Deprecated: (!First Steps) with Oracle Cloud’s Pub/Sub Service: Oracle Messaging Cloud Service

Lucas Jellema

Fire and forget messaging is a powerful concept. Asynchronous, decoupled communication is key to scalability and independence of services. Oracle Cloud provides a pub/sub solution called Oracle Messaging Cloud Service. This is an HTTP based publish and subscribe mechanism for asynchronous communication – based on persistent messages and durable subscriptions. […]

Scheduling Oracle Cloud Function execution

Lucas Jellema 2

Functions on Oracle Cloud are an important element in any cloud native application architectures. Functions are typically small, well contained and fairly independent pieces of logic to carry out specific tasks. These tasks can be executed upon reception and handling of HTTP requests – a very common use case – […]

Introduction to Oracle Machine Learning – SQL Notebooks on top of Oracle Cloud Always Free Autonomous Data Warehouse

Lucas Jellema

One of the relatively new features available with Oracle Autonomous Data Warehouse is Oracle Machine Learning Notebook. The description on Oracle’s tutorial site states: “An Oracle Machine Learning notebook is a web-based interface for data analysis, data discovery, and data visualization.” If you are familiar with Jupyter Notebooks (often Python […]

Tour de France Data Analysis using Strava data in Jupyter Notebook with Python, Pandas and Plotly – Step 2: combining and aligning multi rider data for analyzing and visualizing the Race

Lucas Jellema

In this article, I analyze the race that took place in stage 14 of the 2019 Tour de France in a Jupyter Notebook using Python, Pandas and Plotly and based on the Strava performance data published by Steven Kruijswijk, Thomas de Gendt, Thibaut Pinot and Marco Haller. In this previous […]

Tour de France Data Analysis using Strava data in Jupyter Notebook with Python, Pandas and Plotly – Step 1: single rider loading, exploration, wrangling, visualization

Lucas Jellema

In this article, I will show how to analyze the performance of Steven Kruijswijk during stage 14 of the 2019 Tour de France in a Jupyter Notebook using Python, Pandas and Plotly. Strava collects data from athletes regarding their activities – such as running, cycling, walking and hiking. Members can […]

Monitoring Oracle Database using Prometheus

Lucas Jellema 1

Prometheus is a very popular framework for gathering metrics from a plethora of runtime components, recording, analyzing, visualizing them and making them available for companion technologies such as Grafana. Prometheus harvests information from ‘exporters’ – processes that expose an HTTP endpoint where Prometheus can scrape metrics in a format that […]

Collective Data Set and Equal Data Position between B2B Partners in Data Sharing Ecosystems – enter: Blockchain

Lucas Jellema

Many organizations collaborate in one or more ecosystems: groups of organizations that work together in vertical chain or share common interests sometimes even despite being competitors. Examples are research environments (health, climate, agriculture, environment), supply chains & logistics, insurance industry, government agencies, pension funds, traffic management. Note that within large, […]