Elastic Berlin Meetup @ Zalando: October Edition

We're back with another meetup at Zalando!

Please make sure to provide your first name and last name as this will be required by security to enter the meetup.

Address: Zalando BHQ-X, Valeska-Gert-Straße 5, 10243 Berlin

Agenda:
18.00: Doors open
18.10: Execution in a Vectorized Query Engine
18.40: Break with pizza and drinks
19.00: Open source observability with OpenTelemetry and Elasticsearch
19.30: Evaluating Elasticsearch Nearest Neighbour Search for E-Commerce
20.00: Networking
20.30: Close

Talks:
Execution in a Vectorized Query Engine
ES|QL is a new piped query language for Elasticsearch. It supports writing composable queries and it features a multi-staged execution. Unlike the other languages supported by Elasticsearch, ES|QL doesn't transpile to Query DSL or use the internal search client: it's based on its own stack. This comes with a sophisticated query analysis and optimisation steps, as well as parallelisation and vectorisation. This talk will give an overview of the execution flow of a query and touch on a few key implementation aspects, following the query from its first syntactic analysis down to Lucene delegation followed by returning the results back to the user, all in a distributed environment.

Bogdan Pintea (Senior Software Engineer @ Elastic)

Open source observability with OpenTelemetry and Elasticsearch
Recognized by Gartner as a leading observability tool, Elasticsearch is not just log analytics. It has infrastructure monitoring, alerts, APM capabilities - and it's all open-source!

Now with the addition of OpenTelemetry, it's even easier to onboard your telemetry data in a standard and vendor-neutral way.
Join Andrzej in a technical session to discover the shortest path from zero to a fully functional open-source observability solution with the OTEK stack - OpenTelemetry, Elasticsearch and Kibana.

Andrzej Stencel - (Senior Software Engineer @ Elastic)

Evaluating Elasticsearch Nearest Neighbour Search for E-Commerce
Experiments to analyze the utility, efficiency and effectiveness of brute force k nearest neighbor and approximate nearest neighbor algorithms available in Elasticsearch to enable Zalando's search, browse and fashion assistant capabilities.

Girish Chandrasheka (Zalando)