Kibana Deep Dive

It's the grand tour of new visualizations and exciting updates in Kibana, including time series visual builder, heatmaps, Timelion, tag clouds, Watcher UI, and cluster alerts. Plus, a look at what's to come in 6.x.

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Machine Learning Deep Dive

GA'ed in 5.5, machine learning can uncover insights from your data automatically. This session walks you through using the Elastic Stack to ingest, enrich, visualize, analyze, and alert on NGINX logs to detect and eventually predict anomalies in your data.

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Opening Keynote

Get the update from Shay on where the Elastic Stack is headed, from logging to metrics to the APM solution that's brewing.

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Smart Tracing at Deutsche Telekom - Revealing the secrets behind modern networks with the Elastic Stack

Data drives our modern world but most data is never seen and yet its implications can be wide ranging. Using the Elastic Stack and its data analytics techniques, Smart Tracing works like an x-ray to reveal what sits behind modern networks based on network data. It uses the hidden data which network equipment and devices use to communicate with each other to create new insights into performance issues, security threats and network faults.

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Using Elasticsearch to drive car2go's realtime business insights from their connected cars

Car2go is an always-on business offering mobility service with cars to customers living in urban areas. Customers and cars constitute an IoT service generating data which must be processed and analyzed in real-time. E.g. vehicle connectivity and condition, position data, reservation and payment, registration and validation. Elasticsearch was introduced to all development teams as an offering, and as a result high quality data analysis can be generated based on systems inside status to all parts of the organization. Using DevOps methods each team is able to implement, modify and visualize data effectively. This gives a fast understanding of capacity, errors and business opportunities in real-time.

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Managing Elasticsearch Clusters with Elastic Cloud Enterprise

Learn how to easily deploy and manage secure Elasticsearch clusters at scale and on the infrastructure of your choice using Elastic Cloud Enterprise.

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Distributed Logging and Monitoring at Volkswagen using the Elastic Stack

To be an independent cloud provider and enforce additional security guidelines, Volkswagen developed their internal central logging and monitoring solution. The solution is based on Microservices implemented in Java as a log endpoint, Kafka for the processing pipeline, Elasticsearch for log storage and Kibana for visualization. In this talk we’ll explain the rationale around the decision to build our own service, the architecture and describe our experiences with the platform.

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Ingest and the Elastic Stack

Walk through all things ingest for Logstash 5.x, from dead letter and persistent queues to the Grok Debugger and new monitoring APIs. Then get caught up on new lightweight data shipper additions like Heartbeat and Metricbeat, as well as new modules that simplify the getting started process.

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Elasticsearch Deep Dive

Cross-cluster search, ingest node, rollover API, shrink API, field collapsing, unified highlighter . . . there's lots to love in Elasticsearch these days. Get up to speed on all things 5.x and see how 6.x will address pain points around scale, upgrading, recovery, and sparse data and disk usage.

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VELTRA: 日・英・中、問い合わせ仕分け業務の自動化と、CS 戦略分析基盤を Elastic Stackで実現 (Japanese)

専門的な地域知識と、多言語にたけたトラベルコンサルタントのパフォーマンスを最大限に発揮できるように、 VELTRA カスタマーサービスでは、業務の自動化や効率化に力を入れています。日・英・中、自然言語と言う非定型データを多く取り扱うため、今まで解決できなかった課題も Elastic Stack を活用することで解決しています。

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決済サービスの監視を支えるElastic Stack (Japanese)

膨大な取引データ、サービス提供状態の可視化やElastic Machine Learningによる異常検知の仕組化など、年間取扱額2兆円を超える決済システムを支えるElastic活用事例をお話しします。

また、システムリソース以外のビジネスデータの可視化についても取り上げます。

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Tokyo 2017: Elastic Cloud Deep Dive (Japanese)

Elastic Cloud Enterpriseをお好きな環境で運用し、セキュアにElasticsearchクラスターを展開・管理する方法をご紹介します。

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Tokyo 2017: Machine Learning Deep Dive

5.5でリリースされたMachine Learningは時系列データの異常検知を可能にしました。本セッションでは、NGINXログの投入から、情報付加、可視化、分析、そして異常の予測まで、Elastic Stackを利用した手順をご覧いただきます。

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15分でお届けするElastic Stack on Azure設計・構築ノウハウ (Japanese)

Azureはマイクロソフトが提供するオープンで柔軟な、エンタープライズレベルのクラウドプラットフォームです。ここではAzure特有のインフラコンポーネントにフォーカスしてElastic Stack on Azureの設計・構築ノウハウをご紹介します。

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Tokyo 2017: Kibana Deep Dive (Japanese)

誰にでも使いやすくなったKibana 6.0のUIのヒミツ、直近のリリースで追加された美しいチャート、Time-series Visual Builder、CSVでのダウンロードなどX-Packの導入で利用が可能になる数々の新機能を、デモを交えて紹介します。Kibanaのエキスパートには新鮮で、これから始める方にもわかりやく説明します。

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Tokyo 2017: Ingest and the Elastic Stack

Logstash 5.xのデータ投入についてご紹介します。また、軽量データシッパーであるBeatsに加わったHeartbeatやMetricbeatについてもご説明します。

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Tokyo 2017: Elasticsearch Deep Dive (Japanese)

Elasticsearch 5.xでどのような機能や変更が行われたのか。アップグレードやスケール、リカバリ、ディスク使用量などの懸念事項について、6.xではどのように進化していくのかを解説します。

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Tokyo 2017: Opening Keynote

CEOであるShay Banonが、Elastic Stackのロードマップや、ログ・メトリック分析からAPMソリューションまで、詳しく紹介します。

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Seoul 2017: Opening Keynote

Get the update from Shay on where the Elastic Stack is headed, from logging to metrics to the APM solution that's brewing.

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Seoul 2017: Elasticsearch Deep Dive (Korean)

Cross-cluster search, ingest node, rollover API, shrink API, field collapsing, unified highlighter . . . there's lots to love in Elasticsearch these days. Get up to speed on 5.x and see how 6.x will address pain points around scale, upgrading, recovery, and sparse data and disk usage.

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