Deployment in the Enterprise Beats
Elasticsearch
Custom UI FILEBEAT
WINGLOGBEAT
HEARTBEAT
METRICBEAT
Master (3)
Ingest (X)
Logstash
Coordinating (X) PACKETBEAT
Elasticsearch Clients
AUDITBEAT
Data – Hot (X) Kafka
Kibana Data – Warm (X) Data store
Web APIs
Redis
Workers (2+)
Alerting (X)
Messaging Queue
Social
Machine Learning (2+)
Sensors
LDAP
ES-Hadoop
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AD
Authentication
SSO
Notification
Slide 4
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https://www.elastic.co/fr/subscriptions
Slide 5
Agenda • Elasticsearch overview • Workshop 0: getting started • Workshop 1: let’s index some documents • Workshop 2: let’s search them • Workshop 3: let’s pull some analytics • Workshop 4: let’s add a powerful live UI on top
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Slide 6
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think document! • Change your mindset: ‒ Forget SQL! ‒ Index what you want to find
• A document ‒ A JSON object ‒ Core field types (string, numbers, booleans, dates) ‒ Complex field types (arrays, objects) ‒ Additional field types (dates, geo points, geo shapes)
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start • run docker-compose up
• open Kibana open http://0.0.0.0:5601/
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Slide 13
workshop 1 we index persons
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workshop 1: index some documents • Load demo-console.txt file in Kibana dev console
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https://gist.github.com/dadoonet/f3c67bebf2cf604df02f78ac2cb2fbde
Slide 15
workshop 1: 500 000 persons • use injector script java -jar injector-7.0.jar —debug —nb 500000 • see effect with _cat API GET _cat/indices/person?v
https://ela.st/injector 15