Data Driven Dashboards with Kibana and Elasticsearch by Philipp Krenn

From the trenches: what does it really take to scale up a large Elastic security log deployment? Elasticsearch for enterprise security log storage & management is a hot topic today. Specular gains in performance, functionality and cost are ready for harvest. But what exactly does it take to create a large Elastic log storage infrastructure? This talk will present war stories related to at 150,000 events per second Elastic log storage implementation with 2 month retention built at a large commercial client.

Supporting employees in a work from a home environment can be challenging. Do they have access to these systems? Can they locate the documents they need? This would be easier if documents are centrally located. In most organizations, documents can live in services like Dropbox, Goole Drive, and or Github. In this virtual meetup, I will show you how to create a search box between these different services and finally solve the question.. "Where did that document go?"

Ask Me Anything hour with Elastic Developer Advocates

There are various publicly available data-sources that we may leverage to visualize the COVID-19 pandemic. We will use the materials created by SiScale (https://www.siscale.com/) as they have composed a rather elegant means of ingesting COVID-19 data. This document is designed to be an instructional guide on how to implement this solution locally or with the Elastic Cloud. We will first configure the necessary components, ingest the data source, then show how to create the additional Machine Learning jobs as well as creating a Canvas dashboard.

Let's look at the good parts of logging:

• How can you bring logging to production quickly?
• How does this work with Spring Boot in as a practical example?
• Do you want to add tracing and make the most of the combination?
• How do you manage the data that you are collecting?

Evolving With Elastic Ray Myers and Eric Bjerstedt, GetSet Learning So you’ve got a search index - now what? What benefits will that investment provide as your product grows? We’ll explore the timeline of Elasticsearch adoption at an Education Tech startup as told by the heads of Engineering and Product and see how those teams juggled trade-offs between business value and technical capabilities leading to solutions neither side would have come up with on their own.

About Elastic - Search and Analytics; Examining OpenData with a Search Index.

Elasticsearch is the world's most popular open source search engine. Kubernetes (k8s) is the popular container orchestration engine giving developers the flexibility to run all sorts of workloads easily. Elastic launched Elasticsearch k8s operator sometime ago. With this, one can not only run Elasticsearch on k8s but also can launch other Elastic Stack projects like APM Server, help run rolling upgrades, manage data etc. This talk is a demo of all latest features.

This talk starts with the significance of search problem and its origin in history how it has been an integral part of our daily lives. Also, basics of full text search will be discussed along with the anatomy of a full text search engine by taking Elastic Search as an example. Speaker: Muhammad Junaid Muzammil is a Software Engineer with over 9 years of professional experience, along with over 4 years of experience working with Elasticsearch. He is also an Elastic Certified Engineer and one of our active Elastic user group organizers, based in Pakistan, Karachi.