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heidloff.net - Building is my Passion
Niklas Heidloff
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Authentication of Users in Serverless Applications

Recently I open sourced a complete serverless web application which can be deployed on the IBM Cloud in less than 10 minutes. In this article I describe how users are authenticated via IBM App ID. ...

Hosting Resources for Web Applications on the IBM Cloud

Recently I open sourced a complete serverless web application which can be deployed on the IBM Cloud. This short article describes how static web resources like HTML and JavaScript files can be hos...

Developing Serverless Web Applications on the IBM Cloud

With serverless platforms like IBM Cloud Functions different types of scenarios can be built. Very common scenarios are APIs and web applications. I’ve open sourced some code that shows how to buil...

Pictures from W-JAX 2018

This week I had the pleasure to attend W-JAX in Munich which is a conference for Java and enterprise developers with 1400 attendees. I’ve been to JAX and W-JAX several times and really like this co...

Hosting Static Web Application Resources on OpenWhisk

The tutorial Serverless Web Application and API describes how to develop serverless APIs and web applications via IBM Functions, the IBM Functions API Gateway and a No-SQL database. The static web ...

Pictures from data2day

This week my colleagues Stephan Reimann and Thomas Südbroecker and I attended data2day in Heidelberg. data2day is a technical conference for data scientists and developers focussed on topics relate...

Using Docker Containers in the Deep Learning Platform FfDL

In order to train the object detection model for my sample TensorFlow Object Detection for Anki Overdrive Cars, I used a custom Docker container. I’ve extended the description of my repo to also do...

Installing Knative on the IBM Cloud

I finally found some time to start playing with Knative. It took me a few hours to get a simple sample running. Below I describe some pitfalls when installing Knative and tips how to avoid them. Wi...

Training TensorFlow Object Detection Models

TensorFlow Object Detection is a powerful technology to recognize different objects in images including their positions. The trained Object Detection models can be run on mobile and edge devices to...

Deploying Machine Learning Models in the Cloud

For software development there are many methodologies, patterns and techniques to build, deploy and run applications. DevOps is the state of the art methodology which describes a software engineeri...

Disclaimer
The postings on this site are my own and don’t necessarily represent IBM’s positions, strategies or opinions.
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