Root-cause analysis: logs, metrics and deploys in a single picture

On an incident signal the scenario collects logs, metrics, deploys and flags, clusters the errors, lines the events up in time and posts the analysis to chat.

  • Four sources collected at once instead of one by one, by hand
  • A thousand log lines collapse into a handful of failure types
  • Events lined up in time — you can see what came first
  • The analysis lands in chat instead of staying in one person's head
WebhookEmbeddings OpenAIDefault Data Loader
Connect inmemory and goScriptera

How it works

To connect Telegram and Webhook, you don't need a developer: a ready-made scenario links them in minutes.

  1. Starts when: Incident Trigger
  2. Then: Workflow Configuration
  3. Then: Fetch Logs
  4. Then: Normalize and Denoise Logs
  5. Then: Merge Context Data
  6. Then: Cluster Log Messages
  7. Then: Identify Failure Patterns
  8. Then: Time-Align Events
  9. Then: Root Cause Analysis Agent
  10. Then: Create Incident Ticket
  11. Then: Fetch Metrics
  12. Then: Fetch Recent Deployments
  13. Then: Fetch Feature Flags
  14. Then: OpenAI Embeddings
  15. Then: OpenAI Chat Model
  16. Then: Root Cause Output Parser
  17. Then: Document Loader

You can launch this Telegram + Webhook integration in Scriptera: describe the task in plain words — the scenario is built, launched and monitored for you.

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