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# log-classifier
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The purpose of this project is to analyze tickets that are in the IOHK Zendesk system and provide a solution to the end user while collecting statistics so Cardano developers can prioritize the issues.
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The purpose of this project is to analyze Cardano log file and provide a solution to the end user while collecting statistics so Cardano developers can prioritize the issues.
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## What it is
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- Log-classifier is a [command line interface](https://en.wikipedia.org/wiki/Command-line_interface) IOHK Zendesk agents can use to classify tickets.
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- Log-classifier is a [command line interface](https://en.wikipedia.org/wiki/Command-line_interface) IOHK help desk agents can use to classify tickets.
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- Currently, identifying the issue manually takes a decent amount of time and knowledge. Using classifier, the agent will be able to automate the identification of the issue without having to know all the known issues.
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- This is a Haskell program so the agent will need [stack](https://docs.haskellstack.org/en/stable/README/) and [Nix](https://nixos.org/) in order to use the classifier. Instruction on how to use it will be documented on different file.
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- The classifier cannot find any unknown/unique issues.
This is a use case diagram. Use case diagrams overview the usage requirements for a system. They are useful for presentations to management and/or project stakeholders, but for actual development, you will find that use cases provide significantly more value because they describe "the meat" of the actual requirements. For more details, please see [here](http://www.agilemodeling.com/artifacts/useCaseDiagram.htm)
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### Overview
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- Many of the Daedalus's issues can be identified by analyzing the log file. The classifier will utilize this by analyzing the log file and map with possible solution and problem which can be provided to the end user.
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- Ticket sent from Daedalus bug report has log file attached. The classifier will analyze the log file that is attached to the ticket. If any known issues where found, it'll then post a comment to that ticket. (See example below)
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- It uses [CSV](https://en.wikipedia.org/wiki/Comma-separated_values) (basically small record file) which contains all the information need to perform the analysis. This makes it easy to add new known issues.
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-Zendesk agent will use [command line interface](https://en.wikipedia.org/wiki/Command-line_interface) in order to run the classifier.
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-Help desk agent will use [command line interface](https://en.wikipedia.org/wiki/Command-line_interface) in order to run the classifier.
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- The classifier will use the [Zendesk API](https://developer.zendesk.com/rest_api/docs/core/introduction) to perform any action. Because of this, agents will need to provide their email address and password to the classifier.
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## Requirements
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### Add tags to the tickets
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After classifier has done analysis on the ticket, it'll add tags to the ticket which can be used to identify what the issues are. Agents can later use this tags to collect statistics of the Zendesk. <br />
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After classifier has done analysis on the ticket, it'll add tags to the ticket which can be used to identify what the issues are. Agents can later use this tags to collect statistics. <br />
### Collect email addresses of the tickets in which both requester and assignee is report server
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[Report server](https://github.com/input-output-hk/cardano-report-server) had a bug where it assigned both requester and assignees as report server and write down user's address in the comment section. This made it so that Zendesk agent where unable to reply back to the user unless agents create new tickets manually which takes some time to reply back. Note that this issue is already fixed.
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[Report server](https://github.com/input-output-hk/cardano-report-server) had a bug where it assigned both requester and assignees as report server and write down user's address in the comment section. This made it so that help desk agent where unable to reply back to the user unless agents create new tickets manually which takes some time to reply back. Note that this issue is already fixed.
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The classifier can collect email addresses of tickets with this issue.
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## Simple use-case scenario
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### IOHK Zendesk agent finds ticket submitted from the end user with log file attached and wants to perform analysis on it
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### IOHK help desk agent finds ticket submitted from the end user with log file attached and wants to perform analysis on it
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In this case, one can run the command below.
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This will parse the log file attached to the `<TICKET_ID>` and provide the result to the agent using private comment in the Zendesk UI. The agent then use that comment to help troubleshoot the end user.
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### IOHK Zendesk agent wants to parse every ticket that is sent from Daedalus bug report with log file attached
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### IOHK help desk agent wants to parse every ticket that is sent from Daedalus bug report with log file attached
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In this case, one can run the command below.
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This will parse any tickets with log file attached that are sent from the Daedalus bug report. It then post analysis result as private comment on any ticket that it has parsed so that the agents can provide the end user with solution.
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### IOHK Zendesk agent wants to know the statistics of the current Zendesk so he/she can report to the Cardano-SL team which will categorize/prioritize the issue
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### IOHK help desk agent wants to know the statistics of the occurring issues so he/she can report to the Cardano-SL team which will categorize/prioritize the issue
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