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All DevOps learning concepts and their practical implementations are discussed
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This code sets up a turnkey, ready-to-go DevOps toolchain in minutes, using Amazon Web Services (AWS) as a platform for hosting all our tools on a virtual computer, accessible to us only. One command will trigger the fully automated process.
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This serverless application will leverage the workflow capabilities of AWS Step Functions, the pub/sub messaging capabilities of Amazon SNS, and the processing capabilities of AWS Lambda. The AWS resources will be deployed using Terraform and GitLab
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"Cloud container data analytics, statistical modeling, and machine learning on distributed databases". "A free opensource alternative to SPSS, SAS, MATLAB, PowerBI, Tableau and Alteryx". Runs on Linux, Windows, MacOS, and in the cloud via containers.
LaTeX statistics sas spss matlab Python R spark cloud gcp Oracle azure Amazon Web S... Kubernetes containers Docker ML machine lear... regression clustering TiDB Yugabyte MySQL MariaDB SQL sparkr pyspark RStudio - KNIME Anal... Apache Spark... PyTorch MXNet Chainer keras gluon Scikit-learn... ONNX MLOps - Anac... NumPy Ipython) StatsModels pytest dask Koalas API -... Tornado - Py... Altair Bokeh Jupyter Voila Plotly/Dash matplotlib Seaborn - C#... SASPy - R: T... ggplot2 shiny dash Sparklyr BlueSky Stat... Jamovi - Int... vs code Vim - Tableau TabPy Tableau Buil... Python) - PL... SQL Developer PostgreSQL MySQL/MariaDB pgAdmin4 dbeaver MySQL Workbench Spark SQL Delta Lake Angular 2+ React .NET Core JavaScript (JS) Typescript (TS) Blazor Razor html5 CSS3 AWS EC2 Servers docker-compose podman Red Hat Ente... Oracle Linux fedora centos Ubuntu (WSL 2) debian Kestrel nginx Apache web s... jira Git Gitlab CI/CD... Code Climate... Ansible helm Terraform Cloudera Dat... nifi blender godot MS OfficeUpdated
