Developer Tools
BugSnag
Connect your AI to BugSnag
Developers triage production errors by clicking through nested stack traces, breadcrumbs, and metadata across siloed projects. AI can surface the right error context instantly, but only if it sees clean fields instead of 2,000-token raw event payloads.
Why it matters
Capabilities that matter most for BugSnag
01
Errors as clean fields
Popdock flattens BugSnag events into labelled fields, so AI reads the error context instead of a 2,000-token raw payload.
02
Errors beside the customer
Join BugSnag errors with helpdesk or CRM lists to see which customers and tickets an error is behind.
03
Every project in one view
Summary and matrix lists roll errors up across projects by day or release, without clicking through each one.
Use cases
Example AI Use Cases for BugSnag
scenario
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When an error lands, someone has to own it in Bugsnag and someone has to own the Jira issue that tracks it, and those are often set separately by different people. Matching the same person across both systems by hand means looking up their account in each, and the error ends up with one engineer while the issue sits with another.
What popdock provides
--
Give an error and the owner's email address, and it finds that person in both Bugsnag and Jira by email, then finds the Jira issue that tracks the error. You see the error, the issue key, the person and both current assignees, and nothing is assigned until you approve. If the email matches more than one person it stops and lists them, and if either record already has an assignee it asks before reassigning. When the person or the issue is missing on one side, it assigns the other half and tells you plainly which half was skipped, without granting access or changing status.
Business outcome
---
One engineer owns the error and its Jira issue together, so nobody assumes someone else is handling it.
scenario
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Judging a release means pulling its session and error numbers from Bugsnag, working out which errors really happened on that build, and then scanning Jira for the work that shipped around the same time. Errors from older builds get blamed on the new one, and Jira issues that merely moved that week get presented as related.
What popdock provides
--
Name the app version, the Bugsnag project and the Jira project, and it reads the release's sessions and unhandled rate, then checks events to confirm which errors actually occurred on that build. Jira issues updated since the release are read alongside, and only an issue whose summary carries an error id counts as a confirmed link; everything else is labelled as date-window context. Each confirmed error is marked tracked or untracked in Jira, and where the previous release can be read it says whether this one looks better or worse. Nothing in either system is changed.
Business outcome
---
You get an honest picture of what a release broke and what is being tracked, without mistaking coincidence for cause.
scenario
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Assigning a Bugsnag error sounds simple, but you need the right project and person, and the person may exist in your organization without access to that project. Assign the wrong one, or someone with a pending invitation, and the error sits with someone who never sees it.
What popdock provides
--
Give the error, the project and the person's name, and it resolves the project and finds the person among the project's collaborators. If they exist in the organization but lack access to the project, it says so and stops rather than granting access; if several people match, it lists them. You see the error class, message, severity and assignee before anything changes, and it warns about pending invitations and existing assignees, asking before reassigning. It assigns only, never guesses an id, and leaves status and severity alone.
Business outcome
---
Errors go to someone who can actually see and act on them, with no silent misassignments.
scenario
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Bugsnag projects collect collaborators over time: invitations nobody accepted, people who have not signed in for months, and accounts without two-factor sign-in. Reviewing access means comparing project members with organization details person by person.
What popdock provides
--
Name a project, or audit every project, and it lists each collaborator and fills in their last activity, pending invitation, two-factor and administrator status. It flags pending invitations, accounts idle past your threshold, 90 days by default, missing two-factor and administrators. You get a table with the flags and a short list of access worth reviewing, and it says which checks it could not make when data was empty. It only reads and does not recommend removing anyone; that decision stays with you.
Business outcome
---
Access reviews take minutes, and stale or weakly secured accounts are caught before they become a risk.
scenario
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Deciding whether to keep rolling out a build means working out the stability of recent releases from session counts, comparing them with the project's targets, and figuring out which errors the new build introduced. Builds with only a handful of sessions make the percentages misleading.
What popdock provides
--
Name the project, and optionally a release stage, and it reads recent releases and works out the share of sessions without an unhandled error for each, setting aside builds with too few sessions to mean anything. Each build is compared with the project's target and critical stability. For the latest build it names the errors most likely introduced, separating those first seen in this build from older ones still occurring, and gives a verdict to keep rolling out, hold or roll back, with the reason. It only reads, and without a target it reports the raw numbers without a verdict.
Business outcome
---
You decide whether to continue a rollout on evidence, with the errors driving the call named.
scenario
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Working out why an error happens means reading its events across app versions, spotting the shared file, context and route, and placing it against the release where it first appeared. It is easy to stop at the first plausible explanation and fix the wrong thing.
What popdock provides
--
Give the error and its project, and it reads the error, its recent events and the project's releases. It looks at which app versions it occurs in, whether it reached users unhandled, the shared file and context, the URLs involved and whether it is still arriving. You get the most likely cause with its evidence, the versions and stages affected, a recommended fix, the causes it ruled out and why, and how confident it is. It diagnoses without changing anything, and if all events predate the last release it says the error may already be resolved.
Business outcome
---
Engineers start on the real cause, backed by evidence, instead of chasing the first guess.
scenario
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Setting up a new Bugsnag project means picking the correct platform type, avoiding a near duplicate of an existing project, and granting the right people access. A project cannot easily be removed afterwards, so a typo in the name or type lingers.
What popdock provides
--
Give the project name, platform type and the people who need access, and it checks for an existing or similar project first, stopping or asking before a near duplicate. The platform type is checked against types already in use, and the name and type are confirmed with you before anything is created. It then creates the project, reads back its id, and finds each collaborator by name before granting access, reporting anyone it could not resolve rather than guessing. You get the new project, its link and who was or was not given access.
Business outcome
---
New projects start with the right name, type and team access, without duplicates to clean up.
scenario
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When an error needs tracking, someone has to write a tracker issue with a title that says what broke, where and how many people it hits. Written in a hurry, titles end up vague, and the same error gets a second issue because nobody checked.
What popdock provides
--
Give the error and its project, and optionally a title, and it reads the error and its recent events to establish the class, impact, versions, stages, context and link. If you supplied no title it drafts one from the error, the failing context and the impact, and shows it to you before creating anything. It checks that no issue already exists for the error, raises exactly one through Bugsnag's linked tracker, and reports the result with the error link. It does not assign or close the error, and if no tracker is linked it reports the failure rather than retrying.
Business outcome
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Each error gets one clearly titled issue that tells the reader what broke and how badly.
scenario
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Marking an error fixed, ignored, discarded or reopened takes one click in Bugsnag, which is exactly how the wrong error gets closed. Discarding is the riskiest choice, because it also drops every future occurrence of the error, and a mistaken choice is not always noticed until users complain.
What popdock provides
--
Give the error, the project and the resolution, and it resolves the project and shows you the error's class, message, severity, status and impact along with the action it is about to take. It maps the resolution to exactly one action and stops if the request is unclear. Nothing changes until you confirm, discarding needs an explicit yes after a warning, and an error already in the requested state is left alone. Afterwards it reads the error again and reports the status it now holds, telling you if the change did not take.
Business outcome
---
Errors are resolved deliberately, one action at a time, with the result confirmed rather than assumed.
scenario
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A project with dozens of open errors needs a decision about what to fix first, and sorting by event count puts a noisy warning above a crash hitting hundreds of users. Spotting the new regressions in that pile, rather than the familiar noise, takes careful reading of every error's dates.
What popdock provides
--
Name the project and a look-back period, and it reads the open errors seen in that window. They are ranked by users affected first, then severity, then events and whether they are still arriving, with errors first seen in the window called out as new regressions. You get up to ten errors with impact, dates and links, and a short paragraph naming the one to fix first and why. It only reads, ranks on evidence without guessing at causes, and if the window is quiet it shows the most recent errors outside it.
Business outcome
---
Your team fixes the errors that hurt the most users first, and new regressions are not buried.
scenario
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After a deploy, you want to know whether it introduced new errors, but GitHub knows the run and commit while Bugsnag knows the releases and errors. Matching them by date alone pulls in old errors that simply appeared on a new version.
What popdock provides
--
Give a GitHub Actions run, or use the latest successful run on a branch, and it records the workflow, commit, author and message. It finds the Bugsnag releases built from that exact commit in each project, then lists the errors first seen after each release, with severity, events and links. You get session counts, errors introduced and a one-line verdict: clean, new handled errors only, or new unhandled errors. It only reads, and if no release carries the commit it says the build was not reported rather than matching by date.
Business outcome
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You know within minutes whether a deploy broke something, tied to the exact commit that shipped.
scenario
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Errors get marked fixed in Bugsnag while their GitHub issues stay open, so the backlog overstates what is broken. Closing them by hand means matching each error to its issue, and closing on a title that only looks similar shuts the wrong issue.
What popdock provides
--
Name the Bugsnag project and a look-back period, and it lists errors marked fixed in that window and looks for open GitHub issues carrying each exact error id in the title, never a loose title match. You see the pairs with issue numbers and assignees and choose which to close. For each one you confirm, it posts a comment with the Bugsnag link and last seen date, then closes the issue without changing anything else. If a comment posts but the close fails, it reports the issue as still open and does not comment again.
Business outcome
---
Your GitHub backlog reflects what is actually still broken, without wrongly closed issues.
scenario
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Filing a GitHub issue for a Bugsnag error means copying severity, users affected, release stages and recent occurrences into the body, then linking the issue back in Bugsnag. Skip the search first and you end up with two issues for one error.
What popdock provides
--
Give the error, and optionally a label, and it reads the error and its five most recent occurrences, then checks GitHub for an issue with that error id and for open issues about the same error class, asking whether one already covers it. You see the exact title, label and body before anything is created. After your yes it creates one issue, reads back its number and link, and links it to the error in Bugsnag. If the read-back or the link fails it reports where things stand and never creates the issue twice.
Business outcome
---
Each Bugsnag error gets one well documented GitHub issue, linked in both directions.
scenario
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When a release introduces new errors, the culprit is usually among the commits shipped since the previous release. Finding it means listing those commits from GitHub and reading them against each new error, which is slow and invites guesswork.
What popdock provides
--
Name the Bugsnag project and app version, and it finds that release and the one before it in the same stage. It lists errors first seen in the new release and the GitHub commits in between, using the source revisions as boundaries where available. For each new error it names commits whose message mentions its class, context or file as leads, never as findings. It only reads, uses a seven-day window when there is no previous release, and says when the range is too wide to attribute.
Business outcome
---
Engineers get a short list of suspect commits for each regression instead of reading the whole release.
scenario
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Some open Bugsnag errors have a GitHub issue, some have none, and some point at an issue that was closed while the error kept happening. Sorting that out means searching GitHub error by error, keeping track of what you found, and deciding which loose title matches to trust.
What popdock provides
--
Name the Bugsnag project, and optionally a severity, and it reads the open errors, busiest first, and looks for GitHub issues carrying each error id, whether open or closed. Where none is found it tries the error class and marks any hit as a probable match only. You get three tables, tracked by an open issue, tracked by a closed issue, and untracked, with counts, and an error matching several issues shows every match. It only reads and suggests next steps without filing or closing anything.
Business outcome
---
You see which errors are tracked, which have fallen through, and which issues were closed too early.
scenario
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When a release misbehaves you want the exact commit and build behind it, but Bugsnag stores a revision that may be short or full, and GitHub has many runs around the same time. Matching them by date alone risks blaming the wrong build and sending engineers to read the wrong code.
What popdock provides
--
Name the Bugsnag project, and optionally an app version, and it reads the release with its stage, build label, revision and health figures. The revision is carried to GitHub to find the commit, coping with short revisions, and then the workflow runs built from that commit. You get the release, commit, workflow runs and health side by side. It only reads, asks which release you mean when several stages match, and reports a commit without a run rather than guessing a nearby one.
Business outcome
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Every release is traceable to the commit and build that produced it, in a single step.
scenario
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A GitHub issue for an error goes stale when nobody updates it with how often the error is still happening. Pulling counts by version and stage from Bugsnag and writing them up is tedious, so the issue keeps describing last month's problem.
What popdock provides
--
Give the error, and optionally the issue number, and it reads the error and the last seven days of events, counting occurrences by app version and release stage and how many were unhandled. It finds the GitHub issue, asks which one if several match, and checks whether a similar update was posted in the last day. You see the draft comment, and it posts once only after your yes. If the issue is closed while the error is still being seen, it points that out and leaves reopening to you.
Business outcome
---
Issues stay current with real error activity, so priorities are set on this week's numbers.
scenario
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Assigning an error and its Jira issue to the same person only works if that person exists and is active in both systems. When emails differ or a Jira account is deactivated, assignments quietly fail and nobody notices until something goes unowned.
What popdock provides
--
Name the Bugsnag project, and it lists the project's collaborators with their roles and invitation status, then looks each one up in Jira by email, never by display name, along with any Jira team membership. You get three groups: matched and active, matched but inactive in Jira, and no Jira user, with pending Bugsnag invitations shown as their own state. Blank emails are reported as unmatchable rather than skipped, and multiple Jira matches are all listed. It only reads, and checks the Jira side is connected before reporting a total mismatch.
Business outcome
---
You fix ownership gaps between Bugsnag and Jira before an assignment silently fails.
scenario
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A busy Bugsnag project builds a backlog of high-volume errors that nobody ever raised in Jira. Catching up by hand means checking each one for an existing issue, then creating and linking issues, and raising too many at once floods the board.
What popdock provides
--
Set the Bugsnag project, the Jira project, a minimum event count and a cap, and it finds open errors above the threshold and drops any already tracked by a Jira link or an issue mentioning the error id. It confirms the Bug issue type exists, then shows the capped list for your approval. For each approved error it re-checks for duplicates, creates the issue, reads it back, adds a detail comment and links it to the error. The run stops at the first failure or unverified write, never exceeds the cap, and leaves Bugsnag untouched.
Business outcome
---
Your untracked error backlog is caught up in one controlled pass, without duplicates or a flooded board.
scenario
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A Jira issue tracking an error quickly falls out of date: the error keeps firing and more users are affected, but the issue still reads as it did when it was raised. Copying the current numbers and sample events across by hand rarely happens.
What popdock provides
--
Give the Bugsnag error, the Jira project and how many recent occurrences to sample, and it reads the error's status, severity, events, users, dates and stages, plus a sample of recent events. It finds the Jira issue that tracks it, asking which one if several match. You see the comment and the issue key before it posts exactly one comment, and it never edits anyone else's. Afterwards it flags a mismatch when the issue is done but the error is still open, or the reverse, without changing either.
Business outcome
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Jira issues stay honest about live errors, and mismatched statuses are spotted without anyone digging.
scenario
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You need to know which open Bugsnag errors are tracked in Jira and which are not, but the link may live in a remote link or only in an issue summary. Searching error by error is slow, and an issue whose wording only looks similar gives false comfort that the error is covered.
What popdock provides
--
Name the Bugsnag project, the Jira project and optionally a severity, and it reads the open errors, busiest first. Each one is looked up in Jira by remote link and then by issue summary, and it counts as tracked only when the error id appears in one of those, never from similar wording. You get tracked and untracked tables sorted by events, ending with the untracked error to raise first. It only reads, reports a link with no nameable issue as tracked with the key unknown, and checks the project key is right before calling everything untracked.
Business outcome
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You see exactly which errors lack a Jira issue, so nothing important goes unrecorded.
scenario
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Raising a Jira issue for a Bugsnag error by hand means copying the detail across, checking nobody already raised one, and linking the two so each side can find the other. Miss the check and you get duplicates; skip the link and the error and issue drift apart.
What popdock provides
--
Give the Bugsnag error, the Jira project and the issue type, and optionally your Jira site address, and it reads the error and checks Jira for an existing remote link or issue first, stopping if one exists. It confirms the project and issue type, shows you the summary and waits for approval, then creates one issue, reads it back and adds the detail as a comment. The issue is linked to the error in Jira and, when you supplied the site address, back from Bugsnag. If the read-back fails it stops before linking and never creates a second issue.
Business outcome
---
Each error gets one Jira issue, linked both ways, so engineers and the board share the same picture.
scenario
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When support volume jumps after a release, you want to know whether the release caused it. That means comparing Zendesk tickets before and after, finding the errors the release introduced in Bugsnag, and reading tickets to see if they match, which nobody has time for mid-incident.
What popdock provides
--
Name the Bugsnag project and app version, and a window in days, and it reads the production release and the busiest errors first seen on that version. Zendesk tickets in the same number of days before and after are counted overall and by type and priority. Tickets are tied to new errors by matching subject wording and confirming in the conversation. You get the change in volume and a verdict on whether the release raised support load and which error drove it, without percentages drawn from tiny samples. It only reads, and states that the link is by timing and wording only.
Business outcome
---
You know whether a release drove up support load, and which error to fix to bring it down.
scenario
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A customer reports that something broke, and the agent needs to know which application error is behind it. Customers paraphrase error text, so searching Bugsnag with their full sentence usually finds nothing, and engineers receive tickets with no technical lead.
What popdock provides
--
Give the Zendesk ticket, and optionally a Bugsnag project, and it reads the ticket and every comment, pulling out quoted messages, exception names, pages, URLs, versions and timing. It searches Bugsnag with short distinctive fragments around the reported time, and checks events by page when no message was given. Each candidate is rated high, medium or low on wording, timing, page and version, and a low match is never presented as the cause. It only reads, and if the ticket has no technical detail it tells the agent what to ask the customer.
Business outcome
---
Agents hand engineers the likely error behind a ticket instead of a vague description.
scenario
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When an error is serious, you want to know which customers reported it and how many organizations it touched. Customers never mention class names, so searching Zendesk means guessing the words they used and then reading tickets to rule out the ones about something else.
What popdock provides
--
Give the Bugsnag error, and optionally search text, and it reads the error and picks short fragments a customer would plausibly write. It searches Zendesk tickets created while the error was active and reads each conversation to confirm it describes this failure, discarding the rest with a reason. You get confirmed tickets with requester, organization, status and evidence, plus a count of affected organizations and requesters, kept separate from the Bugsnag user count. It only reads, and suggests alternative wording when many users are affected but no ticket matches.
Business outcome
---
You see which customers an error has reached, so support and engineering can prioritize and follow up.
scenario
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When a ticket is caused by a known error, agents and engineers both need the connection: the error should point at the ticket, and the ticket should carry the error details. Doing it by hand risks pasting error links into a public reply the customer can see.
What popdock provides
--
Give the Zendesk ticket, the Bugsnag error and your Zendesk subdomain, and it reads both records and checks whether the ticket already mentions the error. You see the ticket, the error and the two changes it will make, and nothing is written until you confirm. It links the ticket address to the error in Bugsnag and adds a private internal note to the ticket with the error class, message, status and link, each once. It reads the comments back to confirm the note is present and private, and if one write fails it says exactly which, so the other is not repeated.
Business outcome
---
Tickets and errors are cross-linked for agents and engineers, with nothing technical exposed to the customer.
scenario
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An error marked fixed or ignored in Bugsnag can quietly come back, and the first sign is often new support tickets rather than an alert. Deciding whether to reopen it means checking recent events and reading new tickets to see whether they really describe the same failure.
What popdock provides
--
Give the Bugsnag error and a look-back period, and it confirms the error is not already open, then counts recent events in Bugsnag and searches recent Zendesk tickets using short customer-facing wording, confirming each match in the conversation. It recommends reopening only on confirmed evidence, and points out when tickets suggest the problem is being reported under a different error. You see the event count and ticket ids before any change, and after your confirmation it reopens the error once and checks the status. If neither side has evidence, it reports that the fix is holding.
Business outcome
---
Regressions are reopened on real evidence from customers and events, not on hunches.
scenario
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When engineering fixes an error, the customers who reported it are still waiting in Zendesk. Finding their open tickets and writing to each one takes time, and it is easy to tell a customer something is fixed when Bugsnag does not actually say so.
What popdock provides
--
Give the Bugsnag error, and optionally search text and whether to reply publicly, and it first checks the error is marked fixed, stopping if not. It finds new, open, pending or on-hold Zendesk tickets about the failure and confirms each in the conversation. You see the tickets and the exact text, and can remove tickets before anything is posted. By default each ticket gets an internal note; a plain-language public reply without technical detail is sent only when you ask. It never changes a ticket's status, leaving agents to solve tickets once customers confirm.
Business outcome
---
Customers who reported a bug hear it is fixed, and agents close the loop without manual searching.
scenario
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Before a check-in with a key customer, you want to know how many of their recent tickets came from application defects and which of those are already fixed. Reading every ticket and matching it to Bugsnag by hand is too slow to do routinely.
What popdock provides
--
Name the Zendesk organization and a look-back period, and it confirms the organization and lists its tickets, setting aside clearly non-technical ones such as billing or how-to questions. Each technical ticket is read and matched to a Bugsnag error by short wording fragments and timing, rated high, medium or low. You get a ticket table, a grouping by error, and a call-out of open tickets whose error is already fixed or ignored, so an agent can close the loop. It only reads, and states that Bugsnag does not record which customer saw an error.
Business outcome
---
You know how application defects are affecting a customer and which of their tickets can be closed now.
scenario
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A BugHerd task created from a Bugsnag error has an owner, but the error in Bugsnag often has nobody assigned. Matching them means opening the task, finding the assignee's email, looking up the same person among the Bugsnag project's collaborators and assigning by hand, so the two systems drift apart.
What popdock provides
--
Name the BugHerd project and task number, and it checks the task is linked to a Bugsnag error and has an assignee, then finds that person's email in BugHerd. It reads the Bugsnag error and its project and matches the same email to a collaborator there; if the person is not a collaborator, it says so and stops rather than adding them. You see the error, the person and both projects, and nothing is assigned until you confirm. It then makes the one assignment and gives you the error link.
Business outcome
---
The person fixing the BugHerd task also owns the Bugsnag error, with one confirmed change and no guessing at who that is.
scenario
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After a release ships, judging whether it went well means comparing stability in Bugsnag against the previous version, picking out the errors that are new, then checking BugHerd for what testers and clients reported since. Those reports rarely get matched to the errors, so a bad release can look fine in one tool and broken in the other.
What popdock provides
--
Name the Bugsnag project, the BugHerd project and a release version, or leave the version out to use the latest. It reads the release and the one before it from Bugsnag, compares the share of unhandled sessions, and lists errors first seen since the release. It then reads the BugHerd tasks and feedback created since the release date and matches them to the new errors by page. You get a verdict of healthy, watch or roll back candidate, with one sentence why, and nothing is changed in either system.
Business outcome
---
You know in one question whether a release needs attention, backed by both error data and what people reported.
scenario
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An error in Bugsnag only gets fixed once it is on the web team's board in BugHerd. Logging it by hand means copying the error class and message, working out which page it happens on, choosing a severity, checking it is not already logged and linking the error back, and any skipped step leaves a duplicate or an error nobody can trace.
What popdock provides
--
Give a Bugsnag error and the BugHerd project, and it reads the error and its recent events to find the page where it happens most. It checks BugHerd for a task already logged from that error and stops if one exists. It drafts the task with the error details, users affected, first and last seen and the error link, and sets severity from the Bugsnag severity and user count. Nothing is created until you confirm; then it adds the task, reads back its number and link and links the Bugsnag error to it. It never changes the error's status or severity.
Business outcome
---
Bugsnag errors land on the BugHerd board once, on the right page, and each side links to the other.
scenario
-
When a BugHerd task is closed, its linked Bugsnag error often stays open, and when an error is fixed in Bugsnag the task stays on the board. Bringing them back in step means checking every linked pair by hand, and marking fixed an error that has started firing again hides a regression.
What popdock provides
--
Name the BugHerd project, and it reads the tasks and archived tasks linked to Bugsnag errors and the state of each error. It proposes marking errors fixed where the task is finished, but flags any error with new events since the task closed as may have regressed instead. Where the error is fixed or ignored and the task is still open, it proposes setting the task to done with a comment. You see all proposals in one table and only the rows you approve are applied. It never discards, ignores or reopens an error and never reopens a task.
Business outcome
---
BugHerd and Bugsnag agree on what is fixed, regressions are flagged rather than hidden, and only approved changes are made.
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