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Learnings
The development of this project can be segmented into three crucial phases:
Analysis of Fabric Logs
Before I started working on creating a performance analysis tool, I decided to dig into a bunch of Hyperledger Fabric logs. I explored different versions and configurations, checking out things like whether there was a peer gateway or not. My goal was to pinpoint the crucial log lines that I needed to include in our service.
Development of Logstash Pipelines
In the next step, I set up an input log pipeline to direct logs to their respective pipelines. I then created separate pipelines for each service, like one for peer and another for orderer, to handle specific logs. After preprocessing and adding necessary tags, I stored the logs in a CouchDB database for future retrieval.
Development of Python Script for Performance Analysis and Visualization
In the final phase, I developed a Python script to fetch and structure the logs. The script not only conducted performance analysis but also presented the information visually.
Articles
Hashnode Blog: https://mayank-bondre.hashnode.dev/lfx-halfway-journey