DEVELOPMENT OF A DEEP LEARNING-BASED AUTOSCALER ON KUBERNETES
Kubernetes has become the primary platform for container management in modern computing environments. However, the built-in Kubernetes autoscaler, HorizontalPodAutoscaler (HPA), still has limitations in responding to sudden workload changes. This study aims to develop a deep learning-based autosc...
Saved in:
Main Author: | Fadhil Al Hafidz, Rozan |
---|---|
Format: | Final Project |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/85029 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Similar Items
-
DYNAMIC RESOURCE SCHEDULER FOR DISTRIBUTED DEEP LEARNING TRAINING IN KUBERNETES
by: Fadhriga Bestari, Muhammad -
IMPLEMENTASI FAULT TOLERANT METODE DEEP LEARNING PIPEDREAM MENGGUNAKAN KUBERNETES
by: Aditya Farizki, Muhamad -
WORKER BALANCING IMPLEMENTATION ON DRAGON SCHEDULER FOR DISTRIBUTED DEEP LEARNING IN KUBERNETES
by: Prima Yoriko, Naufal -
DYNAMIC RESOURCE ALLOCATION FOR DEEP LEARNING TRAINING USING TENSORFLOW ON KUBERNETES CLUSTER
by: Yesa Surya, Rahmad -
SHARPNESS AWARE LEARNING RATE UNTUK MEMPERBAIKI AKURASI DEEP LEARNING TERDISTRIBUSI DI KUBERNETES
by: Ansa Razumardi, Ariel