This is our group project for Advanced Network Management 2020 final project.

This repository is for the final project of The Anomalies

• Docs/ Documentation for this project. Includes the project specification as well as our presentation and final report.
• Legacy All of our previous prototypes and pre-trained models.
• Processing The notebooks we created for processing data of different KPI resources.
• Scripts The main and test scripts.

• Make sure python script has the following at the beginning

  #!/usr/bin/env python3

• Give it permission

  chmod +x Consumer.py

• Run it using:

  nohup python -u ./Consumer.py > [output file name].log &

• View the output log:

  cat [output file name].log

• Kill the process:

  ps ax | grep Consumer.py
  kill PID

Root cause an anomaly for a microservice-based software system.

1. Anomaly detection: Considering the time series behavior of the system, label values that exceed an arbitrary threshold as anomalies.

2. Troubleshooting: refers to the task of finding the root cause of failure and fixing it. It has 3 steps:

   1. Find time t when success rate is much lower than 1
   2. Around that time, check the behavior of microservices and other hosts and containers.
   3. After finding the abnormal source, find which KPIs perform anomalously.

3. Microservice system

   1. The user send a request (UUID-n).
   2. The Remote Procedure Call (RPC) Framework makes consecutive calls to different micro-services to process user's request.
   3. The web service posts a response (UUID-n)

   MSG Order	UUID	Sent at	Received at	MSG (m->n)
   1	UUID-1	1516171819	1516171821	call(start a)
   2	UUID-1	1516171820	1516171821	call(a - b)
   3	UUID-1	1516171821	1516171822	response(b-a)

1. ESB business indicator (ESB)

   Service name	Start time	Average time	num: # requests	# success	Success rate
   osb_001	1516171819	0.45678	360	360	1.0
   osb_001	1516171819	0.45678	461	461	1.0

   We only have osb_001 so we can neglect this column. The data is recorded every minute.

2. Trace: a user request (with a unique ID) --- it consists of several microservice calls (AKA span). Each span has a tree structure; therefore, each span has a parent span, except for the root span. There are also two types of span: inside and outside.

   ID	Parent ID	Trace ID	Start time	Elapsed time	Service name	cmdb ID	Call type	Success	ds name
   1	None	1	t1	t2-t1	foo	db_008	osb	True	-
   2	1	2	t3	t4-t3	bar	db_008	csf	True	-
   3	2	3	t5	t6-t5	bar	db_009	local	False	ANM

   callType: has 6 types.

   inside spans: 1. osb 2. remoteprocess 3. flyremote

   outside spans: 4. csf 5. local 6. jdbc

   dsName: named of the database accessed by the microservice, only when local of jdbc (where we can regard accessing databases as the microservice).

3. Host KPIs data

   Item ID	Name	Bomc ID	Timestamp	Value	cmdb ID
   1111	CPU_free	ZJ02	163249574938	420.69	db_008