EncartaLabs

ELK Stack (Elastic Search)

( Duration: 8 Days )

To master the ELK Stack concepts, a candidate must-have the basic understanding of the following:

  • SQL
  • JSON Data Format
  • Restful API

  • Full Stack Technical Architects
  • Big Data Analytics Engineers - Elastic Search
  • System Log Analysts
  • Web Analysts
  • Web Administrators

COURSE AGENDA

1

Introduction to ELK Stack

  • An overview of ELK Stack
  • Why choose ELK?
  • Architecture of ELK
  • An explanation of Elastic Search
  • Logstash and Kibana
2

Introduction to Logstash

  • A brief explanation of Logstash
  • Installation process
  • Log file configuration
  • Stashing process of the first event
  • Analyzing logs with Logstash
  • Uses of input and output
  • Plugins
  • Execution model
3

Introduction to Elastic Search

  • Then inverted index
  • Lucene internals
  • Indexes and Documents
  • Shards
  • Cluster Structure - Nodes
  • Data Replication - Replicas and synchronization
  • Pipelining and batching
  • Distributing documents across nodes
  • An overview of Elastic Search
  • Installation and running process
4

The ElasticSearch Data Model

  • Data Model and ElasticSearch API Introduction
  • Key/Value access
  • Lists
  • Objects
  • Numeric types
  • Keywords
  • Text
5

Indexing and Searching in Depth

  • 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
  • Organized Search
  • Full-text Search
  • Intricate Search
  • Phrase Search
  • Underlining the Search
  • Multi-field Search
  • Proximity Matching
  • Partial Matching
6

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
7

Dealing with Human Languages

  • An introduction to various human languages
  • Identifying Words
  • Controlling Tokens
  • Decreasing Words to their actual Root Form
  • Stop words: Performance versus Precision
  • Synonyms
  • Typographical Errors and Spelling Mistakes
8

Aggregation

  • An insight into concepts
  • A brief introduction to Aggregation
  • Analysis process
  • Filtering Process of the Aggregations and Queries
  • Sorting Multivalue Loads
  • Expected Aggregation
  • Doc Values and Field Data
  • 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
9

Boolean logic queries

  • Using Boolean Logic with Queries
  • Compound queries
  • Using named queries for development
  • Understanding the match query
10

Introduction to Data Modeling

  • Elastic Search versus RDBMS
  • Relationships handling
  • Nested objects
  • Scale Designing
11

Geo-locations

  • Major Geo Points
  • Geo Hashes
  • Geo Aggregations
  • Geo Shapes
12

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
13

Logstash and FileBeats

  • Logstash Introduction
  • Beats introduction
  • Installing and configuring Logstash
  • Using Kibana to visualize log data
14

Application logging

  • Setting up application logs
  • FileBeats or Java Logback
15

Working with Alerts

  • Alerting with Watcher
  • Set up Watcher
  • Setting up Alerts
16

Introduction to Kibana

  • An overview of Kibana
  • Installation process of Kibana
  • Sample data loading process
  • Discovering the saved data
  • Visualization of the data
  • Working with the Dashboard
17

Kibana

  • Kibana introduction
  • Using Kibana to discover
  • Using Kibana to visualize data introduction
  • Kibana and aggregations
  • Creating dashboards with Kibana
18

Kibana visualization Redux

  • 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
19

Discovering the Data in Depth and Dashboard Analysis

  • Set-up of Time Filter
  • Searching of the saved data
  • Filtering by the Field
  • Viewing the document data
  • Viewing the document context
  • Viewing the field statistics
  • Data visualization
  • Dashboard analysis
  • Exploring the live data with the ELK Stack

Encarta Labs Advantage

  • One Stop Corporate Training Solution Providers for over 3,500 Modules on a variety of subjects
  • All courses are delivered by Industry Veterans
  • Get jumpstarted from newbie to production ready in a matter of few days
  • Trained more than 20,000 corporate candidates across india and abroad
  • All our trainings are conducted in workshop mode with more focus on hands On

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