Elastcisearch

Időpont: 2018.11.05 + 11.08 + 11.26 + 11.29 (14-18h) This instructor-led course provides a strong foundation for getting started with Elasticsearch. It covers how to deploy and manage Elasticsearch clusters, as well as how to use your deployment to develop powerful search and analytics solutions. You will learn how to install, configure, manage, and secure Elasticsearch clusters, as well as how to troubleshoot issues you may encounter along the way. You will also explore the inner workings of Elasticsearch and gain insight into queries, analyzers, mappings, and aggregations as you learn to work with search results. After completing this course, you will be well on your way to becoming an Elastic Certified Engineer. The course is delivered by a certified Elasticsearch engineer with real-life experience in various Cloud technologies Software Developers and Engineers, Data Architects, System Administrators, DevOps No prior knowledge of the Elasticsearch required Technical requirements to attend the course Mac, Linux, or Windows Latest version of Chrome or Firefox (Safari is not 100% supported) Stable internet connection Due to virtual classroom JavaScript requirements, we recommend that you disable any ad-blockers and restart your browser before class. Elastic Stack Overview Learn how Elasticsearch and the components of the Elastic Stack work together to solve a myriad of use cases and real-world problems. Hands-on Lab   Getting Started with Elasticsearch Learn how to install Elasticsearch and how to get data in and out. Hands-on Lab   Querying Data Learn how to write and submit queries and how the scoring and relevance of matching documents is calculated. Hands-on Lab   Text Analysis and Mappings We walk through the details of how full text is analyzed and indexed in Elasticsearch, including a discussion of the various analyzers and filters and how to configure them. You will also learn how Elasticsearch mappings are used to define how your documents and fields are stored and indexed, including how to define multi-fields and custom analyzers. Hands-on Lab   The Distributed Model Understand how Elasticsearch scales and distributes data across a cluster, including details on shards, distributed search concepts, and sample architectures. Hands-on Lab   Troubleshooting Elasticsearch Learn to understand the health of your cluster and diagnose health issues, as well as allocate shards and diagnose shard issues. Hands-on Lab   Improving Search Results We take a deeper dive into searching data with a discussion on the multi_match query, configuring fuzziness for dealing with misspelled words, how to highlight matched search terms in a response, and how to perform common tasks when working with search results like sorting and pagination. Hands-on Lab

Időpont: 2019.02.25 + 02.28 + 03.18 + 03.21 (14-18h) This instructor-led course is designed for Elasticsearch professionals who need to expand their skill set for developing and managing powerful search and analytics solutions with the Elastic Stack. You will learn advanced cluster management techniques, best practices for capacity planning and scaling, tips for monitoring and alerting, considerations for going into production, and more. You will also dig into field and document modeling, fixing data with Painless scripting, cross-cluster search, pipeline aggregations, and more. After completing this course, you will be prepared to attempt the Elastic Certified Engineer exam.The course is delivered by a certified Elasticsearch engineer with real-life experience in various Cloud technologies. Experienced Elasticsearch professionals who need to expand their knowledge of Elasticsearch cluster management and application development. Complete the Elasticsearch Engineer I course, or possess equivalent Elasticsearch knowledge Technical requirements to attend the course Mac, Linux, or Windows Latest version of Chrome or Firefox (Safari is not 100% supported) Stable internet connection Due to virtual classroom JavaScript requirements, we recommend that you disable any ad-blockers and restart your browser before class. Elasticsearch Internals Take a deep dive into how Elasticsearch works, including the details of Apache Lucene, segments, doc values, and caching. Hands-on Lab   Monitoring and Alerting We discuss of monitoring options, including the Stats API, task monitoring, the cat API, the X-Pack Monitoring component, and guidelines for monitoring a cluster and setting up alerts. Hands-on Lab   From Dev to Production We explore items to consider when moving to production, including network setup, hardware requirements, JVM settings, and also a discussion on some of the common causes of poor query performance and how to fix them. Hands-on Lab