Anuket Project


Sridhar Rao

Rohit Singh Rathaur


Jahanvi Ojha 

Kanak Raj


Ildiko Vancsa

Sl. No.TopicPresenterNotes
0Introduction of Volunteers

Jahanvi:  IGDTU-Women . In 3rd Yr. Computer Science.

Kanak: BIT Mesra. 3rd Yr Math/Computing. 

Akanksha: BIT Mesra. 3rd Yr Math/Computing.

1Thoth as formal project in Anuket

Action Item: Sridhar to send a formal mail to TSC, requesting for project approval.

From next week, Thoth will be a formal project in Anuket.

Participation in Lakelse release will be difficult. Targeting 'M' Release.

2EUAG UpdateSridhar Rao

We presented at EUAG meeting on 20th July. 

Action Item: To Create a page in lf-euag confluence page.

Target Completion Date: 30th July

3Review of Model (FP) enhancement Ideas

No progress yet.

Girish: We should continue to enhance the model, and not necessarily wait for the data. 

4Data Status
Failure Type           Data Model Status             Availability           Creation Possibility               
VMYESYESDifficult (Experimental WIP)
ContainerYESNODifficult (Experimental WIP)
ApplicationIN PROGRESSYESDifficult
MiddlewareIN PROGRESSNODifficult
5Volunteers - AlgoSelector 

Work was described on 19th July. Links are also project.

General Strategy Convert your questions to users in MCQ - Yes/No, multiple-choices, Scale

Web-Based application implementation

Step-1: Separate graphs for each of the category. Start with MIT Graph .. and enhance it based on other references.

NameML Category
Jahanvi                                  Supervised                                        
Kanak RajReinforced

Step-2: Integration of these three

Step-3: Implementation platform/approach survey. Software architecture to use to implement (Ex: Python module 'abc' or dynamic forms, chat-bot).

Step-4: Implement the graph

Step-5: Testing/Review

7Volunteers - ML Problem

Relatively easier problems to obtain data. 

Important: Volunteer should be interested in 'Publications'

Step1: Enhance the survey with "Gap Analysis"

Name                                ML Problem                               

Trend and Pattern Analysis

Anomaly Detection

Correlation Analysis

Step2: Ideas to fill the gap.

Step3: Enhance the existing implementation

8TVLV-Tool for FailureGen - Project Update

Work is progressing well, Next week, Demo of Stage-1.

Student: Shubhank Saxena

Other Open problems (looking for contributors)
Project                                         Duration                     Summary                                                          
Model based, Multi-Source Data Extraction1 Month

Given a data model, the tool should extract the required data from multiple sources (Prometheus, Influxdb, Filesystem, etc).

Data Anonymizer1 Month

This can be part of the previous tool, or can be developed independently.

Given the format of the data-source, and columns to exclude,  the tools should create a copy of the data without those columns.

Synthetic Data Generator1 Month

Simulate infrastructure metrics.

Emulate Collectd-Data.

Chaos-Tools and Data-Generation1 Month

Given data-models, Identify which of the chaos tools can be reused to emulate the data.

This applies only to Kubernetes.

10Jumphost Re-Install Status
WIP. Target Date: 25th July.
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