Operations | Monitoring | ITSM | DevOps | Cloud

Canvas is data visualization and presentation tool that sits within Kibana. It allows us to pull live data directly from Elasticsearch and combine it with colours, images and text in order to create dynamic and visually appealing presentations. This talk will cover the basics of building your first presentation based on the live data from Elasticsearch. If you enjoy immersing yourself in the creative process while applying your technical skills, you should join us for this talk.

Hello! This session will be delivered virtually by Tamara Rosini and Lutf Ur Rehman, Education Engineers at Elastic. They will guide us through the new Elastic Observability Engineer course while providing tips on how to structure data properly as an observability best practice. Properly parsing and structuring your data is an important first step in building an efficient and effective observability solution using the Elastic Stack. Effectively indexing and structuring data into Elasticsearch is critical for establishing efficient search criteria and effective results.

In this virtual meetup, we will go over step-by-step how we have replaced our music platform's search capabilities with Elasticsearch achieving better and personalized results based on user's previous music taste.

Practitioners the field of data visualizations often talk about 2 types of visualizations: exploratory vs explanatory. To quote Google definitions, “Exploratory data visualizations (EDVs) are the type of visualizations you assemble when you do not have a clue about what information lies within your data. Nov 19, 2018” Explanatory visualization, by contrast, is defined as “what happens when you have something specific you want to show an audience” (Storytelling with data blog, April 2014)

Building a web application to solve a business problem is easy in today's world. But, how about creating an experience that lets your user spend more time on the service. To do that essentially, we need to equip the application with quintessential features like search. Most of the websites like eCommerce, Food Delivery, Social media rely on search. Search is omnipresent and one can't ignore the users searching for something on your website.

Introducing Elastic Workplace Search: Personalized, unified search across all of your enterprise content, with ready-made connectors for popular cloud sources.

Introducing the new alerting framework for the Elastic Stack bringing alert functionality directly into SIEM, APM, Uptime, and Metrics. The new alerting framework is built from the ground up and designed to offer data-driven triggers that let you do everything from send an email, to automatic Slack notifications, to even integrate with platforms like PagerDuty to initiate escalations.

Distributed tracing is great — it helps you identify (micro)services within complex architectures having issues interfering with user experience, such as high latency or errors. But once a problematic service is identified, it can be difficult to find out which methods are to blame for the slowdown. In this presentation, Felix Barnsteiner (one of the core developers of the APM Java Agent) will show you the different ways to get method-level insight into your application. Specifically, we’ll have a look at the newly added support for profiler-inferred spans that is based on a sampling profiler.

Your Kubernetes app is down. Your users start ranting on Twitter. Your boss is standing right behind you. What do you do? We are using the Elastic Stack in this demo with a special focus on its Kubernetes integration with metadata enrichment and autodiscovery in combination with APM / tracing, metrics, logs, and health checks.

At ThousandEyes and the Endpoint Agent, we have a track record of using Elasticsearch as a time-series database for the metrics that we collect from our agents. I will be presenting how we decided to use Elasticsearch as a Time Series Database (TSDB), and how we got buy-in from stakeholders. Stathis spent several years in Athens, Greece, as a Software Engineer before moving to London. Enjoys working with large distributed systems using technologies like Elasticsearch, Kafka, Java, Kotlin. Wants to build his own tech when he grows up.