How I Automated Incident Management
summary
An automated incident-management pipeline that parses natural-language messages using fuzzy dialogue techniques, stores incidents as documents in Elasticsearch, creates Jira tickets, opens a dedicated chat room, updates a public status page, and posts follow-ups. The prototype is implemented in under 500 lines of Python (built in about 13 hours), recognizes intents (open/update/close/list), deduplicates recent reports, logs timestamps and priorities, and exposes incident data for dashboards and further automation.
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chapters (7)
- 0:00Incident automation intro
- 3:30Manual incident problems
- 5:14Dialogflow automation
- 7:42Live app demo
- 12:19Data analysis improvements
- 15:27Conclusion future outlook
- 16:32Q&A
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