AdroitLogic IPS, Part 2: Installation (Getting the Beast Up and Running)

Okay, all the fancy words aside, what would it take for me to actually try this thing out? A fully-fledged Kubernetes or OpenShift cluster?An AWS account with a valid credit card?A briefcase of cash to pay for support? Fortunately, none of the above. With the DIY IPS Installer you can start up a simple demo … Continue reading AdroitLogic IPS, Part 2: Installation (Getting the Beast Up and Running)

AdroitLogic IPS, Part 1: What it is (and Why You Should Care)

Knowing the yet-again-proven performance margin of UltraESB-X, you may perhaps be wondering what it takes for a brood of them to run in unison, load-balancing and gracefully handling your business demands (web traffic, for instance). Well, never fear, because IPS is here! Okay, I won’t lie: IPS has been around for quite some time (in … Continue reading AdroitLogic IPS, Part 1: What it is (and Why You Should Care)

Using fabric8 docker-maven-plugin to automate docker builds

In building the required libraries for a docker container, using a maven project, the libraries have to be copied to a separate location and we have to manually run a docker build. This process is cumbersome since you have to repeat the same process over even if there is a slight modification. fabric8 docker-maven-plugin is … Continue reading Using fabric8 docker-maven-plugin to automate docker builds

Setting up Kubernetes 1.7 on a CentOS 7.1 cluster

It was quite a daunting task at the beginning to start with Kubernetes 1.7 alpha release because I knew that I was bound to face with difficulties. I built Kubernetes from source on my Ubuntu 16.04 machine. I downloaded the source from kubernetes (https://github.com/kubernetes/kubernetes/tree/v1.7.0-alpha.3) and CentOS 7.1 (minimal version). I set up three virtual machines … Continue reading Setting up Kubernetes 1.7 on a CentOS 7.1 cluster

Changepoint Detection : Theoretical Background

Introduction Changepoints are abrupt variations in the generative parameters of sequential data. Changepoint detection is the process of identifying such abrupt variations and it has been useful in a wide range of applications such as EEG analysis, DNA segmentation, econometrics etc.   Bayesian ways of  change point detection focus on segmentation and techniques to generate … Continue reading Changepoint Detection : Theoretical Background

postCP change point detection with GSOC

Introduction to postCP The project aimed at improving the postCP package and making it available on CRAN again. The snag that prevented the package from being updated is the recent requirement that in the R code, .C() calls require DUP=TRUE arguments, and .Call() is suggested instead of .C(). The implementation of postCP package required that … Continue reading postCP change point detection with GSOC