Advanced Elasticsearch and Elastic Stack Course

Search, analyze, and visualize big data on a cluster with Elasticsearch, Logstash, Beats, Kibana, and more.

Elasticsearch 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.

We’ll cover setting up search indices on an Elasticsearch 6 and querying that data in many different ways. It’s not just theory, every lesson has hands-on examples where we’ll practice each skill.

We’ll cover, in depth, the importing data into 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 using Logstash and Filebeat – commonly referred to as the “ELK Stack” (Elasticsearch / Logstash / Kibana) or the “Elastic Stack”.

We’ll bucket and analyze data using Elasticsearch, and visualize it using the Elastic Stack’s web UI, Kibana.

You’ll learn how to manage operations on 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.

Any engineer who decided to add Elasticsearch to their toolbox for searching and analyzing big data sets.

  • You should familiar with web services and REST
  • Some familiarity with Linux will be helpful
  • Experience with JSON-formatted data will help

Installing and Understanding Elasticsearch

  • Introduction, and Installing Elasticsearch
  • Elasticsearch Overview
  • Intro to HTTP and RESTfull API’s
  • Elasticsearch basics
  • Elasticsearch Architecture

Mapping and Indexing Data

  • Connecting to a cluster
  • Loading a sample data
  • Insert, Update, and Delete functions
  • Using Analyzers and Tokenizers
  • Data Modeling with Elasticsearch

Searching with Elasticsearch

  • Using Query-String Search
  • Using JSON Search
  • Full-Text vs. Phrase Search
  • Pagination
  • Sorting
  • Using Filters
  • Fuzzy Queries
  • Partial Matching
  • N-Grams, and Search as you Type

Importing Data into Index

  • Import Data from Scripts
  • Logstash Overview
  • Installing Logstash
  • Import Logs with Logstash
  • Importing Data from MySQL using Logstash
  • Importing Data from AWS S3 using Logstash
  • Integrating Kafka with Elasticsearch
  • Integrating Spark and Hadoop with Elasticsearch


  • Buckets and Metrics
  • Histograms
  • Aggregating Time Series Data
  • Nested Aggregations

Using Kibana

  • Installing Kibana
  • Analyzing sample data with Kibana

Analyzing Log Data with Elastic Stack

  • The ELK Stack and Elastic Stack
  • Install, Configure, and Use Filebeat
  • Analyzing Server Logs with Kibana

Elasticsearch Operations

  • How Many Shards Should I Use?
  • Scaling with New Indices
  • Choosing Your Hardware
  • Heap Sizing
  • Monitoring with X-Pack
  • Practicing Failover
  • Snapshots
  • Rolling Restarts
פיליפ גולדמן הינו אחד המומחים המובילים בנאיה טכנולוגיות בתחומי פיתוח, Big Data, Devops. פיליפ מעורב בפרויקטים מורכבים ומתקדמים, בארגונים עתירי טכנולוגיות. לפיליפ למעלה מ-10 שנות נסיון בתחום פיתוח והובלת צוותי פיתוח. בנאיה קולג' פיליפ מעביר קורסים מתקדמים בתחומי ההתמחות ובונה חומרי לימוד מותאמים לצרכים של הלקוחות ולסביבות הפיתוח שלהם.
  • על פי דרישה מועד פתיחה
  • 9:00-16:30daysימים ושעות
  • 32academic hours שעות אקדמיות
  • מתקדםcourse levelרמת הקורס
  • אנגליתlanguageשפת הדרכה
  • לבדיקת התאמה לקורס
  • [current_url]

    השאירו פרטים ונחזור אליכם בהקדם!