0 Downsizing the Data Set – Resampling and Binning of Time Series and other Data Sets
Data Sets are often too small. We do not have all data that we need in order to interpret, explain,…
0 Using Elastic Stack, Filebeat (for log aggregation)
In my last article I described how I used ElasticSearch, Fluentd and Kibana (EFK). Besides log aggregation (getting log information…
0 Prepare Jupyter Notebook Workshop Environment through Docker container image and Bootstrap Notebook
Earlier this week, I presented a workshop on Data Analytics. I wanted to provide each of the participants with a…
0 Microservice framework startup time on different JVMs (AOT and JIT)
When developing microservices, a fast startup time is useful. It can for example reduce the amount of time a rolling…
0 A Readers Story: Connor McDonald on Solving a Sudoku with one SQL Statement
The AMIS Technology Blog has reached a milestone and celebrates its 15-year anniversary! Over the past 15 years, we’ve published…
0 Running a container in the AWS cloud using Fargate
There can be moments that you are really proud of what you achieved. You want to show it to colleagues…
2 Determine the Language of a Document from the Letter Frequency – using Levenshtein Distance between sequences
Even though many languages share the same or a very similar alphabet, the use of letters in documents written in…
0 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
In this article, I analyze the race that took place in stage 14 of the 2019 Tour de France in…
0 Tour de France Data Analysis using Strava data in Jupyter Notebook with Python, Pandas and Plotly – Step 1: single rider loading, exploration, wrangling, visualization
In this article, I will show how to analyze the performance of Steven Kruijswijk during stage 14 of the 2019…
0 Analyzing the 2019 Tour de France in depth using Strava performance data from Race Riders
This year’s Tour de France was quite a spectacle. Great performances, exciting stages, unexpected events: it had it all. Analyzing…
0 Apache Camel and Spring Boot: Calling multiple services in parallel and merging results
Sometimes you have multiple services you want to call at the same time and merge their results when they’re all…
0 Monitoring Oracle Database using Prometheus
Prometheus is a very popular framework for gathering metrics from a plethora of runtime components, recording, analyzing, visualizing them and…
0 A transparent Spring Boot REST service to expose Oracle Database logic
Sometimes you have an Oracle database which contains a lot of logic and you want to expose specific logic as…
1 Dynamic tabs with Angular 6+ and ng-bootstrap
One of our Angular applications required the use of dynamic tabs. Since the project already uses ng-bootstrap components and bootstrap…
0 Test Automation Days 2019
Vorige week woensdag en donderdag (19 en 20 juni) werden de Test Automation Days gehouden. De eerste dag bestond uit…
0 Upgrade Failure as Blessing in Disguise?
or The Findings of an Failed Enterprise Manager Upgrade to OEM13.3 When Oracle Enterprise Manager Cloud Control 13.3 (here just…
0 Collective Data Set and Equal Data Position between B2B Partners in Data Sharing Ecosystems – enter: Blockchain
Many organizations collaborate in one or more ecosystems: groups of organizations that work together in vertical chain or share common…
0 Correlation calls for Common Cause Consideration
Correlation is a powerful thing. When two metrics rise and fall in a similar way, surely that cannot be just…
0 Custom Log Parser in OMC Log Analytics to deal with Extended Logging in WebLogic Access Log
We recently enabled Extended HTTP Access Logging on our WebLogic Managed Servers. This adds the average response times and potentially…
0 Graceful shutdown of forked workers in Python and JavaScript running in Docker containers
You might encounter a situation where you want to fork a script during execution. For example if the amount of…