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 Lambda の Ruby 対応
Search
Sponsored
·
Your Podcast. Everywhere. Effortlessly.
Share. Educate. Inspire. Entertain. You do you. We'll handle the rest.
→
ryonext
December 21, 2018
Programming
260
0
Share
AWS Lambda の Ruby 対応
ryonext
December 21, 2018
More Decks by ryonext
See All by ryonext
TwitterのList編集しやすいやつ作った
ryonext
0
1.8k
validationについて
ryonext
1
820
AWS Lambda と API GatewayでRails使わずに済んだ話
ryonext
8
4.4k
capistrano-bundle_rsync使ったらオートスケールが高速化した話
ryonext
8
2.6k
PumaとUnicornで最近自分が理解したこと
ryonext
13
9.5k
Hubot事例
ryonext
1
1.7k
Redisでバッチ処理を冗長化しつつ排他制御
ryonext
0
2.1k
CircleCIとwercker
ryonext
3
1.3k
rubykaigi 3day interactive white board
ryonext
2
400
Other Decks in Programming
See All in Programming
ネイティブアプリとWebフロントエンドのAPI通信ラッパーにおける共通化の勘所
suguruooki
0
230
GC言語のWasm化とComponent Modelサポートの実践と課題 - Scalaの場合
tanishiking
0
130
PHPのバージョンアップ時にも役立ったAST(2026年版)
matsuo_atsushi
0
270
PHP 7.4でもOpenTelemetryゼロコード計装がしたい! / PHPerKaigi 2026
arthur1
1
450
メッセージングを利用して時間的結合を分離しよう #phperkaigi
kajitack
3
520
Cyrius ーLinux非依存にコンテナをネイティブ実行する専用OSー
n4mlz
0
260
夢の無限スパゲッティ製造機 -実装篇- #phpstudy
o0h
PRO
0
180
L’IA au service des devs : Anatomie d'un assistant de Code Review
toham
0
160
Strategy for Finding a Problem for OSS: With Real Examples
kibitan
0
130
「接続」—パフォーマンスチューニングの最後の一手 〜点と点を結ぶ、その一瞬のために〜
kentaroutakeda
4
2.2k
Nuxt Server Components
wattanx
0
220
我々はなぜ「層」を分けるのか〜「関心の分離」と「抽象化」で手に入れる変更に強いシンプルな設計〜 #phperkaigi / PHPerKaigi 2026
shogogg
2
730
Featured
See All Featured
The Director’s Chair: Orchestrating AI for Truly Effective Learning
tmiket
1
140
Marketing Yourself as an Engineer | Alaka | Gurzu
gurzu
0
170
Understanding Cognitive Biases in Performance Measurement
bluesmoon
32
2.8k
実際に使うSQLの書き方 徹底解説 / pgcon21j-tutorial
soudai
PRO
199
73k
Six Lessons from altMBA
skipperchong
29
4.2k
I Don’t Have Time: Getting Over the Fear to Launch Your Podcast
jcasabona
34
2.7k
VelocityConf: Rendering Performance Case Studies
addyosmani
333
24k
How to build an LLM SEO readiness audit: a practical framework
nmsamuel
1
700
GitHub's CSS Performance
jonrohan
1032
470k
Exploring the Power of Turbo Streams & Action Cable | RailsConf2023
kevinliebholz
37
6.3k
JAMstack: Web Apps at Ludicrous Speed - All Things Open 2022
reverentgeek
1
400
Kristin Tynski - Automating Marketing Tasks With AI
techseoconnect
PRO
0
210
Transcript
"84-BNCEBͷ 3VCZରԠʹ͍ͭͯ
SF*OWFOUͰͷ ओͳΞοϓσʔτ w 3VCZαϙʔτ w ΧελϜϥϯλΠϜ w -BZFST w "-#͔Βͷݺͼग़͠
ΧελϜϥϯλΠϜ w $PCPM͕ಈ͘͜ͱͳͲ͕͕ͩɺطʹެࣜʹ αϙʔτ͞Ε͍ͯΔϥϯλΠϜଟ͍ͷͰɺͪ͜ ΒͰཁ݅Λຬͨͤͳ͍͔Λ·ͣߟ͑ͨ΄͏͕ྑ ͍ w ݱߦͷެࣜαϙʔτɺ/PEFKT 1ZUIPO +BWB
(P $ 1PXFS4IFMM 3VCZ
-BZFST w ෳͷ-BNCEB͔ؔΒڞ௨ͯ͠༻͢Δ෦ ΛΓग़ͯ͑͠ΔΑ͏ͳػೳ
"-#͔Βͷݺͼग़͠ w "-#ͷϦΫΤετͷλʔήοτͱͯ͠ࢦఆͰ͖ ΔΑ͏ʹͳͬͨ
3VCZαϙʔτʹ͍ͭͯ w ۩ମతʹԿ͕ಈ͔͘ɻ w ެࣜͰ4JOBUSBΛಈ͔͢αϯϓϧ͕͋Δ w IUUQTHJUIVCDPNBXTTBNQMFTTFSWFSMFTT TJOBUSBTBNQMF w "1*(BUFXBZ
-BNCEBͰ4JOBUSB͕ಈ͘ɻ؆ ୯ͳ8FCαʔόʔͳΒ͜ΕΛϕʔεʹվฤ͢Ε ྑͦ͞͏ɻ
(FNʹ͍ͭͯ w Ұൠతͳ3BJMTΞϓϦέʔγϣϯͳͲͰͬͯ ͍ΔΑ͏ʹαʔόʔʹΞοϓϩʔυ͔ͯ͠Β CVOEMFJOTUBMMΛ͢ΔͷͰͳ͍ w -BNCEBʹΞοϓϩʔυ͢Δύοέʔδʹɺ CVOEMFJOTUBMMࡁΈͷ(FNΛؚΜͰΞοϓϩʔ υ͢Δɻ
(FNʹ͍ͭͯ w CVOEMFJOTUBMMEFQMPZNFOUCVOEMFJOTUBMM QBUIͳͲͰϓϩδΣΫτԼʹ(FNΛஔ͘ɻ
/BUJWF&YUFOTJPOΛؚΜͩ (FN w -BNCEB্Ͱͳ͘ɺϩʔΧϧ։ൃڥͰCVOEMFJOTUBMM͢ Δඞཁ͕͋ΔͷͰɺ/BUJWF&YUFOTJPOͳͲڥΛ߹Θͤͳ ͍ͱτϥϒϧʹܨ͕Δɻ w -BNCEBͷ࣮ߦڥυΩϡϝϯτʹॻ͔Ε͍ͯΔɻ w -BNCEB&YFDVUJPO&OWJSPONFOUBOE"WBJMBCMF-JCSBSJFT
"84-BNCEBIUUQTEPDTBXTBNB[PODPNMBNCEB MBUFTUEHDVSSFOUTVQQPSUFEWFSTJPOTIUNM w ".*rBN[OBNJIWNY@HQ
ͦͷଞ3VCZʹݶΒͳ͍ "84-BNCEBͷҙࣄ߲
ඞཁͷͳ͍ 71$ઃఆΛΘͳ͍ w 71$ͷϦιʔεʢ3%4&$ʹର͢Δ4$1 ͷΞΫηεͳͲʣΛߦΘͳ͍ͷͰ͋Εɺ71$ઃ ఆແޮԽ͢Δ w "84-BNCEBؔΛ༻͢ΔࡍͷϕετϓϥΫςΟ ε"84-BNCEBIUUQT EPDTBXTBNB[PODPNKB@KQMBNCEBMBUFTUEH
CFTUQSBDUJDFTIUNM w
71$Λ༗ޮԽ͢Δͱ w ॳظԽ͕͘ͳΔ w 71$ͷۭ͖*1Λҙࣝ͢Δඞཁ͕͋Δ w Πϯλʔωοτଓʹ/"5͕ඞཁʹͳΔ w ͳͲͷσϝϦοτ͕૿͑·͢ɻ
ॏෳ࣮ߦ w -BNCEBBUMFBTUPODFͷΞʔΩςΫνϟʹͳ͍ͬͯΔͷͰɺ ඇಉظݺͼग़͠ &WFOUܕݺͼग़͠ʣͷ߹ɺॏෳ࣮ߦ͞ΕΔ͜ ͱ͕͋Δ w *OWPLF"84-BNCEBIUUQTEPDTBXTBNB[PODPN KB@KQMBNCEBMBUFTUEH"1*@*OWPLFIUNM w
Ҏ্ݺͼग़͕͠ߦΘΕ͕ͯͳ͍࣮ʹ͓ͯ͘͠ඞཁ͕ ͋Δɻ w "1*(BUFXBZ&-#͔Βͷݺͼग़͠ಉظܕݺͼग़͠ͳͷͰ ॏෳ͠ͳ͍
-BNCEBͷϝϞϦ w "84-BNCEBͷεϖοΫతͳઃఆϝϞϦ͠ ͔ͳ͍͕ɺϝϞϦΛ૿͢ͱ$16Ϧιʔε૿ ͑ΔͨΊɺ͘ͳΔ
-BNCEBͷߋ৽ w ߋ৽࣌ʹϦΫΤετ͕དྷ͍ͯͨ߹ɺμϯλ ΠϜͳͲੜ͡ͳ͍͕ɺఔͷҠߦظؒͷؒɺ ͲͪΒͷόʔδϣϯͰݺͼग़͞ΕΔ͔͕ෆఆ
͓͠·͍