Our blog-posts
System Engineer, Solution Architect or Data Engineer from Germany? – eoda is hiring!
System Engineer, Solution Architect or Data Engineer from Germany? – eoda is hiring! Let’s talk As part of our eoda | analytic infrastructure consulting we are looking for a System Engineer (m/f/d), Solution Architect (m/f/d) and Data Engineer (m/f/d) With strong problem-solving skills, you are the control center of modern analytics infrastructure landscapes. As part […]
Hey Data Scientists from Germany – eoda is hiring
Hello Data Scientists from Germany – eoda is hiring Let’s talk We are hiring: Senior Data Scientist, Data Scientist, Project Manager in Data Science Machine Learning, Artificial Intelligence and Big Data – these are the buzzwords you hear every day. But for you they are more than just buzzwords? You are familiar with the methods, […]
Automating AWS Organizations with Terraform
Automating AWS Organizations with Terraform n this part we will implement a real-world scenario: We will configure our AWS account in a way that allows multiple teams to access a wide variety of AWS services, but still isolate their resources from another. Terraform allows us to automate this process, so we will be able to […]
Webinar: Data Science in Production
Webinar: Data Science in Production The Way to a Centralized Infrastructure Let’s talk In order to exploit the full potential of data science, a proper IT infrastructure is required which meets the high demands for agility, performance and maintenance. Even more: The right infrastructure promotes collaboration and company-wide participation in the topic of data science. At the same time, […]
Dear Data Scientists – make your job easier!
Dear Data Scientists – make your job easier! Let’s talk You are the modern Indiana Jones of digitalization! Always on the lookout to increase knowledge, show relations and take your organization to the next level. Just like the great discoverers like Leif Eriksson, Vasco da Gama and Lewis and Clark, you never let yourself be […]
Data Science Trends 2021
Data Science Trends 2021 This year has shown how important it is to act quickly and adapt immediately to new circumstances. It turned out that the ability to harness digital technologies was and always will be an important issue. The use of modern technologies was not just an option, but became an absolute necessity. One […]
Shiny: Performance Tuning
Shiny: Performance Tuning with future & promises The practice Let’s talk The second part of our blog series on Shiny dealt with the optimization within Shiny applications. We looked at the theoretical part on how Shiny and the packages future & promises work. In the context of these two packages it was presented how they […]
Shiny: Performance Tuning – Theoretical
Shiny: Performance-Tuning mit future & promises Theoretical In our previous article about Shiny we shared our experiences with load testing and horizontal scaling of apps. We showed the design of a process from a proof of concept to a company-wide application. Let’s talk The second part of the blog series focuses on the R packages […]
Shiny: Load testing and horizontal scaling
Shiny: Load testing and horizontal scaling “Money can’t buy you happiness, but it can buy you more EC2 Instances…” – With this quote Sean Lopp, Product Manager at RStudio, PBC, rang in his “Scaling Shiny” showcase. In this showcase, he uses a load-testing approach to show how a Shiny application can be scaled for 10,000 […]
Version control – The uncomplicated work on a joint project
Version control – The uncomplicated work on a common project Let’s talk Whoever starts a job as a developer in 2019, be it in software development or in data science, data ops, etc., is usually confronted with a tool for version management relatively early. Programs such as Git, SVN and BitKeeper are primarily used to […]
Ansible: Infrastructure as code (IaC)
“Infrastructure as code” has become an important key term in the world of system administration for the development and provision of IT systems – also in a data science context, test and production systems can be set up quickly and easily. The term “as code” refers to the fact that systems are no longer set up and configured manually but are developed using a scripting language. In our article we will show you how configuration processes can be automated by using Ansible.
Kubernetes: Horizontal scaling of data science applications in cloud
Prediction models, machine learning algorithms and scripts for data storage: The modern data science application not only shows more and more complexity, but also puts the existing infrastructure to the test by temporary resource peaks. In this article, we will show how tools such as the RStudio Job Launcher in conjunction with a Kubernetes cluster can be used to outsource the execution of arbitrary analysis scripts to the cloud, scale them and return them to the local infrastructure.
Get started now:
We look forward to exchanging ideas with you.
