This document discusses developing a capacity prediction model for event management. It involves: 1. Developing a capacity model as part of event management to focus on major alarms from file system events monitored by Spectrum tool. 2. Correlating file system data with memory and CPU usage to predict the percentage of file system occupancy over time through statistical modeling. 3. The models generate predictions of when major alarms on file system partitions will occur based on the estimated average usage rate and time remaining until the alarm threshold is reached.

1. Event Management
Capacity Prediction Model
Artificial intelligence
Event Management Group

2. Challenge
Fonte: https://ibgp.net.br/evento/encontros-ibgp-on-line-arquitetura-de-nuvem-na-pratica-maio

3. Capacity Prediction Model
1. Develop the Capacity Model, part of the
Event Management Discipline
2. Focus on Major alarms, from FileSystem
events, monitored by the Spectrum tool
3. Correlate FileSystem data with Memory and
CPU
4. Predict the percentage values of FileSystem
occupancy in a given period through
statistical modeling

4. Event Management– ITIL 4
• The purpose of the event monitoring and management
practice is to systematically observe a service, or service
component, record and report selected changes of state
identified as events.
• This practice identifies and prioritizes infrastructure, services,
business processes and information security events, and
establishes the appropriate response to those events,
including responding to conditions that can lead to possible
failures or incidents.
• An event is any change of state that has significance for the
management of a configuration item (CI) or IT service.

5. ITIL 4

6. Valores - IT4IT
https://www.linkedin.com/posts/robakershoek_de
vops-it4it-itil-activity-6616362686705876992-K1Fo
Image: Rob Akershoek

7. Events in the Value Stream Network

8. Capacity Prediction Model

9. File System data

10. Line Selection

11. Scatter Plot

12. Values Graph

13. Linear Model
MODELO PROPOSTO
- % OCUPAÇÃO (Y)
- TEMPO DIAS (X)
- MÉDIA ESTIMADA (α)
- TAXA DE CRESCIMENTO (β)

14. File System Mongo DB

15. Capacity Prediction

16. Capacity Prediction

17. Capacity Prediction
PREVISÃO DO ALARME MAJOR DA PARTIÇÃO ( /PRODUTO)
MODELO14 MODELO25
PERIODO: 14 25
MÉDIA ENTIMADA (α): 75,243 75,287
TAXA DE CRESCIMENTO (β): 0,212 0,161
ALARME MAJOR (Y): 80 80
TEMPO PREVISTO (X): 22,49 29,29
TEMPO RESTANTE: 8,49 4,29
ÚLTIMA LEITURA: 19/04/20 30/04/20
PREVISÃO DO ALARME
MAJOR:
28/04/20 05/05/20

18. Capacity Prediction Python

19. Next steps
Fonte: http://mentoriadsalc.com/2020/06/05/a-automacao-do-trabalho/
Implement AutoML

20. Obrigado!
Event Management Group