DeepAI
Log In Sign Up

Seagull: An Infrastructure for Load Prediction and Optimized Resource Allocation

09/27/2020
by   Olga Poppe, et al.
0

Microsoft Azure is dedicated to guarantee high quality of service to its customers, in particular, during periods of high customer activity, while controlling cost. We employ a Data Science (DS) driven solution to predict user load and leverage these predictions to optimize resource allocation. To this end, we built the Seagull infrastructure that processes per-server telemetry, validates the data, trains and deploys ML models. The models are used to predict customer load per server (24h into the future), and optimize service operations. Seagull continually re-evaluates accuracy of predictions, fallback to previously known good models and triggers alerts as appropriate. We deployed this infrastructure in production for PostgreSQL and MySQL servers across all Azure regions, and applied it to the problem of scheduling server backups during low-load time. This minimizes interference with user-induced load and improves customer experience.

READ FULL TEXT

page 1

page 2

page 3

page 4

09/17/2018

The Serverless Scheduling Problem and NOAH

The serverless scheduling problem poses a new challenge to Cloud service...
09/27/2019

Improving Resource Allocation in Software-Defined Networks using Clustering

Software-defined networks (SDNs) are a huge evolution in simplifying imp...
04/05/2018

Dynamic Load Balancing with Tokens

Efficiently exploiting the resources of data centers is a complex task t...
01/11/2022

Performance Evaluation of Stochastic Bipartite Matching Models

We consider a stochastic bipartite matching model consisting of multi-cl...
01/11/2021

System Design for a Data-driven and Explainable Customer Sentiment Monitor

The most important goal of customer services is to keep the customer sat...
08/27/2020

Propensity-to-Pay: Machine Learning for Estimating Prediction Uncertainty

Predicting a customer's propensity-to-pay at an early point in the reven...
12/15/2010

Customer Appeasement Scheduling

Almost all of the current process scheduling algorithms which are used i...