Mark Krijgsman

Software developer

Mark is strong in making technical concepts understandable for non-technical people within the organisation and gets a lot of pleasure out of this. He also has an eye for the process within scrum teams and enables the team to achieve goals within the sprint.

On a technical level he likes to take the lead in introducing new frameworks, but also gets a lot of satisfaction from refactoring existing code. Mark specialises in Continuous Delivery (CD) and the Elastic stack. With this knowledge he has already helped several customers to make the move to an application landscape that runs entirely on Docker, possibly in combination with other tooling such as Jenkins and Ansible. He also has experience with setting up and upgrading Elasticsearch landscapes.

Mark thrives on varied work where he can contribute to the architecture vision, the CD process and the actual implementation of user requirements.

Feel free to follow his projects on Github

Integration testing Pub/Sub interactions in your application

How do you make sure all goes well when working with big data? At we frequently make use of Pub/Sub queues to decouple data streams between applications. This blog explains how we created integration tests that allow you to test these queues and the interactions that they have with the application. As part of […]

Migrating from GSA to Elasticsearch with ANTLR

Starting January 1st of 2019, the Google Search Appliance (GSA) is set to be EOL. For one of my clients, we have chosen Elasticsearch as our alternative from 2019 onwards. However, there was one problem; the current GSA solution is in use by several API’s that can’t be changed for various reasons. Therefore, it was […]

Elasticsearch instances for integration testing

In my latest project I have implemented all communication with my Elasticsearch cluster using the high level REST client. My next step was to setup and teardown an Elasticsearch instance automatically in order to facilitate proper integration testing. This article describes three different ways of doing so and discusses some of the pros and cons. […]

Providing developers and testers with a representative database using Docker

When developing or testing, having a database that comes pre-filled with relevant data can be a big help with implementation or a scenario walk-through. However, often there is only a structure dump of the production database available, or less. This article outlines the process of creating a Docker image that starts a database and automatically […]

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