Elasticsearch 7 and the Elastic Stack: In Depth and Hands On

• Install and configure Elasticsearch 7 on a cluster
• Create search indices and mappings
• Search full-text and structured data in several different ways
• Import data into Elasticsearch using several different techniques
• Integrate Elasticsearch with other systems, such as Spark, Kafka, relational databases, S3, and more
• Aggregate structured data using buckets and metrics
• Use Logstash and the "ELK stack" to import streaming log data into Elasticsearch
• Use Filebeats and the Elastic Stack to import streaming data at scale
• Analyze and visualize data in Elasticsearch using Kibana
• Manage operations on production Elasticsearch clusters
• Use cloud-based solutions including Amazon's Elasticsearch Service and Elastic Cloud

We've teamed up with Coralogix to co-produce the most comprehensive Elastic Stack course we've seen. Elasticsearch7 is a powerful tool not only for powering search on big websites, but also for analyzing big data sets in a matter of milliseconds! It's an increasingly popular technology, and a valuable skill to have in today's job market. This course covers it all, from installation to operations, withover 100 lecturesincluding11 hoursof video.

We'll cover setting up search indices on anElasticsearch 7cluster (if you need Elasticsearch 5 or 6- we have other courses on that), and querying that data in many different ways. Fuzzy searches, partial matches, search-as-you-type, pagination, sorting - you name it. And it's not just theory, every lesson has hands-on examples whereyou'll practice each skillusing a virtual machine running Elasticsearchon your own PC.

We'll explore what's new in Elasticsearch 7 - including index lifecycle management, the deprecation of types and type mappings, and a hands-on activity with ElasticsearchSQL.We've also added much more depth on managing security with the Elastic Stack, and how backpressure works with Beats.

We cover, in depth, the often-overlooked problem ofimporting datainto an Elasticsearch index. Whether it's via raw RESTful queries, scripts using Elasticsearch API's, or integration with other "big data" systems like Spark and Kafka - you'll see many ways to get Elasticsearch started from large, existing data sets at scale. We'll also stream data into Elasticsearch usingLogstashandFilebeat- commonly referred to as the "ELKStack" (Elasticsearch / Logstash / Kibana) or the "Elastic Stack".

Elasticsearchisn't just for search anymore- it has powerfulaggregationcapabilities for structured data. We'll bucket and analyze data using Elasticsearch, and visualize it using the Elastic Stack's web UI,Kibana and Kibana Lens.

You'll learn how to manageoperationson your Elastic Stack, using X-Pack to monitor your cluster's health, and how to perform operational tasks like scaling up your cluster, and doing rolling restarts. We'll also spin up Elasticsearch clusters in the cloud usingAmazon ElasticsearchServiceand theElastic Cloud.

Elasticsearch is positioning itself to be a much faster alternative to Hadoop, Spark, and Flink for many common data analysis requirements. It's an important tool to understand, and it's easy to use! Dive in with me and I'll show you what it's all about.