Ninja Webtechnologies. Eray Basar, 9elements



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Transcription:

Ninja Webtechnologies Eray Basar, 9elements

Webdeveloper vs. Security Engineers

Webdeveloper vs. Security Engineers

Introduction Past and Present Evolution

Past and Present Evolution 9elements Web Hardware

Past and Present 9elements 2005 PHP Apache MySQL Actionscript / Flash Javascript C++

Past and Present 9elements 2010

Past and Present 9elements 2010 Javascript

Past and Present 9elements 2010 Javascript JQuery im Frontend

Past and Present 9elements 2010 Javascript JQuery im Frontend NodeJS im Backend / Middle-end

Past and Present 9elements 2010 Javascript JQuery im Frontend NodeJS im Backend / Middle-end Coffeescript als Abstraktionslayer

Past and Present 9elements 2010 Javascript JQuery im Frontend NodeJS im Backend / Middle-end Coffeescript als Abstraktionslayer Objective-C / Cocoa

Past and Present 9elements 2010 Javascript JQuery im Frontend NodeJS im Backend / Middle-end Coffeescript als Abstraktionslayer Objective-C / Cocoa Actionscript / FLEX

Past and Present 9elements 2010

Past and Present 9elements 2010 Ruby

Past and Present 9elements 2010 Ruby Rails als Framework

Past and Present 9elements 2010 Ruby Rails als Framework HAML / SASS als Abstraktionslayer fuer HTML / CSS

Past and Present 9elements 2010 Ruby Rails als Framework HAML / SASS als Abstraktionslayer fuer HTML / CSS Apache, NginX, Lighttp

Past and Present 9elements 2010 Ruby Rails als Framework HAML / SASS als Abstraktionslayer fuer HTML / CSS Apache, NginX, Lighttp MySQL, PostGre, MongoDB, CouchDB

Past and Present 9elements 2010 Ruby Rails als Framework HAML / SASS als Abstraktionslayer fuer HTML / CSS Apache, NginX, Lighttp MySQL, PostGre, MongoDB, CouchDB C++

Hardware Mobile & Embedded Revolution

Hardware Mobile & Embedded Revolution

von Ray Kurzweil, Age of the Spiritual Machines

Past and Present Web 2005

Past and Present Web 2005

Past and Present Web 2010

Past and Present Web 2010

Past and Present Web 2010

Past and Present Web Platforms 2010

Past and Present Web Platforms 2010

Anforderungen Adaptivität Platformübergreifend Konnektivität & Shared Data (APIs) Realtime Data Skalierbarkeit Big Data

Frontend APIs Backend / Middle-end Database

Frontend html5 & javascript

Actionscript vs. HTML5

Frontend HTML5 & CSS3

Frontend HTML5 & CSS3

Frontend HTML5 & CSS3

PNG Hack

APIs Connectivity, Shared Data, Vulnaribily

I personally find it disheartening that a protocol handling third-party authentication for the personal data of 400 million users has a section entitled Security Considerations that still only contains the note, Todo. - Joey Tyson, Social Hacking

...big companies act like they all really protect our privacy and such, but they see that people donʼt care and donʼt do anything really. - Vahe G. to techcrunch

Backend & Middle-end Javascriptism

Javascript Closures & Scopes

Ben Nadel http://www.bennadel.com/ Text Text

Ben Nadel http://www.bennadel.com/

Meet NodeJS

NodeJS Event-basiertes asynchrones IO Läuft auf V8 Javascript stable version: v0.25 (!!) Warum nicht ruby statt Javascript?

Warum nicht ruby statt Javascript? Javascript was made for evented IO!

Warum nicht ruby statt Javascript? Javascript was made for evented IO!

Warum nicht ruby statt Javascript? Javascript was made for evented IO!

Beispielanwendung NodeJS Proxy Applikation http://www.pgrs.net/2010/2/1/web-proxy-in-node-js-for-high-availability

Beispielanwendung NodeJS Proxy Applikation http://www.pgrs.net/2010/2/1/web-proxy-in-node-js-for-high-availability

Beispielanwendung NodeJS Proxy Applikation http://www.pgrs.net/2010/2/1/web-proxy-in-node-js-for-high-availability

quo vadis, NodeJS für welche Applikationen interessant? backend? middle-end? scalability?

NoSQL Realtime Data, Big Data, Semantic Data

NoSQL Cap Theorem Consistency: Alle Nodes greifen auf die selben Daten zu Availibility: Jeder Node kann immer schreiben u. lesen Partition Tolerance: Das System funktioniert trotz des Ausfall von Nodes

NoSQL Cap Theorem

http://robhirschfeld.com/

Key Value & Document Database CouchDB Document

Map Reduce für Queries { } id : 1 date : 20101201 checkout : 100 { } id : 2 date : 20101201 checkout : 42 { } id : 3 date : 20101201 checkout : 215 { } id : 4 date : 20101201 checkout : 73

Map Reduce für Queries z.b sum(checkout) { } id : 1 date : 20101201 checkout : 100 { } id : 2 date : 20101201 checkout : 42 { } id : 3 date : 20101201 checkout : 215 { } id : 4 date : 20101201 checkout : 73

Map: emit(checkout) 100 42 215 73 { } id : 1 date : 20101201 checkout : 100 { } id : 2 date : 20101201 checkout : 42 { } id : 3 date : 20101201 checkout : 215 { } id : 4 date : 20101201 checkout : 73

Reduce: sum(checkouts) 142 288 100 42 215 73 { } id : 1 date : 20101201 checkout : 100 { } id : 2 date : 20101201 checkout : 42 { } id : 3 date : 20101201 checkout : 215 { } id : 4 date : 20101201 checkout : 73

Reduce: sum(checkouts) 430 142 288 100 42 215 73 { } id : 1 date : 20101201 checkout : 100 { } id : 2 date : 20101201 checkout : 42 { } id : 3 date : 20101201 checkout : 215 { } id : 4 date : 20101201 checkout : 73

Reduce: sum(checkouts) Assoziativgesetz: sum(a + b +c +d) = sum( sum(a+b), sum(c,d) ) 430 142 288 100 42 215 73 { } id : 1 date : 20101201 checkout : 100 { } id : 2 date : 20101201 checkout : 42 { } id : 3 date : 20101201 checkout : 215 { } id : 4 date : 20101201 checkout : 73

Updates in O(log(n)) 440 152 288 100 52 215 73 { } id : 1 date : 20101201 checkout : 100 { } id : 2 date : 20101201 checkout : 52 { } id : 3 date : 20101201 checkout : 215 { } id : 4 date : 20101201 checkout : 73

OMG! It s javascript again!

OMG! It s javascript again!

OMG! It s javascript again!

OMG! It s javascript again!

OMG! It s javascript again!

Realtime Data, Big Data, Semantic Data Twitter

Realtime Data, Big Data, Semantic Data Twitter 1.200.000 delivered Tweets per second

Realtime Data, Big Data, Semantic Data Twitter 1.200.000 delivered Tweets per second 400GB während ich den Vortrag halte

Realtime Data, Big Data, Semantic Data Twitter FE: Javascript / Ruby on Rails Middleend: Ruby on Rails / Scala Text BE: Scala, Java, C++ FlockDB for Social Graph, HBase, Cassandra, Pig & Hadoop for Storage and Data Analysis http://nosql.mypopescu.com/post/619925133/learning-nosql-from-twitters-experience

Let s sum up Technologiezyklen verkuerzen sich Spektrum an eingesetzten Technologien erweitert sich horizontal & vertikal immer mehr Middelware, Zwischeninstanzen und Dependencies Einsatz von Technologien < v1.0 Trügerisches Gefuehl der Sicherheit?

Danke.

Danke.

Danke. we re hiring;)