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Sridhar Rao

Beth Cohen

Akanksha Singh

Rohit Singh Rathaur

Kanak Raj

Jahanvi Ojha

Girish L

Timo Hauswirth




Al Morton

Ildiko Vancsa

Sandra Jackson

Sl. No.TopicPresenterNotes
1AlgoSelector Update

Supervised Learning:

Started with the implementation. Request for Feedback.

Goal For Next Week: Unsupervised Learning. 

2Failure Emulation Update

No Breakthrough Yet.

Still Trying with stress-ng (interrupts, system-calls, ...)

3FP Model Development Update

Documentation: Pending


models/failure_prediction/ *.ipynb, models/failure_prediction/static_htmls, models/failure_prediction/data_preprocessing.

Rohit presented his work as part of the 'Final-Presentation' of his Internship.

Beth: Were the results expected? 


Steve: Out of 26 features, only 6 features are used. This choice is based on?


Girish: Going ahead, we will try with better data and improve these models.

Rohit: Continue to contribute to Thoth.

Target date for Whitepaper: October 20th.

4Data Extraction Tool StatusStuck at Prometheus (tested), Elasticsearch(untested).
5Synthetic Data Generation - GANs

Girish L et. al.,

Generate Monitoring/logging data using GANs.  This is a new project to create synthetic data for testing of operational ML algorithms.  The idea is to create this data set to be used across the industry as a reference data set.

Hemashree, Vidyashree, Renuka

6Exploration: Openstack Log Analysis

Openstack Logs: 

Existing Approaches: ELK - Kibana + Alarms.

Analysis: Common approach is using NLP.

Approach:  Google's BERT model for Openstack Logs.

Problems: Anomaly Detection + Pattern Analysis

Deekshita and Rakshita - NLP, Try with Openstack Logs (??)


Use of NLP for Openstack Logs has already been tried: .  This work will be used as a reference.