DevOps Pipelines for Big Data Event - Video & Slides

DevOps Pipelines for Big Data Event - Video & Slides

 
Following the successful FullStack event with over 300 members, we are happy to share the slides and video's from the event.
This event described the tooling & Methodologies used to manage a Big Data project, considering we wish to provide a development environment which is identical or similar to production the challenge is even bigger when dealing with it

Challenges of DevOps for Big Data

When designing a Continuous Delivery Pipeline there are many things to consider, but there is a sentence that helps drive it, which is "Logic and Process stay intact Distribution may differ", in this intro talk we will dig into this three fold and show the different routes one may choose alongside one of the routes by example.
By: Haggai Philip Zagury, Tikal - DevOps group leader
 

CI in the docker world

Docker has recently become a popular deployment vehicle, and is still gaining popularity over more traditional deploy methods, such as RPMs.It is a natural desire to want the product's CI pipeline to cover the product end-to-end and deliver a deployable artifact.This talk will cover our usage of Docker at aloooma, and in particular how we integrated it into our build-CI pipeline, with Maven and Jenkins.
By: Eli Oxman from Alooma
 
 

DevOps Tools for enabling the Big Data applications lifecycle

DevOps on the big data arena has several challenges to deal with:First, there are many tools out there and they do not all adhere to one deployment paradigm.Second, many of those tools are not mature enough and do not have a stable ecosystem for deployment.Third, when we deal with Big Data, we generally deal with clusters that include dependencies between processes on different nodes. There are several approaches that try to deal with those challenges.
By: Ran Silberman from Tikal