Enterprise Applications

Porting an Enterprise App to System Z – My Experience Pt.3

Part 3 of 4: The Bad

As I’ve explained in Part 1 Basics and Part 2 Good, I did a proof of concept port of an Enterprise Application from Amazon Web Services on x86 to Linux on System z in 2017. The good news was I got to the point I needed to, the bad news was it was more than difficult to get there.

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Porting an Enterprise App to System Z – My Experience Pt.2

Part 2 of 4: The Good

I provided a simplistic overview of what I intended to port to Linux for System z in Part 1. The original application was built for x86 systems. As such, all binaries are built to run on x86 systems. The Docker containers that these applications run in are x86 binaries as well. So my job was to create the Linux for System z (aka S390X) binaries, with as little change as possible.

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Enterprise App

Porting an Enterprise App to System Z – My Experience

Part 1 of 4: The Basics

At the end of 2016 and lasting a few months into 2017, I completed a proof of concept port of a large Enterprise Application that had been running on the Amazon Web Service Cloud to Linux for System z. This was a Docker based application written in Java…so of course, it would be trivial to port. WRONG. While the application is in Java, it called many pieces of open source code. Much of that code hadn’t been ported to System z yet or wasn’t widely adopted. What I thought was a very simple exercise turned into a six month effort.

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Advanced Analytics

Embracing the Challenges of Gaining Value from Analytics

Data volume and higher transaction velocities associated with modern applications are driving change in organizations across all industries. This has occurred for many reasons. Customer and end-user expectations for interacting with computerized systems have changed—and technology changes to accommodate these requirements. Furthermore, larger and larger amounts of data are generated and made available both internally and externally to businesses. Therefore, the desire and capability to store large amounts of data continues to expand.

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Modern Analytics

Analytics – now – and in the future

It has been going on for decades on the mainframe
The future is about doing it better in multi-platform environments
And – in real time

Given the meteoric rise in the use of smartphones, the increasing inter-connectivity between what were previously non-connected devices (IoT), and more business-relevant data becoming available now more than ever before, you need to ask yourself – “Okay, just exactly how do I find the proverbial “needle in the haystack?”

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Machine Learning

Bringing Machine Learning to Big Iron

In today’s data driven economies there is evermore pressure to drive financial returns and payback for IT investments, increasing the need for IT organizations to deliver both analytics and digital transformation with practical and meaningful business outcomes.

The need for instant services has increased exponentially due to ’consumer driven’ services such as Application Stores, Digital Music, Social Media, E-commerce, FinTech and even IoT. This consumerization of technology drives innovation within the enterprise to reach user expectations but the challenge, as always, is doing this in a highly available and secure manner.

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big data analytics

Big Data at true scale!

Big Data is not an overly sized star trek character or endless storage, but is rather the new currency for IT organizations, that can be analyzed, queried and manipulated to provide a meaningful outcome to almost any analytical question.

And that currency has been paying off big dividends for those organizations with the need and the willingness to dive in. Here are some examples of how the Big Data and Analytics currency is being used today in business environments.

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A guide to machine learning

Machine learning (the subfield of computer science that, according to Arthur Samuel, “gives computers the ability to learn without being explicitly programmed”) is one of the most innovative and interesting fields of modern science around today. Something that you probably associate with things such as Watson, Deep Blue, and even the infamous Netflix algorithm. However, as sparkly as it is, machine learning isn’t exactly something totally new. In fact, the concept and science of machine learning has been around for much longer than you think.

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A Clear Picture

A Clear Picture

IT and business management are increasingly concerned with the rising costs associated with their highly complex and ever-growing mainframe and distributed systems data centers. They are also concerned about controlling outages and mitigating the lack of transparency that they have into cost drivers—including in their outsourced environments.

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Banking Trends

Banking Trends and IT Issues

Digital transformation is impacting businesses far and wide, but you could argue that none are being impacted more dramatically than banking. Over the course of the past few decades the manner in which banks interact with their customers has changed significantly, and more changes are on the horizon.

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