# Blog

## New nonlinear least squares solvers in R with {gslnls}

Introduction Solving a nonlinear least squares problem consists of minimizing a least squares objective function made up of residuals $g_1(\boldsymbol{\theta}), \ldots, g_n(\boldsymbol{\theta})$ that are nonlinear functions of the parameters of interest $\boldsymbol{\theta} = (\theta_1,\ldots, \theta_p)'$: $$\boldsymbol{\theta}^* \ = \ \arg \min_{\boldsymbol{\theta}} \frac{1}{2} \Vert g(\boldsymbol{\theta}) \Vert^2$$ In the context of regression, this problem is usually formulated as: \begin{align} \boldsymbol{\theta}^* & \ = \ \arg \min_{\boldsymbol{\theta}} \frac{1}{2} \Vert \boldsymbol{y} - f(\boldsymbol{\theta}) \Vert^2 \\ & \ = \ \arg \min_{\boldsymbol{\theta}} \frac{1}{2} \sum_{i = 1}^n (y_i - f_i(\boldsymbol{\theta}))^2 \end{align}

## Rotating log files in Rust, and reassembling them for inspection

Context Open Analytics is working on a huge data processing pipeline in the context of high-content imaging. The latest work to this end is a new product that will work in conjunction with Phaedra as part of the pipeline which now covers much more ground than before. The entire backend of this new component is written in Rust and consists of several web servers. Proper log rotation has been a focus as of late, since it is critical to be able to keep on top of things in this massive processing pipeline.

## ShinyProxy 2.6.0

ShinyProxy 2.6.0 Today we release version 2.6.0 of ShinyProxy which includes over forty improvements. ShinyProxy is a novel, open source platform to deploy Shiny apps for the enterprise or larger organizations. Nevertheless, ShinyProxy is also an excellent choice for deploying a handful of apps in smaller organizations. While ShinyProxy is generally used to host Shiny applications, it has always been designed with the idea to host any application that can be packaged into a Docker container.

## Serverless Fan-Out in Vaccine Research

Serverless Fan-Out in Vaccine Research Discovering new vaccines involves intensive data science: the 3D structure and shape of viruses need to be matched to the 3D structure of hundreds of thousands of proteins that can potentially bind on the virus surface. We will not go into the multiple challenges this problem poses from a methodological point of view, but focus on how to deal with the hundreds of thousands of proteins that enter the arena.

## Kustomize Best Practices

Introduction In recent years, Kubernetes has become a renowned solution for orchestrating cloud-independent infrastructure. Open Analytics supports the data analysis process end to end. This includes infrastructure that underpins the data science platforms we build. Since we exclusively work with open technology, it should come as no surprise that we adopted Kubernetes early on in our technology stack. As Kubernetes rose in popularity and maturity, it became an essential backbone to deliver fully open-source data science platforms.

## Trends Gazelle 2021

Open Analytics nominated as a Trends Gazelle 2021 The ‘Trends Gazelles’ is an annual award organised by the leading Belgian financial and economic news magazine Trends. The nomination was not sought. It fell in our letter box. No slick sales pitches or polished presentations, but based on a quantitative analysis of our numbers. According to Trends Open Analytics is a fast growing, competitive company with a positive impact on the regional entrepreneurial environment, a real power source of innovation and employment, and an inspiring role model for other companies.

## Phaedra 1.0.9

High Content Screening Phaedra is a 100% open source platform for data capture and analysis of high-content screening data. It offers functionality to import image data from any source assess your data with industry’s richest toolbox improve data quality using intelligent validation methods use built-in statistics and machine learning workflows generate QC and analysis reports using templates What’s new? What’s new in this release? Among many other things:

## RDepot 1.4.3

100% Open Source Enterprise Management of R Repositories RDepot is a solution for the management of R package repositories in an enterprise environment. It allows to submit packages through a user interface or API and to automatically update and publish R repositories. Multiple departments can manage their own repositories and different users can have different roles in the management of their packages. package submission through a user interface and via the REST API modern, mobile-friendly interface to browse packages and repositories authentication and fine-grained authorization with repository roles (administrator, repository manager, package manager, user) full versioning of repositories and audit trails for use in regulated contexts built-in support for load-balanced package repositories integration with continuous integration infrastructure for quality assurance on R packages What’s new in this release?

## ShinyProxy 2.4.0

ShinyProxy is a novel, open source platform to deploy Shiny apps for the enterprise or larger organizations. Full Kubernetes Support One of the main advantages of ShinyProxy is the use of plugable container back-ends which allows people to use ShinyProxy on a plain Docker host, on a Docker Swarm cluster or on internet-scale Kubernetes cluster in the cloud. The way organizations have been deploying ShinyProxy on Kubernetes clusters has grown exponentially and providing a means to configure ShinyProxy tailored to the specific Kubernetes setup became more important.

## ShinyProxy 2.2.0

ShinyProxy is a novel, open source platform to deploy Shiny apps for the enterprise or larger organizations. Secured Embedding of Shiny Apps Since version 2.0.1 ShinyProxy provides a REST API to manage (launch, shut down) Shiny apps and consume the content programmatically inside broader web applications or portals. This allows to cleanly separate the responsiblity for the Shiny apps (data science teams) and those broader applications (IT teams) while still achieving seamless integration between the two from the user’s perspective.