This talk assumes that you know the basics of full-text search. We will explore how to work with Elasticsearch, what the available features are, and how to scale it:

* How data is stored and how to query Elasticsearch.
* How the score of a search result is calculated.
* How to handle languages, search for terms and phrases, run boolean queries, add suggestions, work with ngrams, and more.
* How to scale it.

We will run all the queries live and explore the possibilities of Elasticsearch.

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How does Elasticsearch work in a resilient and performant way?

This talk is a deep dive into its internals:
* What are the different node types?
* How is the master node selected?
* How are indexes spread over shards and how are they allocated?
* What is the replication protocol?
* How is data actually written and queried?
* How are node failures and added nodes handled?
* How do snapshots work in the background?

While we will focus on the current implementation, we will also dedicate some time to mistakes of the past. What has gone wrong and how did we fix it.

This talk gives an in-depth overview of distributed systems and their implementation in Elasticsearch.

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How to use the Elastic Stack (previously called ELK Stack) to monitor logs is widely known. But it can also give you a complete picture of your PostgreSQL installation:

* System metrics: Keep track of network traffic and system load.
* Logs: Collect and parse PostgreSQL logs.
* PostgreSQL metrics: Gather the most relevant attributes with the dedicated Metricbeat module.
* Queries: Monitor your queries on the wire without instrumenting PostgreSQL with Packetbeat.

And we will do all of that live since it is so easy and much more interactive that way.

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