Visão Geral

Curso Elasticsearch Engineer II Domine as habilidades de gerenciamento de um cluster, incluindo como configurar filtragem de fragmentos, reconhecimento de alocação de fragmentos e reconhecimento forçado. Por meio do treinamento Elasticsearch Engineer II, aprenda sobre como projetar para escala, escalar com réplicas, escalar com índices, casos de uso de planejamento de capacidade e trabalhar com dados baseados em tempo.

Objetivo

No final Curso Elasticsearch Engineer II, você também se aprofundará na modelagem de campo e documento, corrigindo dados com script indolor, pesquisa entre clusters, agregações de pipeline e muito mais.

Assuntos abordados

• Modelagem de campo
• Dados de correção
• Pesquisa Avançada e Agregações
• Gerenciamento de Cluster
• Planejamento de capacidade
• Internos do Elasticsearch
• Modelagem de documentos
• Monitoramento e Alerta
• Passando de Dev para Produção

Publico Alvo

• Profissionais experientes do Elasticsearch que precisam expandir seus conhecimentos sobre gerenciamento de cluster Elasticsearch e desenvolvimento de aplicativos.

Pre-Requisitos

• Conclua o curso Elasticsearch Engineer I ou possua conhecimento equivalente do Elasticsearch

Materiais

Conteúdo Programatico

Field Modeling

1. Learn how to design and model the fields in your documents, including discussions on granular fields, range types, dealing with large field cardinality, and designing for proximity matching.
2. Hands-on Lab

Fixing Data

1. Learn how to use the new Painless scripting language in Elasticsearch and discuss use cases for scripting, including the Reindex, Update By Query and Delete By Query APIs.
2. Hands-on Lab

Document Modeling

1. We discuss denormalizing documents, working with nested fields, and using the join field for parent/child relationships
2. Hands-on Lab

Advanced Search and Aggregations

1. Learn some of the advanced search and aggregation techniques, including cross cluster search and pipeline aggregations.
2. Hands-on Lab

Cluster Management

1. We walk through the details of managing a cluster, including how to configure shard filtering, shard allocation awareness and forced awareness.
2. Hands-on Lab

Capacity Planning

1. Learn about designing for scale, scaling with replicas, scaling with Indices, capacity planning use cases, and working with time-based data.
2. Hands-on Lab

 Elasticsearch Internals

1. Take a deep dive into how Elasticsearch works, including the details of Apache Lucene, segments, doc values, and caching.
2. Hands-on Lab

Monitoring and Alerting

1. 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.
2. Hands-on Lab

 From Dev to Production

1. 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.
2. Hands-on Lab