ElasticSearch Onsite Training Course

ElasticSearch Training - Onsite, Instructor-led

ElasticSearch, ELK, Kibana, FileBeats and Logstash

Training for DevOps, Architects and Developers

This ElasticSearch course teaches the basics of the #1 full text search solution.

The ElasticSearch database is supported by Amazon WebService via ElasticCache. ElasticSearch has become the go to stack for full text search and analytics. ElasticSearch transcends the role of a database as it is a full text search solution with analytics support.

ElasticSearch is fault tolerant, highly scalable full text search server.

This course provides a technical introduction to all the conceptual and practical areas needed to use the ElasticSearch Database successfully, and deploy to production. The course provides a solid foundation in the architecture and data model of the ElasticSearch NoSQL Search Database and how to work with it. It covers queries in detail, as well as important data representation techniques to optimize your usage of the database. It includes either in-depth coverage of the Java API for the ElasticSearch Database, Python or using from Node.js from AWS Lambda.

After taking this course, you will be ready to work with ElasticSearch in an informed and productive manner. You will gain a clear understanding of how ElasticSearch works, and be fully prepared to use it in production systems.

We provide more than just developer training. We provide the training to maximize your developer and DevOps expertise.

Why choose us and our ElasticSearch Course

We have successfully deployed and used the ElasticSearch database at large fortune 100s and very high traffic web properties.

We have been there and done that and understand when and where certain ElasticSearch features makes sense and how to avoid common pitfalls with ElasticSearch.

Our ElasticSearch course is taught by real-world AWS consultants who implement high-traffic, high-speed, microservices and tools for the AWS environment.

Don’t forget we also provide ElasticSearch consulting, and related consulting. We have no instructor on staff who is not also a seasoned developer.


”(The instructor) taught an onsite course at our office…. I highly recommend (the instructor). The training was thorough and the examples were non-trivial. … He was ready with answers to the most detailed of questions.” –Jack

“He’s an engaging instructor who is genuinely interested in his client’s results. He did a great job customizing our course content to meet our exact needs. A few months earlier we had another vendor teach a similar course without nearly the same positive results. “ –John

”(The instructor) knowledge of … technologies is both deep and wide. His training and mentoring skills are the best that I’ve come across. His passion and proficiency has been inspiring for me and many others in the development community.” –Tom

(The instructor) delivered what was hands-down the best technical training I’ve ever received. He also played a key role on a large project, and it was always a great pleasure to work with him. –Aaron

Being a consultant as well as an teacher, he speaks from experience and possesses a deep knowledge of his subject areas. Highly recommended. –Thomas

AWS Cassandra/Kafka and Cassandra/Kafka as a Service

Our company is setup to support tools like Cassandra, Kafka and ElasticSearch running in AWS EC2. We have deployed 100 million user microservices in AWS using NoSQL solutions, and implemented streaming at scale. We provide Cassandra, Kafka, ElasticSearch support, AMI images for Cassandra/Kafka, CloudFormation templates, and tools for collecting metrics and logs to support Cassandra and Kafka in AWS via CloudWatch. Supporting Cassandra, Kafka, cloud-native microservices, AWS Lambda and ElasticSearch in production in AWS, EC2, and S3 is what we do.

You can be assured that the person teaching the course is a battle-hardened expert. Contact us to book onsite training today. Call to book 1-415-758-1113.

Why ElasticSearch is so common and important

ELK (ElasticSearch, Logstash and Kibana) have become the cornerstone in managing systems with its ability to drill down into OS, systems, services and application logs. It allows you to not fly blind when debugging distributed systems. It is hard to imagine doing any sort of distributed system development (uServices, Cassandra, Kafka, etc.) without an ELK stack to aggregate the logs and make them searchable. ElasticSearch is the power, and the engine behind ELK.

Kibana has become a top analytics visualization tool. This tool is beloved by business analysts, data analysts and data scientists for understanding data. ElasticSearch is the power, and the engine behind Kibana.

ElasticSearch Course Information

Duration: 3 to 4 days

Labs: Minimum 50% hands-on labs


Reasonable Java experience, Python or AWS Lambda Node.js experience

Supported Platforms:

ElasticSearch running locally or in AWS. Accessing ElasticSearch from Java or AWS Lambda/Node.js.

Skills Gained:

  • Understand the motivation for non-relational data stores
  • Understand ElasticSearch at a high-level
  • Basic setup of ElasticSearch, and how to run ElasticSearch locally
  • Understand the ElasticSearch architecture
  • Understand and use data replication and eventual consistency with ElasticSearch
  • Learn the basics of the ElasticSearch data model, and how to create good data models
  • Perform queries
  • Perform aggregations
  • Use Kibana for analytics
  • Learn how to improve search results
  • Learn and use ElasticSearch API including the async API
  • Know the standard ElasticSearch data types
  • Understand and use primary keys, sort keys, and secondary indexes (global and local)
  • Use the basic ElasticSearch API to connect to and work with ElasticSearch
  • Use asynchronous API

Hands on and interactive

Students are encouraged to follow along in the Kibana developer tools to try out queries as the instructor goes through the material. The course is very hands-on and interactive. There are also plenty of hands-on labs.


Day 1

Session 1: Introduction to the ElasticSearch Database


  • The motivation for non-relational data stores
  • Why relational databases don’t support modern applications well
  • The need for search and a brief history of search
  • ElasticSearch Search at a high-level
  • ElasticSearch use cases : Analytics, Search, Flexible queries
  • ElasticSearch eco-system, ELK, Logstash, Beats, Kibana

Acquiring and Installing the ElasticSearch Database

  • Local Install of ElasticSearch and Kibana
  • Configuration Structure
  • Using the ElasticSearch from Kibana development tools


  • Configure, Start/Stop the ElasticSearch Database
  • Using Kibana to execute queries

Session 2: Overview of Architecture and Data Model

Basic ElasticSearch Database Architecture:

  • Then inverted index
  • Lucene internals
  • Indexes and Documents
  • Shards
  • Cluster Structure - Nodes
  • Data Replication - Replicas and synchronization
  • Pipelining and batching
  • Distributing documents across nodes

The ElasticSearch Data Model:

  • Data Model and ElasticSearch API Introduction
  • Key/Value access
  • Lists
  • Objects
  • Numeric types
  • Keywords
  • Text

Session 3: Using ElasticSearch

  • Creating an index
  • Adding documents - Adding Documents to an Index
  • Basic CRUD on a document - Get a documents by ID
  • Modifying - Overwrite a documents, Updating documents, Upserts
  • Get a whole and partial Documents
  • Batch processing - Performing Bulk Operations on Documents
  • Bulk Indexing of Documents from a JSON File
  • Importing test data with cURL
  • Deleting Documents and Indices

LABS: (Labs use ElasticSearch CLI/REPL) * Store, and retrieve Key/Value pairs using what we learned

Session 4: ElasticSearch Mapping

  • ElasticSearch mapping - schema of a document
  • What is Dynamic mapping?
  • Field data types
  • Adding a mappings to existing indices
  • Updating an existing mappings
  • Parameters of mappings (parameters, custom dates)
  • Adding multi-fields mappings

LABS: (Labs use ElasticSearch and Kibana) * Modify the default mapping of our sample index

Session 5: ElasticSearch Searching Introduction

  • The mechanics of search - How search works!
  • Understanding the Query context (scoring and relevance)
  • Understanding the Filter Context
  • Simple searches with query Params
  • Understanding source Filtering Document Contents
  • Performing basic Full Text Searches
  • Term Queries and the Boost Parameter
  • Understanding Relevance and the TF/IDF Algorithm
  • Pagination, Sorting, and Filtering
  • Join queries

LABS: (Labs use ElasticSearch and Kibana) * Perform some basic queries highlighting difference between query and filter contexts * Use pagination, sorting and filtering on queries * Perform a basic join query

Session 6: Term queries

  • Understanding ElasticSearch term level queries
  • Searching for a term and multiple terms
  • Searching for multiple terms
  • Working with range queries
  • Working with relative date ranges and date math
  • Matching documents with missing values
  • Matching based on prefixes
  • Using wildcard searches and regular expressions

LABS: (Labs use ElasticSearch and Kibana) * Perform some basic term queries

Session 7: Boolean logic queries

  • Using Boolean Logic with Queries
  • Compound queries
  • Using named queries for development
  • Understanding the match query

LABS: (Labs use ElasticSearch and Kibana) * Write some basic compound queries using boolean logic * Used named queries to debug a problem with a query

Session 8: Using Aggregations with ElasticSearch

  • Aggregations Types
  • Using Metric Aggregations
  • Cardinality Aggregation
  • Bucketing Aggregations - Introduction to bucket aggregations
  • Filter and Filters Bucketing Aggregations - Defining bucket rules with filters
  • Nested Aggregations and aggregating nested objects
  • Document count approximations
  • Range aggregations
  • Creating histograms

LABS: (Labs use ElasticSearch and Kibana) * Write some common metric queries * Use bucketing aggregations * Write a range query * Create a histogram

Session 9: Full Text query redux with and improving search results

  • Full text queries redux
  • Match query - flexible matching
  • Matching a whole phrase
  • Matching multiple fields using multi_match
  • Improving search
  • Searching with synonyms
  • Search Highlighting
  • Stemming redux
  • Proximity searches
  • Redux on relevance scoring
  • Relevance scoring with proximity
  • Fuzzy match query, fuzzy query

LABS: (Labs use ElasticSearch and Kibana) * Lab to reinforce some key concepts in this lesson

Session 10: ElasticSearch Admin

  • Monitoring ElasticSearch
  • Production deployment set up
  • Taking a snapshot
  • Backing up
  • Restoring from a snapshot
  • Admin tools
  • Determining the number of shards you need
  • Using new Indices to scale
  • Hardware Selection guidelines
  • Using X-Pack for Monitoring
  • Handling Failover and Rolling Restarts
  • Setting up and using Amazon Elasticsearch Service
  • (Optional) Integrating Logstash with Amazon ES

LABS: * Lab to reinforce some key concepts in this lesson

Day 3 and 4

Section 11 through 20

  • Call us for the specific details
  • We have custom API coverage for Java, Python and JavaScript
  • We repeat the labs we did in section 3 through 8 using the language/API of your choice
  • There are 10 labs

If you prefer to get a basic introduction to Kibana and/or Logstash, then let us know and we can substitute one or two days of programming with ElasticSearch with Basic Data analytics with Kibana.

Day 3 and 4 (Kibana Optional)

Kibana (Optional)

  • Kibana introduction
  • Using Kibana to discover
  • Using Kibana to visualize data introduction
  • Kibana and aggregations
  • Creating dashboards with Kibana

Kibana visualization Redux (Optional)

  • Line chart visualization
  • Data table visualization
  • Area chart visualization
  • Using Markdown
  • Pie chart and bar chart visualization
  • Other Kibana visualizations
  • Kibana plugins - heatmap, tagcloud
  • Other Kibana plugins

We also have the option of exploring FileBeats and Logstash.

Day 3 and 4 (Logstash and FileBeat Optional)

Logstash and FileBeats (Optional)

  • Logstash Introduction
  • Beats introduction
  • Installing and configuring Logstash
  • Using Kibana to visualize log data

Monitoring Linux Servers (Optional)

  • Installing and Configuring FileBeat
  • Working with MetricBeat for Linux
  • Creating a Linux Dashboards in Kibana

Application logging (Optional)

  • Setting up application logs
  • FileBeats or Java Logback

Working with Alerts (Optional)

  • Alerting with Watcher
  • Set up Watcher
  • Setting up Alerts

If there is a specific topic that you want to cover regarding ElasticSearch, let us know. We can customize the course based on your needs if given enough lead time, or combine material from this course with our others courses on Kinesis, AWS, Kafka and Cassandra.

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For more details on the subscription support or pricing please contact us or call ((415) 758-1113) or write info@cloudurable.com.