Talks

Introduction Serverless architectures take on-demand tasks to the next level with event-driven scheduling of workloads. Elastic Observability gives you the same insights into your serverless activities as the rest of your environment. Gather logs and metrics from your serverless invocations and tie them together with traces from your serverless functions. For example Identify AWS Lambda latency issues, cold starts, and other invocation issues. Logs are collected with the rest of your telemetry data, so you can look at all your data in context, in one place. ...

Introduction In today’s data-driven world, just having a search engine is not enough; the key is making it smart. Enter Elasticsearch Relevance Engine (ESRE) augmented with Retrieval Augmented Generation (RAG), a powerful solution that marries Elasticsearch’s superior search capabilities with Large Language Models (LLMs) like ChatGPT for precise, contextual querying over proprietary datasets. This session is a hands-on guide that will show you how to amplify the power of Elasticsearch with advanced LLMs. ...

Introduction In this gist we will quickly spin a sample Kubernetes cluster and deploying the nginx pod. Additionally, we will implement monitoring using Elastic. Setup K8s cluster Cluster architecture 3 Node cluster Machine - Centos7, 4GB RAM kube1.local - Control plane node kube2.local - worker node kube3.local - worker node Here I am setting hostname kube1.local, kube2.local, kube3.local. Login into all of the servers and perform below command on all three nodes. ...

Introduction ES|QL is a new query language for Elasticsearch. It is the unified language for all kinds of use cases like simple queries, aggregations, performing correlations, finding logs, etc. It provides simple easy syntax to perform complex queries. If you come from SQL background, You going to find this very handy. It is a piped separated langugage with a combination of source commands and process commands. The Elasticsearch Query Language (ES|QL) makes use of “pipes” (|) to manipulate and transform data in a step-by-step fashion. This means output of the first step will go as an input for second step. ...

Introduction Search is not just traditional TF/IDF any more but the current trend of machine learning and models has opened another dimension for search. This talk gives an overview of: Classic search and its limitations. What is a model and how can you use it. How to use vector search or hybrid search in Elasticsearch. Where OpenAI’s ChatGPT or similar LLMs come into play to with Elastic. Check how to leverage Leverage ChatGPT with Elasticsearch. ...