1. Cloud Resource Scheduling for Online and Batch Applications
Project Introduction

2. Motivation
The hardware resources in an enterprise level data center is fixed and limited.
How to allocate resources to applications?
Application with insufficient resource incurs penalty.
According to the Service Level Agreement(SLA).

3. Project Goal
Develop a resource management framework for private cloud.
Dynamically adjust the resource allocation in order to meet the SLA of applications.

4. Two Topics Deploy the VM/container to a proper server for execution.
Decide the number of VM/container for an application in order to meet SLA.

5. Deploying to Server Study the scheduler in the existing systems.
Google Kubernetes
Design new scheduling strategies

6. Adjust Number of VM/Container
Collect information during runtime.
CPU utilization, memory usage, … etc.
Build a component with some “rules”.
Increase or decrease the number of VM/container for an application by comparing its runtime to the rules.

7. Potential Impact
Increase the QoS and resource utilization of a private cloud.
Increase the profit of enterprise.

8. Thank you for listening.