Gek's starred repositories
build-your-own-x
Master programming by recreating your favorite technologies from scratch.
devops-exercises
Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git, Kubernetes, Terraform, OpenStack, SQL, NoSQL, Azure, GCP, DNS, Elastic, Network, Virtualization. DevOps Interview Questions
kubernetes-the-hard-way
Bootstrap Kubernetes the hard way. No scripts.
multipleWindow3dScene
A quick example of how one can "synchronize" a 3d scene across multiple windows using three.js and localStorage
goreleaser
Deliver Go binaries as fast and easily as possible
Bash-Oneliner
A collection of handy Bash One-Liners and terminal tricks for data processing and Linux system maintenance.
90DaysOfCyberSecurity
This repository contains a 90-day cybersecurity study plan, along with resources and materials for learning various cybersecurity concepts and technologies. The plan is organized into daily tasks, covering topics such as Network+, Security+, Linux, Python, Traffic Analysis, Git, ELK, AWS, Azure, and Hacking. The repository also includes a `LEARN.md
BlackFriday-GPTs-Prompts
List of free GPTs that doesn't require plus subscription
llama-models
Utilities intended for use with Llama models.
sadservers
SadServers: Linux & DevOps Troubleshooting Scenarios SaaS
awesome-prometheus
A curated list of awesome Prometheus resources, projects and tools.
HierSpeechpp
The official implementation of HierSpeech++
free-kubernetes
List of Free Trials of Managed Kubernetes Services
adm_linux_ops_questions
Репозиторий частых вопросов на собеседованиях на должность администратора Linux / DevOps
clean_registry
Docker Registry Cleanup
Iot-Cyber-Security-with-Machine-Learning-Research-Project
IoT networks have become an increasingly valuable target of malicious attacks due to the increased amount of valuable user data they contain. In response, network intrusion detection systems have been developed to detect suspicious network activity. UNSW-NB15 is an IoT-based network traffic data set with different categories for normal activities and malicious attack behaviors. UNSW-NB15 botnet datasets with IoT sensors' data are used to obtain results that show that the proposed features have the potential characteristics of identifying and classifying normal and malicious activity. Role of ML algorithms is for developing a network forensic system based on network flow identifiers and features that can track suspicious activities of botnets is possible. The ML model metrics using the UNSW-NB15 dataset revealed that ML techniques with flow identifiers can effectively and efficiently detect botnets’ attacks and their tracks.
new_project_template
This is a smal template that I use for creating new ruby projects