Without the cloud it is very difficult to store and share the huge volumes of data needed for genome sequencing. Given the sensitivity of human genome data in terms of ownership and privacy, security and compliance are paramount.
Organisations, whose functions are classified as “system relevant” by regulators (hospitals, banks etc.), suppliers to these organisations and those who provide important essential services, need to meet special criteria for business continuity: they need to be up and running again very quickly. In this blog post, we provide answers to the most important questions related to business continuity for cloud systems and services.
You have heard of containers, but find them a bit of a mystery? Then this article is perfect for you. In it, we explain the concept and characteristics of containers. This helps to understand why containers are one of the big trends in IT.
In this post, I will show you how to make your application data persist by adding a persistent volume claim to an already deployed pod/container.
With this blog post, our goal is to help customers to avoid irrecoverable loss of data and computing resources, by making sure they have considered the scenarios they need to guard against and have recovery plans for these.
In this article I demonstrate how to set up an autoscaler to scale up the pods when the CPU usage exceeds a certain threshold and back down again.
Customer and other confidential company data is one of the most valuable assets in the digitalized economy. To protect this asset adequately in the cloud, there is currently only one secure strategy: to work with a European owned cloud infrastructure partner.
The Kubernetes cloud is the perfect infrastructure for microservices architecture. It provides an out-of-the-box solution to get you up and running quickly on a managed public or on a dedicated private Kubernetes/OpenShift cluster.
Sharing documents with colleagues, customers and suppliers while collaborating on them is part of everyday life in many companies. But is this data exchange also secure? With the “Data Drop” from Safe Swiss Cloud, the data is stored on a private server in your own virtual data center making it easy to collaborate securely.
Use cases for home office, customer interactions, team meetings, bilateral, formal and supplier interactions are determining the requirements for remote working.
JupyterLab is the most widely used data science / machine learning IDE. Deploying it on OpenShift / Kubernetes adds another layer of flexibility in terms of convenience, resource allocation and horizontal scaling across user groups.