Pranav Shukla and Sharath Kumar M N - Learning Elastic Stack 7.0: Distributed search, analytics, and visualization using Elasticsearch, Logstash, Beats, and Kibana, 2nd Edition
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Pranav Shukla is the founder and CEO of Valens DataLabs, a technologist, husband, and father of two. He is a big data architect and software craftsman who uses JVM-based languages. Pranav has over 15 years experience in architecting enterprise applications for Fortune 500 companies and start-ups. His core expertise lies in building JVM-based, scalable, reactive, and data-driven applications using Java/Scala, the Hadoop ecosystem, Apache Spark, and NoSQL databases. Pranav founded Valens DataLabs with the vision of helping companies to leverage data to their competitive advantage. In his spare time, he enjoys reading books, playing musical instruments, and playing tennis.
Sharath Kumar M N did his master's in computer science at the University of Texas, Dallas, USA. He is currently working as a senior principal architect at Broadcom. Prior to this, he was working as an Elasticsearch solutions architect at Oracle. He has given several tech talks at conferences such as Oracle Code events. Sharath is a certified trainer Elastic Certified Instructor one of the few technology experts in the world who has been certified by Elastic Inc. to deliver their official from the creators of Elastic training. He is also a data science and machine learning enthusiast.
In his free time, he likes playing with his lovely niece, Monisha; nephew, Chirayu; and his pet, Milo.
Tan-Vinh Nguyen is a Switzerland-based Java, Elasticsearch, and Kafka enthusiast. He has more than 15 years experience in enterprise software development. As Elastic Certified Engineer, he works currently for mimacom ag in international Elasticsearch projects. He runs a blog named Cinhtau, where he evaluates technology, concepts, and best practices. His blog posts enable and empower application developers to accomplish their missions.
Marcelo Ochoa works for Direccin TICs of Facultad de Ciencias Exactas at Universidad Nacional del Centro de la Prov. de Buenos Aires and is the CTO at Scotas.com, a company that specializes in near real-time search solutions using Apache Solr and Oracle. He divides his time between ...
, Introducing Elastic Stack , motivates you by introducing the core components of Elastic Stack, and the importance of the distributed, scalable search and analytics that Elastic Stack offers by means of use cases involving Elasticsearch. The chapter provides a brief introduction to all the core components, where they fit into the overall stack, and the purpose of each component. It concludes with instructions for downloading and installing Elasticsearch and Kibana to get started.
, Getting Started with Elasticsearch , introduces the core concepts involved in Elasticsearch, which form the backbone of the Elastic Stack. Concepts such as indexes, types, nodes, and clusters are introduced. You will also be introduced to the REST API to perform essential operations, datatypes, and mappings.
, Searching What is Relevant , focuses on the search use case of Elasticsearch. It introduces the concepts of text analysis, tokenizers, analyzers, and the need for analysis and relevance-based searches. The chapter highlights an example use case to cover the relevance-based search topics.
, Analytics with Elasticsearch , covers various types of aggregations by means of examples in order for you to acquire an in-depth understanding. This chapter covers very simple to complex aggregations to get powerful insights from terabytes of data. The chapter also covers the motivation behind using different types of aggregations.
, Analyzing Log Data , establishes the foundation for the motivation behind Logstash, its architecture, and installing and configuring Logstash to set up basic data pipelines. Elastic 5 introduced ingest nodes, which can be used instead of a dedicated Logstash setup. This chapter also covers building pipelines using Elastic ingest nodes.
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