Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
AWS Loft Tokyo のASK AN EXPERT ブースにおけるご相談・ご対応ロ...
Search
Eiji Shinohara
February 23, 2019
Technology
0
630
AWS Loft Tokyo の ASK AN EXPERT ブースにおける ご相談・ご対応ログ を分析しました :) / ASK AN EXPERT at AWS Loft Tokyo - Tech Consulting Log Analysis
delivered this talk at JAWS DAYS 2019 (
https://jawsdays2019.jaws-ug.jp/
)
Eiji Shinohara
February 23, 2019
Tweet
Share
More Decks by Eiji Shinohara
See All by Eiji Shinohara
Algolia Best Practices Fall 2020
shinodogg
2
1.1k
Algolia Fall 20 Release - wrap up in Japanese
shinodogg
0
890
Algolia 2020 Autumn
shinodogg
0
3.2k
Algolia introduction - DEMO and Ranking Formula
shinodogg
0
440
Introducing Algolia with Demo
shinodogg
0
6k
Algolia Announces Global Expansion Into Japan
shinodogg
0
2.4k
Introducing Algolia in a nutshell
shinodogg
1
1.3k
Building and Running Microservices with AWS
shinodogg
0
720
Accelerating AdTech on AWS in Japan
shinodogg
1
340
Other Decks in Technology
See All in Technology
SREの次のキャリアの道しるべ 〜SREがマネジメントレイヤーに挑戦して、 気づいたこととTips〜
coconala_engineer
1
150
マネジメントって難しい、けどおもしろい / Management is tough, but fun! #em_findy
ar_tama
7
1.2k
マーケットプレイス版Oracle WebCenter Content For OCI
oracle4engineer
PRO
3
970
20250707-AI活用の個人差を埋めるチームづくり
shnjtk
6
4k
Rethinking Incident Response: Context-Aware AI in Practice
rrreeeyyy
1
130
Operating Operator
shhnjk
1
620
20250705 Headlamp: 專注可擴展性的 Kubernetes 用戶界面
pichuang
0
290
衛星運用をソフトウェアエンジニアに依頼したときにできあがるもの
sankichi92
1
160
OpenTelemetryセマンティック規約の恩恵とMackerel APMにおける活用例 / SRE NEXT 2025
mackerelio
2
790
QuickSight SPICE の効果的な運用戦略~S3 + Athena 構成での実践ノウハウ~/quicksight-spice-s3-athena-best-practices
emiki
0
120
FOSS4G 2025 KANSAI QGISで点群データをいろいろしてみた
kou_kita
0
410
クラウド開発の舞台裏とSRE文化の醸成 / SRE NEXT 2025 Lunch Session
kazeburo
1
300
Featured
See All Featured
RailsConf & Balkan Ruby 2019: The Past, Present, and Future of Rails at GitHub
eileencodes
138
34k
CoffeeScript is Beautiful & I Never Want to Write Plain JavaScript Again
sstephenson
161
15k
What’s in a name? Adding method to the madness
productmarketing
PRO
23
3.5k
"I'm Feeling Lucky" - Building Great Search Experiences for Today's Users (#IAC19)
danielanewman
229
22k
How to train your dragon (web standard)
notwaldorf
96
6.1k
Designing for humans not robots
tammielis
253
25k
The Language of Interfaces
destraynor
158
25k
Building Adaptive Systems
keathley
43
2.7k
Navigating Team Friction
lara
187
15k
Designing Experiences People Love
moore
142
24k
10 Git Anti Patterns You Should be Aware of
lemiorhan
PRO
656
60k
[Rails World 2023 - Day 1 Closing Keynote] - The Magic of Rails
eileencodes
35
2.4k
Transcript
© 2019, Amazon Web Services, Inc. or its Affiliates. All
rights reserved. ) 9C :KN : E / L A
© 2019, Amazon Web Services, Inc. or its Affiliates. All
rights reserved. ( ) 2 7B : @ @ @ : A : @ @ @ 31 .4A4 T c 0 - a WS ML 31 /@8 2@ @ JI L J
© 2019, Amazon Web Services, Inc. or its Affiliates. All
rights reserved. AWS Loft Tokyo? ASK AN EXPERT?
© 2019, Amazon Web Services, Inc. or its Affiliates. All
rights reserved. ASK AN EXPERT @ AWS Loft Tokyo ! 2 01 8 - AWS ! Startup Developer J
© 2019, Amazon Web Services, Inc. or its Affiliates. All
rights reserved. AWS Cloud9
© 2019, Amazon Web Services, Inc. or its Affiliates. All
rights reserved. Analyzing ASK AN EXPERT Logs ! Tokenization Word2Vec
© 2019, Amazon Web Services, Inc. or its Affiliates. All
rights reserved. Analyzing ASK AN EXPERT Logs ! Tokenization from janome.tokenizer import Tokenizer t = Tokenizer("userdic.csv", udic_enc="utf8") f = io.open('./sodan.txt', 'r', encoding='utf-8’) tokens = t.tokenize(line) for token in tokens: partOfSpeech = token.part_of_speech.split(',')[0] if partOfSpeech == u'’: if token.surface == ‘https’: pass elif token.surface.isnumeric(): pass else: sodan_words.append(token.surface) https://github.com/mocobeta/janome
© 2019, Amazon Web Services, Inc. or its Affiliates. All
rights reserved. Analyzing ASK AN EXPERT Logs ! Word2Vec from gensim.models import word2vec sodan_sentences = word2vec.Text8Corpus('./sodan_words.txt') sodan_model = word2vec.Word2Vec(sodan_sentences, size=200, min_count=20, window=15) results = sodan_model.wv.most_similar(positive=[u'']) for result in results: print(result) https://github.com/RaRe-Technologies/gensim
© 2019, Amazon Web Services, Inc. or its Affiliates. All
rights reserved. ASK AN EXPERT Logs ! 43 9D 9 . 3 058675 2 3 1 . 3 - 2 3 43 058675 3 . 3 I 9D EAC :
© 2019, Amazon Web Services, Inc. or its Affiliates. All
rights reserved. ASK AN EXPERT Logs ! 2 A L . 201 65 - A 201 2 743 . 8 9:
© 2019, Amazon Web Services, Inc. or its Affiliates. All
rights reserved. AWS Loft Tokyo - ASK AN EXPERT Logs • EC2/RDS/S3 27)+&(70*T LO G;@ ! ⇒ <8=CU • "$Lambda'6,.FMIJT ?QK/ %524LOU ⇒ > J • AWS9SAWS(37-IJ:ND AB# (*´∀V*) " E HRAWS Loft Tokyo “ASK AN EXPERT”17*P J