ansible to enable infrastructure automated configuration management, followed by best practices for using Ansible roles and community modules. Finally, you will explore Ansible features such as Ansible Vault, Ansible Containers, and Ansible plugins.
Nir Yehoshua, Uriel Kosayev
Antivirus software is built to detect, prevent, and remove malware from systems, but this does not guarantee the security of your antivirus solution as certain changes can trick the antivirus and pose a risk for users. This book will help you to gain a basic understanding of antivirus software and take you through a series of antivirus bypass techniques that will enable you to bypass antivirus solutions.The book starts by introducing you to the cybersecurity landscape, focusing on cyber threats, malware, and more. You will learn how to collect leads to research antivirus and explore the two common bypass approaches used by the authors. Once you’ve covered the essentials of antivirus research and bypassing, you'll get hands-on with bypassing antivirus software using obfuscation, encryption, packing, PowerShell, and more. Toward the end, the book covers security improvement recommendations, useful for both antivirus vendors as well as for developers to help strengthen the security and malware detection capabilities of antivirus software.By the end of this security book, you'll have a better understanding of antivirus software and be able to confidently bypass antivirus software.
Apache Airflow Best Practices. A practical guide to orchestrating data workflow with Apache Airflow
Dylan Intorf, Dylan Storey, Kendrick van Doorn
Data professionals face the challenge of managing complex data pipelines, orchestrating workflows across diverse systems, and ensuring scalable, reliable data processing. This definitive guide to mastering Apache Airflow, written by experts in engineering, data strategy, and problem-solving across tech, financial, and life sciences industries, is your key to overcoming these challenges. Covering everything from Airflow fundamentals to advanced topics such as custom plugin development, multi-tenancy, and cloud deployment, this book provides a structured approach to workflow orchestration. You’ll start with an introduction to data orchestration and Apache Airflow 2.x updates, followed by DAG authoring, managing Airflow components, and connecting to external data sources. Through real-world use cases, you’ll learn how to implement ETL pipelines and orchestrate ML workflows in your environment, and scale Airflow for high availability and performance. You’ll also learn how to deploy Airflow in cloud environments, tackle operational considerations for scaling, and apply best practices for CI/CD and monitoring.By the end of this book, you’ll be proficient in operating and using Apache Airflow, authoring high-quality workflows in Python, and making informed decisions crucial for production-ready Airflow implementations.
Scott Cranton, Jakub Korab
Apache Camel is a de-facto standard for developing integrations in Java, and is based on well-understood Enterprise Integration Patterns. It is used within many commercial and open source integration products. Camel makes common integration tasks easy while still providing the developer with the means to customize the framework when the situation demands it. Tasks such as protocol mediation, message routing and transformation, and auditing are common usages of Camel. Apache Camel Developer's Cookbook provides hundreds of best practice tips for using Apache Camel in a format that helps you build your Camel projects. Each tip or recipe provides you with the most important steps to perform along with a summary of how it works, with references to further reading if you need more information. This book is intended to be a reliable information source that is quicker to use than an Internet search. Apache Camel Developer's Cookbook is a quick lookup guide that can also be read from cover to cover if you want to get a sense of the full power of Apache Camel. This book provides coverage of the full lifecycle of creating Apache Camel-based integration projects, including the structure of your Camel code and using the most common Enterprise Integration patterns. Patterns like Split/Join and Aggregation are covered in depth in this book. Throughout this book, you will be learning steps to transform your data. You will also learn how to perform unit and integration testing of your code using Camel's extensive testing framework, and also strategies for debugging and monitoring your code. Advanced topics like Error Handling, Parallel Processing, Transactions, and Security will also be covered in this book. This book provides you with practical tips on using Apache Camel based on years of hands-on experience from hundreds of integration projects.
Nitin Padalia
Apache Cassandra Essentials takes you step-by-step from from the basics of installation to advanced installation options and database design techniques. It gives you all the information you need to effectively design a well distributed and high performance database. You’ll get to know about the steps that are performed by a Cassandra node when you execute a read/write query, which is essential to properly maintain of a Cassandra cluster and to debug any issues. Next, you’ll discover how to integrate a Cassandra driver in your applications and perform read/write operations. Finally, you’ll learn about the various tools provided by Cassandra for serviceability aspects such as logging, metrics, backup, and recovery.
Steve Hoffman, Steven Hoffman, Kevin A. McGrail
Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data. Its main goal is to deliver data from applications to Apache Hadoop's HDFS. It has a simple and flexible architecture based on streaming data flows. It is robust and fault tolerant with many failover and recovery mechanisms.Apache Flume: Distributed Log Collection for Hadoop covers problems with HDFS and streaming data/logs, and how Flume can resolve these problems. This book explains the generalized architecture of Flume, which includes moving data to/from databases, NO-SQL-ish data stores, as well as optimizing performance. This book includes real-world scenarios on Flume implementation.Apache Flume: Distributed Log Collection for Hadoop starts with an architectural overview of Flume and then discusses each component in detail. It guides you through the complete installation process and compilation of Flume.It will give you a heads-up on how to use channels and channel selectors. For each architectural component (Sources, Channels, Sinks, Channel Processors, Sink Groups, and so on) the various implementations will be covered in detail along with configuration options. You can use it to customize Flume to your specific needs. There are pointers given on writing custom implementations as well that would help you learn and implement them.By the end, you should be able to construct a series of Flume agents to transport your streaming data and logs from your systems into Hadoop in near real time.
Apache Hadoop 3 Quick Start Guide. Learn about big data processing and analytics
Hrishikesh Vijay Karambelkar
Apache Hadoop is a widely used distributed data platform. It enables large datasets to be efficiently processed instead of using one large computer to store and process the data. This book will get you started with the Hadoop ecosystem, and introduce you to the main technical topics, including MapReduce, YARN, and HDFS.The book begins with an overview of big data and Apache Hadoop. Then, you will set up a pseudo Hadoop development environment and a multi-node enterprise Hadoop cluster. You will see how the parallel programming paradigm, such as MapReduce, can solve many complex data processing problems.The book also covers the important aspects of the big data software development lifecycle, including quality assurance and control, performance, administration, and monitoring. You will then learn about the Hadoop ecosystem, and tools such as Kafka, Sqoop, Flume, Pig, Hive, and HBase. Finally, you will look at advanced topics, including real time streaming using Apache Storm, and data analytics using Apache Spark. By the end of the book, you will be well versed with different configurations of the Hadoop 3 cluster.
Hanish Bansal, Shrey Mehrotra, Saurabh Chauhan
Hive was developed by Facebook and later open sourced in Apache community. Hive provides SQL like interface to run queries on Big Data frameworks. Hive provides SQL like syntax also called as HiveQL that includes all SQL capabilities like analytical functions which are the need of the hour in today’s Big Data world.This book provides you easy installation steps with different types of metastores supported by Hive. This book has simple and easy to learn recipes for configuring Hive clients and services. You would also learn different Hive optimizations including Partitions and Bucketing. The book also covers the source code explanation of latest Hive version.Hive Query Language is being used by other frameworks including spark. Towards the end you will cover integration of Hive with these frameworks.
Dayong Du
In this book, we prepare you for your journey into big data by frstly introducing you to backgrounds in the big data domain, alongwith the process of setting up and getting familiar with your Hive working environment. Next, the book guides you through discovering and transforming the values of big data with the help of examples. It also hones your skills in using the Hive language in an effcient manner. Toward the end, the book focuses on advanced topics, such as performance, security, and extensions in Hive, which will guide you on exciting adventures on this worthwhile big data journey. By the end of the book, you will be familiar with Hive and able to work effeciently to find solutions to big data problems
Apache Ignite Quick Start Guide. Distributed data caching and processing made easy
Sujoy Acharya
Apache Ignite is a distributed in-memory platform designed to scale and process large volume of data. It can be integrated with microservices as well as monolithic systems, and can be used as a scalable, highly available and performant deployment platform for microservices. This book will teach you to use Apache Ignite for building a high-performance, scalable, highly available system architecture with data integrity.The book takes you through the basics of Apache Ignite and in-memory technologies. You will learn about installation and clustering Ignite nodes, caching topologies, and various caching strategies, such as cache aside, read and write through, and write behind. Next, you will delve into detailed aspects of Ignite’s data grid: web session clustering and querying data.You will learn how to process large volumes of data using compute grid and Ignite’s map-reduce and executor service. You will learn about the memory architecture of Apache Ignite and monitoring memory and caches. You will use Ignite for complex event processing, event streaming, and the time-series predictions of opportunities and threats. Additionally, you will go through off-heap and on-heap caching, swapping, and native and Spring framework integration with Apache Ignite.By the end of this book, you will be confident with all the features of Apache Ignite 2.x that can be used to build a high-performance system architecture.
Raúl Estrada
Apache Kafka provides a unified, high-throughput, low-latency platform to handle real-time data feeds. This book will show you how to use Kafka efficiently, and contains practical solutions to the common problems that developers and administrators usually face while working with it. This practical guide contains easy-to-follow recipes to help you set up, configure, and use Apache Kafka in the best possible manner. You will use Apache Kafka Consumers and Producers to build effective real-time streaming applications. The book covers the recently released Kafka version 1.0, the Confluent Platform and Kafka Streams. The programming aspect covered in the book will teach you how to perform important tasks such as message validation, enrichment and composition.Recipes focusing on optimizing the performance of your Kafka cluster, and integrate Kafka with a variety of third-party tools such as Apache Hadoop, Apache Spark, and Elasticsearch will help ease your day to day collaboration with Kafka greatly. Finally, we cover tasks related to monitoring and securing your Apache Kafka cluster using tools such as Ganglia and Graphite.If you're looking to become the go-to person in your organization when it comes to working with Apache Kafka, this book is the only resource you need to have.
Raúl Estrada
Apache Kafka is a great open source platform for handling your real-time data pipeline to ensure high-speed filtering and pattern matching on the ?y. In this book, you will learn how to use Apache Kafka for efficient processing of distributed applications and will get familiar with solving everyday problems in fast data and processing pipelines.This book focuses on programming rather than the configuration management of Kafka clusters or DevOps. It starts off with the installation and setting up the development environment, before quickly moving on to performing fundamental messaging operations such as validation and enrichment.Here you will learn about message composition with pure Kafka API and Kafka Streams. You will look into the transformation of messages in different formats, such asext, binary, XML, JSON, and AVRO. Next, you will learn how to expose the schemas contained in Kafka with the Schema Registry. You will then learn how to work with all relevant connectors with Kafka Connect. While working with Kafka Streams, you will perform various interesting operations on streams, such as windowing, joins, and aggregations. Finally, through KSQL, you will learn how to retrieve, insert, modify, and delete data streams, and how to manipulate watermarks and windows.
Apache Karaf Cookbook. Over 60 recipes to help you get the most out of your Apache Karaf deployments
Jamie Goodyear, Johan Edstorm, Achim Nierbeck, Heath...
Apache Mahout Clustering Designs. Explore clustering algorithms used with Apache Mahout
Dragan Milcevski, Ashish Gupta, Ashish Gupta