Monday, June 8, 2020

The "Exercise 5. Build your weekly IT-Control Chart by Perfomalist tool" was added to my on-line CMG class "Perfomaly Detection"

As more trainees keep enrolling to my CMG/Teachable on-line class, (https://cmg1.teachable.com/p/perfomaly_detection) I have started updating the content.


So far I have added an additional exercise to use recently developed free performance profiler web tool "https://www.perfomalist.com/". So the trainees can build the weekly IT-Control Chart with the provided sample data and with their own data.


Monday, February 3, 2020

#AnomalyDetection Free Web App "PERFOMALIST" (v1.0) is online and ready for beta testing


Welcome to PERFOMALIST v1.0 - date-time-stamped data on-line analyser  https://www.perfomalist.com/


Functionality
1. VISUALIZATION. Weekly (Monthly in v2+) data profiling to visualize patterns, anomalies and short term seasonality via IT-Control Charts. (v1.0)
2. ANALYSIS. Anomalies and Change Points Detection in date-time stamped data. (v2+)
INPUTCSV file with timestamp data (time series observations of a dynamic object). 

Sample input data can be downloaded from from the Download Input Data Sample (https://www.perfomalist.com/sample-upload.csv)

which should look like:

example

Data granularityhourly (v1.0); minutely, daily (v2+)

OUTPUT:
- IT-Control Chart (see example below)  (v1.0)
- Data cube with  summarized data (168 rows/weekhours - v1.0)
- List of anomalies and change points (v2+)

Requirement: 
Input data should consist of at least 3 weeks of history as the method requires comparing the last 7 days of data (actual) with at least 2 weeks long learning/reference data set (baseline). 
The size of the history is limited by about 5 years. Unlimited size of input data will be implemented in v.2.

Additional resources:
How to read IT-Control Chart (on-line article)
- On-line class "Performance Anomaly Detection"

Project contributors:
- Anfisa Trubina 



Thursday, April 19, 2018

My "Performance #AnomalyDetection" Online Course is Launched at CMG.org (#CMGnews)

  • Link to the course is on CMG.org site 
  • $99 for CMG Members; $149 for Non-Members. 

What is covered:

  • Machine learning based Anomaly Detection technique
  • Classical (SPC) and MASF (For system performance data) Control Chartirting
  • Where is the Control Chart Used?
  • What are the types of Control Charts?
  • Reading, building, and interpreting Control Charts
  • Typical cases of real world issues captured by anomaly detection system (VMs, Mainframes, Middleware, E2E response and more)
  • How to build free AWS cloud server with R and build there control charts
  • Performance anomaly (Perfomaly) detection system R implementation example (SEDS-lite - open source based tool)
See more:

Saturday, November 4, 2017

testing earn.com....

Earn.com for businesses If you’re a sender and want to learn more about how you can use Earn.com to increase your response rates and get more actionable user and customer feedback, contact us: sales@earn.com

CPD - Change Points Detection is planed to be implemented in the free web tool Perfomalist

 See details:  http://www.trub.in/2020/08/cpd-change-points-detection-is-planed.html