CUSTOMER SUPPORT

Attach Sentry crash context to new Zendesk tickets

When a Zendesk ticket is created, finds the matching Sentry issue and attaches the crash group, breadcrumb trail, and affected-user count as an internal note so agents triage…

CategoryCustomer Support
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew Zendesk ticket createdZendeskZendesk
  • ActionBuild Sentry query from ticket text and requester
  • ActionFetch matching Sentry issue, breadcrumbs, affected usersSentrySentry
  • LogicConfident match found?
  • OutputPost internal note and tag ticket sentry-linkedZendeskZendesk

What it does

Every new Zendesk support ticket is enriched with the engineering context behind the bug. The workflow searches Sentry for the issue that matches the reporter or error fingerprint, then posts an internal note containing the crash group title, stack-frame summary, recent breadcrumb trail, and how many users are affected.

When to use it

Use it when your support team handles app-crash and error reports and currently has to ping engineering or dig through Sentry by hand. It collapses that back-and-forth into a single automatic note on the ticket.

How it works

  1. 1A new Zendesk ticket triggers the run.
  2. 2The ticket subject, body, and requester email are parsed to build a Sentry search query (error text, release, user email).
  3. 3Sentry is queried for the best-matching issue; the workflow pulls the crash group, latest event breadcrumbs, and the affected-user count.
  4. 4A filter checks whether a confident match was found.
  5. 5If matched, an internal note with the assembled context is added to the Zendesk ticket and it is tagged `sentry-linked`.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect ZendeskTickets, queues, knowledge base.
  2. 2
    Connect SentryErrors, performance, releases.
  3. 3
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  4. 4
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  5. 5
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

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