Embedded Technology 2014 Smart Japan Aliance IoT AzureAtomu Hidaka
IoT時代に乗り遅れるな!低価格マイコンボードのAzure接続
Microsoft社では現在、IoT (Internet of Things)用途向けの新たなクラウドサービス、Azure Intelligent Systems Service (ISS) を用意しています。本講演では組み込みシステム開発技術者向けに、小型低価格のマイコンボードからISSを始めとする Azure が提供する各種サービスに接続し、活用するための方法を紹介します。
Embedded Technology 2014 Smart Japan Aliance IoT AzureAtomu Hidaka
IoT時代に乗り遅れるな!低価格マイコンボードのAzure接続
Microsoft社では現在、IoT (Internet of Things)用途向けの新たなクラウドサービス、Azure Intelligent Systems Service (ISS) を用意しています。本講演では組み込みシステム開発技術者向けに、小型低価格のマイコンボードからISSを始めとする Azure が提供する各種サービスに接続し、活用するための方法を紹介します。
The presentation at DevFest Tokyo 2017 / @__timakin__
An introduction of blockchain and why go is nice to implement blockchain.
Additionally described about the blockchain projects that are based on Go.
by Joyjeet Banerjee, Enterprise Solutions Architect, AWS
Amazon Aurora is a MySQL- and PostgreSQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. In this deep dive session, we’ll discuss best practices and explore new features in areas like high availability, security, performance management and database cloning. Level 300
Apache Spark Streaming + Kafka 0.10 with Joan ViladrosarieraSpark Summit
Spark Streaming has supported Kafka since it’s inception, but a lot has changed since those times, both in Spark and Kafka sides, to make this integration more fault-tolerant and reliable.Apache Kafka 0.10 (actually since 0.9) introduced the new Consumer API, built on top of a new group coordination protocol provided by Kafka itself. So a new Spark Streaming integration comes to the playground, with a similar design to the 0.8 Direct DStream approach. However, there are notable differences in usage, and many exciting new features. In this talk, we will cover what are the main differences between this new integration and the previous one (for Kafka 0.8), and why Direct DStreams have replaced Receivers for good. We will also see how to achieve different semantics (at least one, at most one, exactly once) with code examples. Finally, we will briefly introduce the usage of this integration in Billy Mobile to ingest and process the continuous stream of events from our AdNetwork.
Streaming Data Analytics with Amazon Redshift and Kinesis FirehoseAmazon Web Services
by Joyjeet Banerjee, Enterprise Solutions Architect, AWS
Evolving your analytics from batch processing to real-time processing can have a major business impact, but ingesting streaming data into your data warehouse requires building complex streaming data pipelines. Amazon Kinesis Firehose solves this problem by making it easy to transform and load streaming data into Amazon Redshift so that you can use existing analytics and business intelligence tools to extract information in near real-time and respond promptly. In this session, we will dive deep using Amazon Kinesis Firehose to load streaming data into Amazon Redshift reliably, scalably, and cost-effectively. Level: 200
5. 規模の⼤きなシステムを作る時の選択肢は? 🤔
l ライブラリ系/ミドルウェアはOSSを漁ればお⼿本はたくさんある
l こんな感じで作ればいいなっていう勘所は⼗分つかめる
l 規模の⼤きいシステムをGo未経験者も含むようなチーム(10⼈~)で作る際の
お⼿本はあまりみかけない
l GopherCon等含め意外とパッケージ構成のパターンに⾔及してるものは少ない
l 本LTでは特にここについてどう考えるようにしているかお話します
l インタフェース設計の話などテクニック的な話はないです 🙇
6. ちまたの流儀?
l Golang Package Composition for Web Application: The Case of
Mercari Kauru
l https://speakerdeck.com/mercari/ja-golang-package-composition-for-web-
application-the-case-of-mercari-kauru
l Standard Package Layout
l https://medium.com/@benbjohnson/standard-package-layout-7cdbc8391fc1
l Go and a Package Focused Design
l https://medium.com/@benbjohnson/standard-package-layout-7cdbc8391fc1
7. でも現実は。。。 😎
l DDDを意識としたパターンが多い気がする
l Goとはいえオブジェクト指向的な考えも必要で、メンバ構成次第では機能配置等で維持
メンテ、レビュー⾟い時もある。
l そこそこ⼤きなシステムを経験者/未経験者混合チームで作る時はトランザク
ションスクリプトの余地も残しておく必要あってまた悩ましい
12. ほんとすいません🙇🙇🙇🙇🙇🙇🙇🙇🙇
Golang UK Conference 2016 - Building an enterprise service in Go GoPhoerCon 2017 - Go Anti-Patterns
l よく使われているのには理由がある?
l これぐらいのよくあるネーミングの⽅が未経験ユーザへの導⼊はしやすい?