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1
Intro
2
MongoDB as a Service
3
MongoDB Revenue Model
4
Atlas Scaling
5
Autoscaling
6
Ideal future
7
Experiment
8
Components
9
Data Flow
10
Planning
11
Data Science
12
Seasonal Patterns
13
MSTL
14
Accuracy
15
Shortterm Forecast
16
CPU Estimator
17
Results
18
Future plans
Description:
Explore MongoDB's groundbreaking predictive auto-scaling algorithm in this 29-minute conference talk by Jesse and Matthieu. Discover how MongoDB prevents overloads, reduces costs, and minimizes carbon footprint across half a million database servers on three public clouds. Delve into the future of cloud computing and machine learning, examining successful techniques and understanding the challenges and opportunities of implementing this revolutionary system. Learn about MongoDB's revenue model, Atlas scaling, and autoscaling processes. Investigate the components, data flow, and planning involved in the algorithm. Analyze seasonal patterns, MSTL, accuracy metrics, short-term forecasting, and CPU estimation. Gain insights into the results achieved and future plans for this innovative approach to database management.

Predictive Auto-Scaling at MongoDB - Revolutionizing Database Management

Data Council
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