Elasticsearch 6 and Elastic Stack

I've been playing with and using the Elastic Stack for at least 4 years. This video course is by far the most informative, up-to-date and useful resource I've found.

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about the subject

Elasticsearch is an industry standard open source search engine. Built on Apache Lucene, Elasticsearch is lightning-fast, secure, and easy to use! Combine Elasticsearch with the Logstash data processing pipeline and the Kibana data analytics dashboard, and you have the powerful Elastic Stack platform, a complete data storage and analysis platform.

about the video

Elasticsearch 6 and Elastic Stack starts by showing you how to install Elasticsearch 6 on your PC and configure it on a cluster. From there, you’ll learn to bucket and analyze data using Elasticsearch and you’ll monitor your cluster’s health using X-Pack. You’ll set up search indices and query your data using common approaches like fuzzy searches, partial matches, search-as-you-type, and more. This amazing course teaches you to perform rolling restarts, scale up your cluster, and even spin up clusters in the cloud using Amazon Elasticsearch Service and the Elastic Cloud.

With Frank Kane’s practical instruction, you’ll tackle the often-overlooked problem of importing data into an Elasticsearch index. You’ll delve into raw RESTful queries and scripts using Elasticsearch APIs, and you’ll see how Elasticsearch seamlessly integrates with other big data systems like Spark and Kafka. After you’ve mastered Elasticsearch basics, you’ll explore the Elastic Stack. You’ll experience the data processing power of Logstash and pick up data analytics techniques with the interactive Kibana visual dashboard! Every lesson has hands-on examples, so you’ll practice your new search and analysis skills as you go!

prerequisites

For tech-minded individuals familiar with web services and REST. Some exposure to Linux and JSON-formatted data would also be beneficial.

what you will learn

• Create search indices and mappings
• Search full-text and structured data in several different ways
• Integrate Elasticsearch with other systems including Spark and Kafka
• Aggregate structured data using buckets and metrics
• Import data into Elasticsearch using several different techniques
• Use Logstash and Kibana to import streaming log data
• Use Filebeats and the Elastic Stack to import streaming data at scale
• Manage operations on production Elasticsearch clusters
• Use cloud-based solutions including Amazon's Elasticsearch Service and Elastic Cloud

about the instructor

Frank Kane holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. He spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to millions of customers every day. Sundog Software, his own company specializing in virtual reality environment technology and teaching others about big data analysis, is his pride and joy.