Video of the presentation is available here: https://youtu.be/L6EMnvALYtU Talk: Elasticsearch for Business Intelligence and Application Insights Speaker: Sean Donnelly Elasticsearch is a distributed, RESTful search and analytics engine capable of solving a growing number of use cases. In this talk, I’ll discuss the fundamentals of storage and retrieval in Elasticsearch, why we decided to use it for search in our applications, and how you can also leverage it for both business intelligence and application insights.

1. Introduction to Elasticsearch for
Business Intelligence and
Application Insights
Presented by Sean Donnelly
at Data Works MD – May 29th 2019

2. @DonSeannelly
http://donseannelly.com
https://github.com/donseannelly
Sean Donnelly
Software Architect at Cyber4All
https://clark.centerCLARK
Cyber4All https://towson.edu/cyber4all

3. Outline
• What we will cover
• Introduction to Elasticsearch
• Fundamentals of Storage and Retrieval in Elasticsearch
• Why we are using it at CLARK
• The Elastic Stack
• Use Beyond Search
• What we will not cover
• Clusters, Nodes, Scaling, Sharding and other nitty-gritty details for getting to
know Elasticsearch
• Details on standing up the Elastic Stack

4. What is Elasticsearch?
RESTful search and analytics engine

5. What does it do?
• Uses Lucene indices under the hood
• Provides built-in tokenizers and analyzers
• Provides a score for the relevancy of each result to the query
• Provides binary matching via filters
• Supports pagination out of the box

6. PUT meetups/_doc/1
{
”name" : ”Data Works MD",
"date" : "2019-05-29T18:30:00"
}
Indexing a Document

7. Getting a Document
GET meetups/_doc/1
{
"_index" : ”meetups",
"_type" : "_doc",
"_id" : ”1",
"_version" : 1,
"_seq_no" : 10,
"_primary_term" : 1,
"found": true,
"_source" : {
”name" : ”Data Works MD",
"date" : "2019-05-29T18:30:00”
}
}

8. Searching for Documents
GET meetups/_search?q=name:Data Works MD
…
"hits": {
"total" : { "value": 1, "relation": "eq" },
"max_score": 1.3862944,
"hits" : [ {
"_index" : ”meetups",
"_type" : "_doc",
"_id" : ”1",
"_score" : 1.3862944,
"_source" : {
”name" : ”Data Works MD",
"date" : "2019-05-29T18:30:00”
}
} ]
}

9. Elasticsearch at CLARK
• Goals for search:
• Fast
• Full text
• Word stemming, stop words, fuzziness
• We already had documents formatted in
MongoDB
• Our searchable data is read-only in the
application

10. What it looks
like

11. Ingest
Store, Search, Analyze
Visualize

12. Ingest
Store, Search, Analyze
Visualize
Custom
Self Hosted Hosting

13. Key Use Cases
• Application Search
• Application Performance Monitoring
• have our response times slowed significantly?
• Logging
• explore the logs that we rarely (never) read
• Machine Learning
• Alert me if there is an unusual increase in abandoned shopping carts
• Alert me if there is an unusual change in HTTP status codes for a resource

14. Thanks!