LINE のUI自動テスト事例
大園 博昭(LINE Fukuoka 開発室 テスト自動化エンジニア)
LINE Developer Meetup in Tokyo #39 Testing & Engineering
での発表資料です
https://line.connpass.com/event/91423/
LINE のUI自動テスト事例
大園 博昭(LINE Fukuoka 開発室 テスト自動化エンジニア)
LINE Developer Meetup in Tokyo #39 Testing & Engineering
での発表資料です
https://line.connpass.com/event/91423/
AWS October Webinar Series - Introducing Amazon Elasticsearch ServiceAmazon Web Services
Running Elasticsearch often requires specialized expertise and significant resources to operate and manage infrastructure and Elasticsearch software.
Amazon Elasticsearch Service makes it easy to deploy, operate, and scale Elasticsearch in AWS.
In this webinar, we will walk through how to launch a fully functional Amazon Elasticsearch domain, load your data, and analyze it using the built-in Kibana integration. We will also cover the CloudWatch Logs integration, which enables you to have your log data, such as VPC logs, automatically loaded into your Amazon Elasticsearch domain for analysis and exploration.
(BDT209) Launch: Amazon Elasticsearch For Real-Time Data AnalyticsAmazon Web Services
Organizations are collecting an ever-increasing amount of data from numerous sources such as log systems, click streams, and connected devices. Launched in 2009, Elasticsearch —an open-source analytics and search engine— has emerged as a popular tool for real-time analytics and visualization of data. Some of the most common use cases include risk assessment, error detection, and sentiment analysis. However, as data volumes and applications grow, managing Elasticsearch clusters can consume significant IT resources while adding little or no differentiated value to the organization. Amazon Elasticsearch Service (Amazon ES) is a managed service that makes it easy to deploy, operate, and scale Elasticsearch clusters in the AWS Cloud. Amazon ES offers the benefits of a managed service, including cluster provisioning, easy configuration, replication for high availability, scaling options, data durability, security, and node monitoring. This session presents a technical deep dive on Amazon ES. Attendees learn: Common challenges with real-time data analytics and visualization and how to address them; the benefits, reference architecture, and best practices for using Amazon ES; and data ingestion options with Amazon DynamoDB, AWS Lambda, and Amazon Kinesis.