Hopsworks, the company that created the first Enterprise Feature Store for machine learning, released Hopsworks 3.0. This evolution brings a new offering that removes the gap between Python prototypes and production projects, resulting in the first Python-centric Feature Store for machine learning. Data Scientists' language of choice is Python, which is the dominant language for creating feature and training pipelines. However, there are challenges when piping enterprise data into machine learning models reliably and at scale. This risks delaying or derailing machine learning initiatives before they're productive.By bridging the gap between the Data Science friendly Python environments and an enterprise's data, Hopsworks dramatically enhances developer productivity by keeping the focus on building pipelines and getting machine learning models into production, and keeping them there.

Just recently, I got to work with Serverless on AWS Lambda. It's a great technology, and I love the idea not to manage and provision underlying servers. I do much programming in Python, and luckily AWS Lambda comes with a Python Runtime. The Serverless Framework is an excellent way to start; that's what I thought… Here is my story with Serverless Development in AWS Lambda and Python and some of my pain. Probably, you have heard the term Serverless which is a technology where you don't care about managing servers and its underlying infrastructure.

AWS Lambda was released back in 2014, becoming a game-changing technology. By adopting Lambda, many developers have found a new way to build micro-services that could be easily achieved. It comes with many additional advantages such as event-based programming, cloud-native deployment, and the development of the now well-known infrastructure-as-code paradigm. A paradigm-shifting technology like AWS Lambda had to define its own standards to support all the modern app development lifecycle requirements. To make things easy to develop, Lambda decided to offer the easiest way of code project management: the zip file format.

Organisations are increasingly putting machine learning models into production at scale. The increasing popularity of serverless scale-to-zero paradigms presents an opportunity for deploying machine learning models to help mitigate infrastructure costs when many models may not be in continuous use. We will discuss the KFServing project which builds on the KNative serverless paradigm to provide a serverless machine learning inference solution that allows a consistent and simple interface for data scientists to deploy their models. We will show how it solves the challenges of autoscaling GPU based inference and discuss some of the lessons learnt from using it in production.

This article is part of #25DaysOfServerless. New challenges will be published every day from Microsoft Cloud Advocates throughout the month of December. Find out more about how Microsoft Azure enables your Serverless functions. Have an idea or a solution? It's freezing cold up here on the North Pole, which normally makes it the ideal place to host a server farm.

IT and data leaders are constantly challenged to keep up with new trends in emerging and disruptive technologies, and to determine how each can best aid the organization. In the midst of all the changes going on in 2019, it gets increasingly hard to know where to invest in all this new technology. To help add clarity, here are my thoughts on some of the most important trends that will shape data management and software development for the next couple of years. The business multi-verse expands through multi-cloud as data inefficiencies are solved: Multi-cloud promises tremendous reward if it can be used properly, but data inefficiencies and complicated compliance policies hinder progress for many. Expect to see some of those data inefficiencies fade away as effective data strategies are implemented and new technologies unleash true multi-cloud functionality to the masses.

IT and data leaders are constantly challenged to keep up with new trends in emerging and disruptive technologies, and to determine how each can best aid the organization. In the midst of all the changes going on in 2019, it gets increasingly hard to know where to invest in all this new technology. To help add clarity, here are my thoughts on some of the most important trends that will shape data management and software development for the next couple of years. The business multi-verse expands through multi-cloud as data inefficiencies are solved: Multi-cloud promises tremendous reward if it can be used properly, but data inefficiencies and complicated compliance policies hinder progress for many. Expect to see some of those data inefficiencies fade away as effective data strategies are implemented and new technologies unleash true multi-cloud functionality to the masses.

We're big fans of keeping track of what is going on in the developer community. So, what does the technical world look like today? And more importantly, where is it going? SlashData's Developer Economics global survey reached more than 21,000 developers from around the world and focused on four major themes: AI, serverless, augmented and virtual reality, and programming languages. According to their research, Machine learning and AI are poised to fuel a new wave of innovation.

For the last six years running, the most important event in cloud computing has been AWS re:Invent, where the market leader announces its latest improvements. This year, 44,000 people descended upon a very crowded set of Las Vegas venues spread across multiple hotels for breakout sessions, certification exams, a diverse expo floor, and the all-important keynotes where the newest offerings were announced. Increasingly, the public cloud arms race is being waged on four fronts, with a fifth quickly emerging. All five had a healthy set of announcements--here are some of the highlights. AWS started the cloud revolution with its S3 object storage service in 2006, which was quickly followed by its EC2 compute offering and a set of other IaaS products.

DXWorldEXPO LLC announced today that Dynatrace will exhibit at the 22nd International CloudEXPO DevOpsSUMMIT DXWordEXPO New York, which will be held November 11-13, 2018, in New York City. Dynatrace is an application performance management software company with products for the information technology departments and digital business owners of medium and large businesses. Today we can collect lots and lots of performance data. We build beautiful dashboards and even have fancy query languages to access and transform the data. Still performance data is a secret language only a couple of people understand.