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TYPO3 CMS v8 in the
cloud
save more time
Johannes Goslar
dkd Internet Service GmbH
11.11.2016
1
Agenda
Machines?
TYPO3 in this context?
Problems?
Cloud principals?
Future!
2
3
Personal
Summer 2006
October 2012 till
April 2016
Software
First TYPO3 CMS experience at media
lights
student at Hochschule Darmstadt

employed at

dkd Internet Service GmbH
Free software fan
Maintainer emacs xdebug extension
First TYPO3 CMS Azure package
Platform.sh integration
Machines
4
Machines
5
What could go wrong?
6
TYPO3 in this context
7
»Inspiring people to share«
8
faster content creation content creation
code
reuse
extensions
faster
content
creation
saved time
Biggest Hurdle?
9
INFRASTRUCTURE
Apache/Nginx/Lighttpd
GNU/Linux/*BSD/Windows
PHP 5.5/5.6/7.0/HHVM
Hoster?
TYPO3 CMS version?
Bootstrap/Foundation/…?
Extensions?
Roles?
Content?
Developer
10
End Users
11
???
–Some Developer
»Let some expert handle that
specific problem.«
13
What is Microsoft Azure (or some
other cloud)?
14
It’s IaaS + PaaSIt’s hybrid readyIt’s open and flexibleIt’s always up, always onIt’s economical and scalableIt’s everywhere
- Olivier Dobberkau
»And let Johnny do the config
there.«
15
Azure Web Gallery
v6 2014
16
17
18
19
20
21
22
Past problems
23
Technical Problems
25
v8
26
doctrine
27
typo3temp
28
typo3temp/assets
typo3temp/var
Misc
• LocalConfiguration.php handling
• Cache configuration
• Read-Only filesystem support
29
Cloud Principles
in conjunction with
30
31
Orchestrated
Consistent
Deterministic
Orchestrated Cloud
• “Planned to produce a desired result”
• Resolve dependencies and build code
• Provision servers, storage, network, launch and configure services
• Manage data
32
Orchestrated Cloud
• Guarantee high availability for all services
• Guarantee disaster recovery for all services
• For every developer and tester, as well as production
33
Orchestrated
Orchestrated
Orchestrated
37
RuntimeRuntimeRuntime
DNS
CDN
Load Balancer
Virtual Machines
Storage (SSD)
Backups / Disaster Reccovery
Databases: Galera/MariaDB, MongoDB, PostgreSQL
Search: ElasticSearch, Solr
Cache: Redis Cluster
Queue: RabbitMQ
1 Application runtimes are split into
separate Virtual Machines, and can
scale horizontally to any number.
2 Databases and other services are on
a separate cluster. This increases the
maximum size and capacity for the
Database tier, and is suitable for
extremely demanding or high traffic
sites.
Load Balancer
Runtime Runtime
Consistent Cloud
• “acting or done in the same way over time”
38
Consistent Cloud
• Use the same tools to deploy, on every environment
• Know from deploying to (@dev / @test / @stage / @UAT ) that deploying
to @production will work.
• Consistent infrastructure, real data
39
Deterministic Cloud
• “for every event there exist conditions that could cause no other event”
41
Deterministic Cloud
• or a given Git repository (hash), exactly the same application code and
infrastructure should be deployed, every time it is pushed to any
environment.
42
Benefits of
• One deployment and server structure that is:
• Simple to execute
• Testable
• Repeatable
• Reversible
43
44
45
46
47
48
49
50
51
DIY
• https://github.com/platformsh/platformsh-example-typo3
• http://bit.ly/typo3-psh
52
Future
53
Future
• More cloud providers supported (Amazon, Google, …)
• Better and more advanced introduction packages
• Cloud API integrations (e.g. image recognition)
• It’s free software, join in!
54
dkd says “thank you”
development - kommunikation - design
Johannes Goslar
johannes.goslar@dkd.de
@ksjogo
https://github.com/ksjogo
56

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