This presentation is to demonstrate, how the homogenous and centralized network architectures cease to operate efficiently and how limited are our abilities to respond to on-demand computing power in such cases. We will show you how to redesign monolithic storage architectures into modular systems, as well as how to migrate them to a scalable and flexible cloud environment. Maciej Kuzniar - Founder and CEO of the project Oktawave. Passionate about technology related to the processing and data storage, having 10 years of experience working for enterprise customers (banks, telecoms, fmcg). Author of the concepts that support the development of tech startups and architectural solutions to ensure high HA and SLA for IT systems.

1. Switching from monolithic approach to modular
cloud computing
Within the context of providing
high availability application
Maciej Kuźniar, Oktawave

2. W h y are w e u su ally n o t
p ro gram m in g in assem b ler?

3. highly complicated
require strong knowledge
about physical architecture
inconvenient
susceptible for mistakes

4. Instead, we are commonly using mid & high level
languages, expecting to get proper advantages.

5. access to rich
and functional libraries
syntax hints
logical verifcation
loop condition checks

6. We sometimes even
switch to
scripting
languages.
fexibility
agile change
management
platform
independency

7. We are looking
for simplifcation.
choosing ready to use ideas/algorithms
choosing ready to use libs/modules
universal interfaces

8. And where
do all of these
lead us
to?

9. Your app become
“all-in-one”.
Your app become monolithic.
Your app become
slow.

10. And the worst part:
your app is
unpredictable.

11. Why?
unexpected algorithms behaviour
while in stress
unknown libs/modules interacton/risks
usually undefned ability to scale
undefned total cost
of new product/features inserton
inevitable maintenance breaks
Why?
unexpected algorithms behaviour
while in stress
unknown libs/modules interacton/risks
usually undefned ability to scale
undefned total cost
of new product/features inserton
inevitable maintenance breaks

12. So what
can we do
about it?

13. You may let your app
to cooperate with others.
The others are usually better in their jobs.

14. Wait a minute. So you
want me to exchange
my beloved algorithms
and libraries
with ready to use
services?

15. Yes!
Swap your
lib with the service
Yes!
Swap your
lib with the service
determined performancedetermined performance
determined availabilitydetermined availability
elastic
and fitted costs
elastic
and fitted costs
clear interfaceclear interface

16. All right, smart guy.
But where are the examples?

17. There are tons
of ready to use
services.
In the cloud!
object
storage
databases
messaging
in-memory
cache
real-time
processing
Big data
DNS

18. Object storage
tons of static data stored in the cloud
remotely & on-demand
short data processing chain
(browser <->storage)
lower processing latency
embedded ACL
separating data from application processing
physical security by replication
simple REST API
charged by used space

19. Databases
predictable performance
vertical and horizontal
scalability
including smart
load balancing option
SQL compatible
easy to deploy
charged
by computing power
& used space

20. Messaging
persistent and secure
message storing
easy to publish
or consume messages
simplifed communication
between participants
ability to separate
application modules while keeping communication between
charged by message count

21. Real-time
in memory caching
usually compatible
with memcached or redis
improve application performance
by storing critical in low-latency memory
may be use as cache for database queries result, session handling, intensive
calculation results
include replication option
ability to build multi-node
cache cluster with simple API/interface
charged by size of memory granted

22. Real-time
processing
can collect and process
hundred of terabytes hourly
data can be collected
from hundreds of thousands of sources
allows to to easily write applications that process information in real-time from sources such as
web site click-streams, marketing and fnancial information
can be use for marketing and fnancial information, manufacturing instrumentation and social
media, and operational logs, metering data, mobile devices
ability to continuously analyse data
at any volume and throughput, in real-time
charged by memory consumption and CPU usage

23. Big data
usually for batch processing
of large amount of data
throgh standardised interface
with cloud - instant availability
(without expensive
on-site infrastructure goods)
unlimited scalability
charged hourly by granted space and computational power

24. SMART Anycast DNS
spread DNS trafc across multiple physical locations
answer provided by location with the fastest path
by constantly monitoring (watch.oktawave) ability to failover one or more servers running your application
Embedded round-robin and response time load balancing across geo regions or servers inside one datacenter
Mixed weight & response time load balancing
Smart load balancing based on .js script included in your site which:
collect speed counters directly on customer browser and transfer them DNS engine (browser response time)
GeoIP analytics
BGP latency calucations
charged by queries count

25. See h ow m an y fu n ctio n s o f yo u r a p p lica tio n ca n b
o n th e o u tsid e. Ju st re lax an d fo cu s o n w h at is tru ly i

26. Thank you!
Visit our site:
w w w.oktaw ave.com
(25 zł for tests
for everybody!)