iptizer

ansible-dropbox

Automated Dropbox installation on CentOS7 including selective sync.

ansible-grafana

Role to install and configure Grafana

ansible-keycloak4

Installs Keycloak 4

ansible-linux-kernel-upgrade

ansible playbook to manually compile and install new kernel on Centos/Redhat Linux

ansible-mediawiki-nginx-phpfpm-mariadb

ansible_vagrant_walkthrough

Very simple walkthrough to illustrate Ansible+Vagrant essentials

install-kubeflow

Installing Kubeflow 1.3

k8s-workshop

This is the repository for the k8s-workshop to be first held on the Easterhegg21 in 2024 in Regensburg.

swiss

My personal k8s troubleshoot container.

iptizer/k8s-workshop

This is the repository for the k8s-workshop to be first held on the Easterhegg21 in 2024 in Regensburg.

iptizer/swiss

My personal k8s troubleshoot container.

iptizer/install-kubeflow

Installing Kubeflow 1.3

iptizer/argocd-demo

Demo repository to showcase argo.

iptizer/Assemblies-of-putative-SARS-CoV2-spike-encoding-mRNA-sequences-for-vaccines-BNT-162b2-and-mRNA-1273

RNA vaccines have become a key tool in moving forward through the challenges raised both in the current pandemic and in numerous other public health and medical challenges. With the rollout of vaccines for COVID-19, these synthetic mRNAs have become broadly distributed RNA species in numerous human populations. Despite their ubiquity, sequences are not always available for such RNAs. Standard methods facilitate such sequencing. In this note, we provide experimental sequence information for the RNA components of the initial Moderna (https://pubmed.ncbi.nlm.nih.gov/32756549/) and Pfizer/BioNTech (https://pubmed.ncbi.nlm.nih.gov/33301246/) COVID-19 vaccines, allowing a working assembly of the former and a confirmation of previously reported sequence information for the latter RNA. Sharing of sequence information for broadly used therapeutics has the benefit of allowing any researchers or clinicians using sequencing approaches to rapidly identify such sequences as therapeutic-derived rather than host or infectious in origin. For this work, RNAs were obtained as discards from the small portions of vaccine doses that remained in vials after immunization; such portions would have been required to be otherwise discarded and were analyzed under FDA authorization for research use. To obtain the small amounts of RNA needed for characterization, vaccine remnants were phenol-chloroform extracted using TRIzol Reagent (Invitrogen), with intactness assessed by Agilent 2100 Bioanalyzer before and after extraction. Although our analysis mainly focused on RNAs obtained as soon as possible following discard, we also analyzed samples which had been refrigerated (~4 ℃) for up to 42 days with and without the addition of EDTA. Interestingly a substantial fraction of the RNA remained intact in these preparations. We note that the formulation of the vaccines includes numerous key chemical components which are quite possibly unstable under these conditions-- so these data certainly do not suggest that the vaccine as a biological agent is stable. But it is of interest that chemical stability of RNA itself is not sufficient to preclude eventual development of vaccines with a much less involved cold-chain storage and transportation. For further analysis, the initial RNAs were fragmented by heating to 94℃, primed with a random hexamer-tailed adaptor, amplified through a template-switch protocol (Takara SMARTerer Stranded RNA-seq kit), and sequenced using a MiSeq instrument (Illumina) with paired end 78-per end sequencing. As a reference material in specific assays, we included RNA of known concentration and sequence (from bacteriophage MS2). From these data, we obtained partial information on strandedness and a set of segments that could be used for assembly. This was particularly useful for the Moderna vaccine, for which the original vaccine RNA sequence was not available at the time our study was carried out. Contigs encoding full-length spikes were assembled from the Moderna and Pfizer datasets. The Pfizer/BioNTech data [Figure 1] verified the reported sequence for that vaccine (https://berthub.eu/articles/posts/reverse-engineering-source-code-of-the-biontech-pfizer-vaccine/), while the Moderna sequence [Figure 2] could not be checked against a published reference. RNA preparations lacking dsRNA are desirable in generating vaccine formulations as these will minimize an otherwise dramatic biological (and nonspecific) response that vertebrates have to double stranded character in RNA (https://www.nature.com/articles/nrd.2017.243). In the sequence data that we analyzed, we found that the vast majority of reads were from the expected sense strand. In addition, the minority of antisense reads appeared different from sense reads in lacking the characteristic extensions expected from the template switching protocol. Examining only the reads with an evident template switch (as an indicator for strand-of-origin), we observed that both vaccines overwhelmingly yielded sense reads (>99.99%). Independent sequencing assays and other experimental measurements are ongoing and will be needed to determine whether this template-switched sense read fraction in the SmarterSeq protocol indeed represents the actual dsRNA content in the original material. This work provides an initial assessment of two RNAs that are now a part of the human ecosystem and that are likely to appear in numerous other high throughput RNA-seq studies in which a fraction of the individuals may have previously been vaccinated. ProtoAcknowledgements: Thanks to our colleagues for help and suggestions (Nimit Jain, Emily Greenwald, Lamia Wahba, William Wang, Amisha Kumar, Sameer Sundrani, David Lipman, Bijoyita Roy). Figure 1: Spike-encoding contig assembled from BioNTech/Pfizer BNT-162b2 vaccine. Although the full coding region is included, the nature of the methodology used for sequencing and assembly is such that the assembled contig could lack some sequence from the ends of the RNA. Within the assembled sequence, this hypothetical sequence shows a perfect match to the corresponding sequence from documents available online derived from manufacturer communications with the World Health Organization [as reported by https://berthub.eu/articles/posts/reverse-engineering-source-code-of-the-biontech-pfizer-vaccine/]. The 5’ end for the assembly matches the start site noted in these documents, while the read-based assembly lacks an interrupted polyA tail (A30(GCATATGACT)A70) that is expected to be present in the mRNA.

iptizer/charts

Curated applications for Kubernetes

iptizer/cka-example-environments

iptizer/configuration-as-code-plugin

Jenkins Configuration as Code Plugin

iptizer/crossplane-tutorial

iptizer/docker-awscli-latest_master

This repo hold the Dockerfile for a container with the latest awscli from GitHub.

iptizer/docker-stress-ng

Easy to use and simple stress-ng Docker image.

iptizer/ecr-login-action

A Github Action which can be used to authenticate with AWS ECR

iptizer/eks-lambda-python

iptizer/examples

A repository to host extended examples and tutorials

iptizer/fairing

Python SDK for building, training, and deploying ML models

iptizer/fastbook

The fastai book, published as Jupyter Notebooks

iptizer/gitea-chart

Gitea Helm Chart

iptizer/helm-charts

Development repo for helm charts

iptizer/homematicip-exporter

Prometheus Exporter for HomematicIP

iptizer/hosting

this repo hosts files to be available on a certain url

iptizer/k8s-kubespray-template

This is a template repository that can be used to set up your own Kubernetes cluster on a remote server.

iptizer/kale

Kubeflow’s superfood for Data Scientists

iptizer/kleinanzeigen-bot

A dilligent command line tool to publish ads on kleinanzeigen.de

iptizer/kubeflow-datascience

JupyterLab image for Kubeflow including kale.

iptizer/KubeflowTraining

iptizer/moritzgraf

iptizer/mqtt-cli

MQTT CLI is a useful command line interface for connecting various MQTT clients supporting MQTT 5.0 and 3.1.1

iptizer/Plotly-Dashboards-with-Dash

This is the repo for the Udemy Course Python Dashboards with Plotly's Dash

iptizer/redeploy

This container may be deployed on kubernetes and will trigger a redeployment of the via env var specified deloyment.

iptizer/stress-ng

This is the stress-ng upstream project git repository. stress-ng will stress test a computer system in various selectable ways. It was designed to exercise various physical subsystems of a computer as well as the various operating system kernel interfaces.