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
What's new in Cloud Next 2019
Search
Sponsored
·
Ship Features Fearlessly
Turn features on and off without deploys. Used by thousands of Ruby developers.
→
Manatsawin Hanmongkolchai
May 21, 2019
Technology
330
0
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
What's new in Cloud Next 2019
GDG Cloud Bangkok
Manatsawin Hanmongkolchai
May 21, 2019
More Decks by Manatsawin Hanmongkolchai
See All by Manatsawin Hanmongkolchai
Nix: Declarative OS
whs
0
140
gRPC load balancing with xDS
whs
0
1.1k
ArgoCD
whs
0
490
Writing Babel Plugin
whs
0
230
A Date with gRPC
whs
1
1.5k
ตีแผ่ Microservice ด้วย Tracing
whs
0
410
Next Generation Smart Home
whs
0
1k
Istio and the Service Mesh Architecture
whs
3
1.1k
State Management with MobX
whs
2
420
Other Decks in Technology
See All in Technology
Amazon EVS で VCF 9.0 / 9.1 のサポート開始まとめ
mtoyoda
0
310
個人開発で育てる「大規模設計の苗床」 - AI時代の1人開発から始める業務への知識接続 / The Seedbed for Large-Scale Design - From AI-Era Solo Projects to Professional Knowledge
bitkey
PRO
1
280
しぶいSRE: サーバから見えない障害にどう向き合うか。ラストワンマイルのデバッグ実践 / Shibui SRE
kanny
13
6.4k
Devsumi 2026 Summer 人もAIも使える共通基盤を事業の加速装置にする~デザインシステム運用に学ぶ組織レバレッジ~ 渡辺 凌央
legalontechnologies
PRO
1
230
Empower GenAI with Agile - あなたのアジャイルが生成AIのバフになる仕組み
hageyahhoo
1
210
穢れた技術選定について
watany
17
5.4k
ゴールデンパスは敷いただけでは道にならない ─ 企画部門のエンジニアが技術標準を事業価値に変えるまで
mhrtech
1
200
大量データに対しても、生成AIを用いてリーズナブルにデータ加工をしたい!Databricksのai_queryについて調べてみた
kamoshika
1
210
AI時代のYAGNI:「爆速で無駄になった機能」からの学び / 20260720 Naoki Takahashi
shift_evolve
PRO
2
300
非定型なドキュメントを効率よくリファクタする 〜えぇ!?仕様書27本の移行が1日で終わったって!?〜
subroh0508
2
550
End-to-Endで考える信頼性 —LINEアプリにおけるクライアント開発×SRE連携の実践
maruloop
4
4.5k
Data + AI Summit 2026 イベントレポート: 「AIがビジネスで意思決定するデータ基盤」へ
nek0128
0
260
Featured
See All Featured
BBQ
matthewcrist
89
10k
HU Berlin: Industrial-Strength Natural Language Processing with spaCy and Prodigy
inesmontani
PRO
0
530
Design of three-dimensional binary manipulators for pick-and-place task avoiding obstacles (IECON2024)
konakalab
0
490
My Coaching Mixtape
mlcsv
0
170
How to Talk to Developers About Accessibility
jct
2
380
The Power of CSS Pseudo Elements
geoffreycrofte
82
6.4k
StorybookのUI Testing Handbookを読んだ
zakiyama
31
6.8k
Kristin Tynski - Automating Marketing Tasks With AI
techseoconnect
PRO
0
290
Visualizing Your Data: Incorporating Mongo into Loggly Infrastructure
mongodb
49
10k
Digital Ethics as a Driver of Design Innovation
axbom
PRO
1
340
Practical Orchestrator
shlominoach
191
11k
SEO in 2025: How to Prepare for the Future of Search
ipullrank
3
3.6k
Transcript
What's new in Google Cloud Next 2019 GDG Cloud Bangkok
21 March 2019
Managed service from open source partners: Open source partnership
Managed service from partners, integrated directly into Cloud Console •
Unified billing • Google Cloud support Open source partnership
• Vertical Pod Autoscaler • Node Auto Provisioning • Binary
Authorization • Usage metering • GKE Sandbox GKE Advanced
Get pod resource recommendation (Optional) Update pod request automatically Vertical
Pod Autoscaler
Automatically create node pool based on unschedulable pods' informations: •
CPU, Memory request • GPU request • Taints, tolerations Node Auto Provisioning
Node Auto Provisioning • Create node pools to accomodate request
Cluster Autoscaler • Resize node pools • Cannot do anything if all node pools doesn't fit request GKE Autoscaling
• Record GKE usage in BigQuery • Plot usage data
using Data Studio Usage Metering
Run untrusted workload on GKE using gVisor sandbox • gVisor
emulates Linux kernel in user space • Same sandbox as Cloud Run, Cloud Function & App Engine v2 GKE Sandbox
Serverless container based on Knative Cloud Run
Serverless on Google Cloud Language support Scale to Zero Run
mostly unmodified app Concurrent calls per instance Cloud Run ✅ ✅ 1 - 80 Cloud Function ✅ ❌ 1 App Engine Standard ✅ ❌ 1 - 80 App Engine Flexible (not serverless) ❌ ✅ By CPU
• Binary classification (eg. buy/no buy) • Multiclass classification (eg.
customer segmentation) • Regression (eg. predict customer spending) AutoML Table
Search product catalog from images • Supported categories: Home goods,
Apparels, Toys Cloud Vision Product Search
• Recommended for you • Others you may like •
Frequently bought together • Shopping cart expansion Recommendation AI
Slides on speakerdeck.com/whs Thank you