Personal Information
Organization / Workplace
Japan, Tokyo Japan
Occupation
Solutions Architect at Amazon Web Services
Industry
Technology / Software / Internet
Website
about.me/hamburgerkid
About
Supporting customers to take advantage of AWS services more efficiently. It's challenging but really enjoyable.
In previous position, I had worked on keeping up site reliability of a part of big e-commerce service mainly, and also developed anything from front-end UI to back-end batch/stream system for running web services on demand.
And formally my main assignment was to expand and stabilize Hadoop and the related systems in that company.
In addition, I had worked as a web application developer and also as a service producer in a variety of web services like web advertisement, recommendation and so on.
And that, always interested in any challenging solution.
Tags
aws
ivs
ctonight
stream processing
spark
streaming
scalavility
hadoop
See more
Presentations
(4)Likes
(175)ARM CPUにおけるSIMDを用いた高速計算入門
Fixstars Corporation
•
2 years ago
UNICORNの機械学習ワークロードにおけるSpot&AWS Batchの活用
Inoue Seki
•
3 years ago
大規模データ活用向けストレージレイヤソフトのこれまでとこれから(NTTデータ テクノロジーカンファレンス 2019 講演資料、2019/09/05)
NTT DATA Technology & Innovation
•
4 years ago
リペア時間短縮にむけた取り組み@Yahoo! JAPAN #casstudy
Yahoo!デベロッパーネットワーク
•
6 years ago
Parquetはカラムナなのか?
Yohei Azekatsu
•
4 years ago
Best Practices for CI/CD with AWS Lambda and Amazon API Gateway (SRV355-R1) - AWS re:Invent 2018
Amazon Web Services
•
5 years ago
20180729 Preferred Networksの機械学習クラスタを支える技術
Preferred Networks
•
5 years ago
The Columnar Era: Leveraging Parquet, Arrow and Kudu for High-Performance Analytics
DataWorks Summit/Hadoop Summit
•
7 years ago
ML Platform Q1 Meetup: Airbnb's End-to-End Machine Learning Infrastructure
Fei Chen
•
6 years ago
BuildKitによる高速でセキュアなイメージビルド
Akihiro Suda
•
5 years ago
Principles of microservices velocity
Sam Newman
•
8 years ago
今だから!Amazon CloudFront 徹底活用
Yasuhiro Araki, Ph.D
•
7 years ago
Best Practices for Integrating Active Directory with AWS Workloads
Amazon Web Services
•
7 years ago
IOT308-One Message to a Million Things Done in 60 seconds with AWS IoT
Amazon Web Services
•
6 years ago
DeNAの分析を支える分析基盤
Kenshin Yamada
•
8 years ago
Deep Dive into AWS Fargate
Amazon Web Services
•
6 years ago
HTTP/2で 速くなるとき ならないとき
Kazuho Oku
•
6 years ago
HBase at LINE 2017
LINE Corporation
•
6 years ago
NEW LAUNCH! Deep dive on Amazon Neptune - DAT318 - re:Invent 2017
Amazon Web Services
•
6 years ago
AWS Black Belt Online Seminar 2017 Amazon DynamoDB
Amazon Web Services Japan
•
6 years ago
Learning to Rank in Solr: Presented by Michael Nilsson & Diego Ceccarelli, Bloomberg LP
Lucidworks
•
8 years ago
Secured API Acceleration with Engineers from Amazon CloudFront and Slack
Amazon Web Services
•
7 years ago
DB2をAWS上に構築する際のヒント&TIPS 2018年1月版
Akira Shimosako
•
6 years ago
Apache Kudu - Updatable Analytical Storage #rakutentech
Cloudera Japan
•
6 years ago
ネットワーク ゲームにおけるTCPとUDPの使い分け
モノビット エンジン
•
6 years ago
形態素解析の過去・現在・未来
Preferred Networks
•
12 years ago
HBase Sizing Guide
larsgeorge
•
9 years ago
Paxos
Preferred Networks
•
11 years ago
SEC306 Using Microsoft Active Directory Across On-Premises and AWS Cloud Windows Workloads
Amazon Web Services
•
6 years ago
分散システムについて語らせてくれ
Kumazaki Hiroki
•
6 years ago
Personal Information
Organization / Workplace
Japan, Tokyo Japan
Occupation
Solutions Architect at Amazon Web Services
Industry
Technology / Software / Internet
Website
about.me/hamburgerkid
About
Supporting customers to take advantage of AWS services more efficiently. It's challenging but really enjoyable.
In previous position, I had worked on keeping up site reliability of a part of big e-commerce service mainly, and also developed anything from front-end UI to back-end batch/stream system for running web services on demand.
And formally my main assignment was to expand and stabilize Hadoop and the related systems in that company.
In addition, I had worked as a web application developer and also as a service producer in a variety of web services like web advertisement, recommendation and so on.
And that, always interested in any challenging solution.
Tags
aws
ivs
ctonight
stream processing
spark
streaming
scalavility
hadoop
See more