intelligentdds / nezha Goto Github PK

Hi,

I have gone through your paper and published code here on GitHub and I was wondering if you've made public the way you implemented MicroRCA and TraceAnomaly for the comparison with Nezha.

I inspected the available code here but I don't think I've seen their usage.

Thanks in advance!

Hi my idol @yuxiaoba 😄

I came across the Drain config and really interested in it. How did you obtain these numbers and regular expressions?
https://github.com/IntelligentDDS/Nezha/blob/main/log_template/drain3_hipster.ini

Thank you so much in advance ^^

Hi my idol @yuxiaoba 😄

I've been trying to reproduce the results of Nezha on Hister shop. I followed the instructions carefully to install the environment, but unable to reproduce the results. I have attached here the results I got.

I see other people also have the number exactly like me (#1)

I'm wondering whether you have met this problem before (and how did you solve it?). I know you're busy, but please help when you have time. Much appreciate! 😄

This file has incorrect timestamps.
https://github.com/IntelligentDDS/Nezha/blob/main/construct_data/2022-08-22/metric/adservice-5f6585d649-fnmft_metric.csv
They all start with 18 when they should start with 16, e.g. 1861140279 when it should be 1661140279.

There could be other files as well. I am building a data loader for Nezha to https://github.com/EvoTestOps/LogLead so I just did raw string replacement and it did not check all files.

Hi,

I was wondering if you have made or can make public the complete replication package of your study. I was particularly interested in your implementation of MicroRCA and TraceAnomaly algorithms for your benchmark.

Thanks in advance!

Greetings.
First of all, I sincerely appreciate your generosity in providing the source code.
We plan to use Nezha as part of the baseline of our new platform, for which I need to reproduce Nezhe on five multi-modal datasets.
In this process, I've met two problem and had some tiny questions about Nezha.
The first problem is about the test environment. In requirements.txt, Orange3_Associate==1.1.9 was in demand, which also requires numpy==1.15.4. But Orange3_Associate1.1.9 requires Orange3>=3.25.0 and openTSNE>=0.6.1, which two requires numpy>=1.16.0.
The second problem may be caused by the first one: I've successfully run Nezha with Orange3_Associate==1.1.9 and numpy==1.15.4 on python3.6. But the outcome was awful. Here's part of the result:
[INFO]2023-11-13 21:04:39,357 pattern_ranker.py:650: --------AS@1 Result-------
[INFO]2023-11-13 21:04:39,357 pattern_ranker.py:651: 5.357143 %
[INFO]2023-11-13 21:04:39,357 pattern_ranker.py:652: --------AS@3 Result-------
[INFO]2023-11-13 21:04:39,357 pattern_ranker.py:653: 7.142857 %
[INFO]2023-11-13 21:04:39,357 pattern_ranker.py:654: --------AS@5 Result-------
[INFO]2023-11-13 21:04:39,357 pattern_ranker.py:655: 7.142857 %
I'd like to know what caused this.
And I noticed that your source code provide your own data, which contains both trace_id file and trace file. If my understanding was correct, the code only use traces when its id appreared in the trace_id file (reflected in data_integrate.py and in the function data_integrate()). I wonder why.
Please provide illuminate and dispell the darkness for us, amen.