6 décembre 2016 Nouveautés

First Wave of Elastic{ON}17 Sessions Revealed

Par Amy White

Elastic{ON}, our annual user conference, is one of the highlights for us each year. The conference is mainly about bringing a community of developers together who are utilizing the Elastic Stack to achieve various goals . . . it’s about all of us being on this journey separately, yet together, with the Elastic Stack being what unites us.

This is why we view the sessions at Elastic{ON} as a way to share stories.

Our engineers get to share everything they’ve been working on for the past year, as well as where they’re thinking of going in the coming year. They want to hear your reactions and thoughts to their plans. They want your ideas on how we should be shaping the direction we’re going.

Our users and customers get to share the journey they’ve each been on while using Elasticsearch, Logstash, Beats, and Kibana to do things we never would have dreamed of. We get ideas and inspiration when hearing these stories as to how we should continue to develop our Stack, so we can best help them accomplish their goals. 

Because when it comes down to it, it's really about creating something wonderful – together.

Today, we’re pleased to unveil the initial agenda for Elastic{ON}17. We expect to finalize the agenda with 30+ more sessions in January, but there is so much goodness in there now that we wanted to highlight just a few talks we’re particularly jazzed about: 

Machine Learning Comes to the Elastic Stack

With Prelert joining us in September 2016, we started down the path to more tightly integrate their unsupervised machine learning engine into the Elastic Stack. At Elastic{ON}17, you can hear from the creators of Prelert about how it works, what problems it can solve for your business, and how it can proactively detect and alert you to anomalies into the behavior and performance of your business and systems. Afterwards, you can find them at the Ask Me Anything booth – which is open all day, every day of the conference – to pick their brains about what you heard.

Walgreens’ Journey to Creating an End-to-End Search Platform

Walgreens is one of the the largest drugstore chains in the United States, interacting with 8 million customers each day. Somewhere along the way, their Endeca-powered search platform couldn’t keep up. Sound familiar? We thought it might, which is why we invited Syed Ali, a Senior Technical Architect at Walgreens, to share the story of how they migrated to Elasticsearch for a complete search platform as a service, which led them to also set up a log management and analysis cluster, as well as utilize Kibana to view technical and business metrics. You’ll hear about things like capacity planning, cluster setup and architecture, data ingestion using Logstash and a bulk API framework, relevancy tuning, performance optimization, query analysis using Packetbeat, how they handle monitoring and operations, and, of course, challenges and resolutions.

The Queries Behind Uber Marketplace’s Core Data System

I think we’ve all wondered how Uber utilizes data to manage dynamic pricing and supply/demand/trips, which is why we’re stoked to have Jae and Isaac give a glimpse into Uber’s Elasticsearch cluster that handles 1000 QPS at peak. They plan to map out their data flow – from Kafka and Samza to Spark and ES-Hadoop, give some insights into how they handle their surge multiplier calculation, as well as share some general tips and tricks they’ve learned along the way – such as how they’re solving many data modeling challenges with Elasticsearch partial document update with dynamic scripting and lightweight transaction concepts. 

Walmart Will Share How Bananas Impact Fraud Detection

OK, maybe not exactly. But thanks to the Elastic Stack, they know that they sell 156 of them a second (banana bread, anyone?). In this talk, you’ll learn how what started as an engineering hack to prove 'the banana myth’ is now a fully-operational self-service analytics platform used to detect fraud and gain insights into customer purchasing patterns, as well as track store performance metrics.

Is Time-Series Your Jam? Learn How Workday Built Its Metrics Pipeline

With the release of Elasticsearch 5.0, we deepened our support for numbers to better help with the time-series use cases we’re starting to see all over our user base. Workday, which provides enterprise cloud applications for finance and human resources to more than 1,000 organizations worldwide, is one of them. As a SaaS provider, application performance is extremely important to their business. After struggling to find a traditional database that could ingest large volumes of application metrics at an acceptable rate, they noticed that each of their already existing Elastic Stack deployments for other use cases at the company were able to process over 1 billion log events a week without issues. Problem solved. In this talk, you’ll learn how they used Logstash and Elasticsearch to build a metrics processing pipeline that allows them to monitor their products’ operational stability as well as analyze usage patterns to facilitate better product decisions. 

See a Live Demo of Elastic Cloud Enterprise

If you’re managing multiple Elasticsearch clusters, hopefully by now you’ve heard about Elastic Cloud Enterprise, which allows you to monitor, manage, and provision one to thousands of Elasticsearch clusters from a central place, on the infrastructures and environments of your choosing. After spending most of 2016 in private beta, we recently released the first public version of the product (go ahead and try it out!), and at Elastic{ON}17, we'll give you a tour of Elastic Cloud Enterprise’s ins and outs, as well as updates on the next major milestones for the product. 

Learn How Sprint’s IT Department Evolved to Be More Than IT

IT can sometimes be viewed as a cost center whose sole job is to make sure there's enough hardware in place to support the business – which isn’t always the best feeling. We were inspired when we heard Steffen’s story about how he and his team transformed the IT department into the business engine at Sprint by allowing the vast amount of data they generate to be utilized by various business units. We’re talking ingesting nearly 3 billion records a day into the Elastic Stack, making 50 TB of real-time data usable by their marketing team to monitor the performance and user experience of Sprint.com, their retail operations group to monitor the performance of their demo phones, their wholesale sales unit to understand the hundreds of B2B relationships they maintain, and much, much more. 

Those are just a few of the sessions you can find in the initial agenda we published this week – we hope you share in our excitement! 

You can view the rest of the sessions here, and yes, we’ll be adding 30+ more in January when we finalize the agenda – but don’t wait until then to register! Holiday pricing ($300 discount) ends in the new year on January 6, so make sure you lock in your savings now before (hopefully) taking some time off to spend time with your friends and family over the holidays. 

We hope to see you there – and if there's anything in particular you want to see on the agenda, give us a shout at elasticon@elastic.co (or Tweet @elastic with #ElasticON).