1.
Webalkalmazások skálázhatósága
a Google Cloud Platformon
Kodok Márton
@martonkodok
Google Developer Expert
REEA.net
Marosvásárhely

2.
● angolul „cloud computing”
● a szolgáltató eszközein (Google GCP, Amazon AWS, Microsoft Azure)
● a szolgáltatás üzemeltetési részleteit a felhasználótól elrejtve
● adatközpontok - data center - távoli hozzáféréssel irányítható
● nincs szükség dedikált hardver vásárlására
● Idényjellegű is lehet (“per second billing”, “black friday”)
● gyorsan változtatható az allokált erőforrások mérete is
● Helyfüggetlen - Méretezhető - Nagy rendelkezésre állás - Költségkímélő
● Rendszeres biztonsági frissítések
Felhőalapú számítástechnika
A felhőalapú architektúrák és szolgáltatások @martonkodok

3.
REEA.net uses GCP
Build on the same infrastructure
that powers Google

4.
Google Cloud Platform (GCP)
Compute Big Data
BigQuery
Cloud
Dataflow
Cloud
Dataproc
Cloud
Datalab
Cloud
Pub/Sub
Genomics
Storage & Databases
Cloud
Storage
Cloud
Bigtable
Cloud
Datastore
Cloud SQL
Cloud
Spanner
Persistent
Disk
Machine Learning
Cloud Machine
Learning
Cloud
Vision API
Cloud
Speech API
Cloud Natural
Language API
Cloud
Translation
API
Cloud
Jobs API
Data
Studio
Cloud
Dataprep
Cloud Video
Intelligence
API
Advanced
Solutions Lab
Compute
Engine
App
Engine
Kubernetes
Engine
GPU
Cloud
Functions
Container-
Optimized OS
Identity & Security
Cloud IAM
Cloud Resource
Manager
Cloud Security
Scanner
Key
Management
Service
BeyondCorp
Data Loss
Prevention API
Identity-Aware
Proxy
Security Key
Enforcement
Internet of Things
Cloud IoT
Core
Transfer
Appliance

5.
1. Virtual Machines
2. Instance Templates
3. Instance Groups
4. Health check
5. Load Balancer
6. Backend health check
7. Autoscaling - Design for resiliency, scalability, and disaster recovery
8. Demo
9. Practical use cases
Agenda
@martonkodok

6.
GCP: Compute Engine
@martonkodok
iOS
Android
Web
Backend Services
Compute Engine
Flexibility for Every Workload
● High-Performance, Scalable VMs
● Custom Machine Types
● CentOS, Ubuntu, Windows
● Persistent Disks or SSD (local or
network based)
● Per-second billing
● Networking
● Firewall
● Load balancing
● Compliance & Security

7.
@martonkodok
Creating a VM instance steps

8.
Virtual Machine
@martonkodok
Compute Engine
VM
Cloud
Firewall Rules
Ephemeral IP
Labels/Tags: “http-server”
Allow port 80 for: “http-server”
VM details

9.
Instance Group - Autoscaling - Health Check
@martonkodok
Template VM
Startup script
Instance tag
Instance Group
Region + Zone(s)
Autoscaling
Health check
Instance Group
Backend
Compute Engine
Multiple Instances
Region 2 - EU
eu-west 1-b
eu-west 1-a
Instance Group
Backend
Compute Engine
Multiple Instances
Region 1 - US
us-east 1-b
us-west 1-a
Instance Group
Backend
Compute Engine
Multiple Instances
Cloud Load
Balancing
Cloud
Firewall Rules
Health
Check
Allow port 80 for: “http-server”
Static IP Failover

10.
@martonkodok
Live DEMO on GCP

11.
Creating a VM instance
@martonkodok

12.
Creating a VM instance - Choosing Region, Instance type
@martonkodok

13.
Creating a VM instance - OS, boot disk, Network
@martonkodok

14.
VM instances
@martonkodok

15.
Virtual Private Network - Firewall rules
@martonkodok

16.
@martonkodok
Autoscaling
with Instance Groups

17.
Creating an Instance Group
@martonkodok

18.
Setting Autoscaling settings
@martonkodok

19.
Downscale on no load after 10 minute
@martonkodok

20.
@martonkodok
Example Architecture for Autoscaling

21.
CMS with Autoscaling
@martonkodok
ZONE B
Content Server
Compute Engine
Autoscaling
ZONE A
Content Server
Compute Engine
Autoscaling
Static Content
Cloud Storage
Dynamic Content
Cloud SQL
Publisher
Cloud Load
Balancing
Cloud
DNS

22.
DB multiple zones and Master/Slave topology
@martonkodok
Zone 1
us-central 1-a
Instance Group
Compute Engine
Web Applications
Master
Cloud SQL
Zone 2
us-central 1-f
Instance Group
Compute Engine
Web Applications
Read Replica
Cloud SQL
ReplicationCloud Load
Balancing

23.
@martonkodok
Data layer design

24.
Database Mapping
@martonkodok

25.
@martonkodok
Serverless

26.
Meet Serverless
@martonkodok

27.
Meet Serverless
serverless data center depicted
@martonkodok

28.
Serverless is about maximizing elasticity, cost
savings, and agility of cloud computing.
@martonkodok
@martonkodok

29.
Serverless types
@martonkodok
Platforms Triggered Code

30.
App Engine - Websites > API Hosting
@martonkodok
API
Compute Engine
Virtual Machines
API
App Engine
Cloud Endpoints
API
Container Engine
Kubernetes Services
Multiple
Clients
API Requests
Cloud Load
Balancing
● Fully managed serverless application
platform
● Scale your applications seamlessly from
zero to planet scale
● Automatically scales depending on your
application traffic
● Traffic Splitting (app versions, A/B tests,
incremental rollouts)
● Standard vs Flexible environments
Python, Java, Node.js, Go, Ruby, PHP, .NET

31.
App Engine Languages
@martonkodok

32.
App Engine
@martonkodok
Instance startup time Minutes Seconds
Maximum request timeout 60 minutes 60 seconds
Background threads Yes Yes, with restrictions
SSH debugging Yes No
Writing to local disk Yes, ephemeral (disk initialized on VM
startup)
No
Modifying the runtime Yes (through Dockerfile) No
Supports installing third-party binaries Yes No
Pricing Based on usage of vCPU, memory, and
persistent disks
Based on instance hours
Flexible Standard

33.
@martonkodok
Cloud Functions

34.
Cloud Functions
@martonkodok
● Simplest way to run your code in the cloud - just deploy
● Automatically scales, highly available and fault tolerant
● No servers to provision, manage, patch or update
● Pay only while your code runs
● Connects and extends cloud services
Languages: Node.JS and Go, Python coming later.

35.
Cloud Functions
On-Premises Servers
ApplicationEvent Sourcing
Frontend
Platform Services
Metrics / Logs/
Streaming
Event
Triggered
Cloud
Functions
Triggered Code
@martonkodok
Result

36.
Email Delivery + Webhook response
@martonkodok

37.
@martonkodok
Message Queue systems: Task Queue
Cloud Pub/Sub

38.
Task Queue - Message Queue systems
@martonkodok
Static Content
Cloud Storage
Dynamic Content
Cloud SQL
Dynamic Content
Cloud Datastore
Front End App
App Engine
Autoscaling
Task
Queues
Memcache
Batch App
App Engine
Autoscaling
Cloud Load
Balancing
Cloud
DNS
Workers
Compute Engine
Autoscaling

39.
Task Queues
@martonkodok
Slides: https://www.slideshare.net/martonkodok
Title: Architectural Patterns - Message Queues
Push queues
● Put with delays
Pull queues
● Ability to “tag”
● Lease multiple eg: gameboard
updated, game id as tag.

40.
● No servers to provision or manage
● Abstract away the complexity
● Scales with usage (ready every time for viral spikes or #BlackFriday)
● Availability and fault tolerance built in
● No orchestration in code
● Never pay for idle
● Cost savings (ps: we don’t have the same budget for security like GCP or AWS)
● Decoupled: APIs as contracts
● Monitored: Metrics and logging are a universal right
● Think concurrent, stateless, queue, stream based.
Serverlessmeans
@martonkodok

41.
“ Data needs to be processed in
multiple services.
How can we pipe to multiple places?
@martonkodok

42.
Architecting for The Cloud
On-Premises Servers
Event Sourcing
Frontend
Platform Services
Analyze
Metrics / Logs/
Streaming
Cloud Storage
@martonkodok
Cloud
Dataflow
Process
BigQuery
Cloud SQL
Stream
Batch
Data
Studio
Third-Party
Tools

43.
Thank you.
Slides available on: slideshare.net/martonkodok
Reea.net - Integrated web solutions driven by creativity to deliver
projects.