A mini container orchestration tool similar to k8s.
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Updated
Jun 11, 2022 - Python
A mini container orchestration tool similar to k8s.
Backend.AI Manager and API Gateway Daemon
Django Blog Page Application deployed on AWS Application Load Balancer with Auto Scaling, S3, Relational Database Service(RDS), VPC's Components, Lambda, DynamoDB and Cloudfront with Route 53
Scales the number of docker containers for service based on threshold(s) for metrics
Some of the code used to set up an auto-scaling infrastructure on Amazon AWS
This gym simulates a very basic cloud provider environment to be able to train automatic scaling agents
This repo has scripts and instructions for deploying a Django project on AWS EC2 with Auto Scaling and Load Balancer, including RDS for database, SSL setup, Route53 config, and RDS-PgAdmin connection.
❄️ An Auto-Scaling Cluster Manager for Discord.py
An AI-driven auto-scaling solution using Azure Functions and Azure Kubernetes Service (AKS) to dynamically adjust resources based on real-time application performance metrics
ETC mining on AWS
Phonebook Application deployed on AWS Application Load Balancer with Auto Scaling and Relational Database Service using Terraform
Custom autoscaling service for Azure VM scale sets
Auto Scalable and Highly Available Weblogic Cluster
Kernreaktor — A fast, load-driven orchestration system for Proxmox containers. Secure, scalable, and optimised for intelligent resource management.
Autoscale Docker Swarm services based on cpu utilization.
This Python package provides a robust solution for managing MySQL connections in multi-threaded applications. It implements an auto-scaling connection pool that grows and shrinks based on demand, ensuring efficient resource use and eliminating the hassle of manually creating and deleting connections.
Companion repo of "Predictive Auto-scaling with OpenStack Monasca" (UCC 2021)
A simple python flask application to generate load on container or Linux server on every hit , Useful for testing auto-scaling
Companion repo of the paper "Extending OpenStack Monasca for Predictive Elasticity Control" (BDMA)
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