Bitbucket Pipeline Failure Triage and Issue Creation

When a Bitbucket Pipeline fails, identify the failing step, search for related recent commits, create a Bitbucket issue for the failure, and notify the responsible developer via Microsoft Teams.

How the workflow runs

The scenario uses specific integration tools at each step, while Metorial keeps access scoped and visible.

  1. 1

    Identify the Failing Pipeline

    List recent pipeline runs and retrieve full details of the failed pipeline, including which step failed, the branch, and the trigger.

    • atlassian-bitbucket.manage_pipelines
  2. 2

    Trace Recent Commits

    List recent commits on the failing branch to identify which change most likely introduced the failure.

    • atlassian-bitbucket.list_commits
  3. 3

    Inspect Relevant Source Files

    Browse the source files or pipeline configuration referenced by the failing step to gather additional context for the issue.

    • atlassian-bitbucket.browse_source
  4. 4

    Create a Tracked Issue

    Create a repository issue documenting the pipeline failure, the failing step, the suspected commit, and steps to reproduce.

    • atlassian-bitbucket.create_issue
  5. 5

    Notify the Team

    Post a failure alert to the engineering Teams channel with a link to the issue, and send a direct message to the developer who authored the most recent commit on the branch.

    • microsoft-teams.send_channel_message
    • microsoft-teams.send_chat_message

Integrations used in this scenario

atlassian-bitbucket

Manage Pipelines

List recent pipelines and retrieve details of the failed pipeline including which step failed and the branch it ran on.

View details

atlassian-bitbucket

List Commits

Retrieve recent commits on the failing branch to identify the likely change that introduced the failure.

View details

atlassian-bitbucket

Browse Source

Inspect the relevant source files or configuration that the failing pipeline step references.

View details

atlassian-bitbucket

Create Issue

Create a tracked issue in the repository for the pipeline failure with details about the failing step and suspected cause.

View details

microsoft-teams

Send Channel Message

Post a pipeline failure alert to the engineering Teams channel with the issue link and failure context.

View details

microsoft-teams

Send Chat Message

Send a direct message to the developer who made the most recent commit on the failing branch.

View details

Connected systems

Integration

Bitbucket

Manage Git repositories, pull requests, and CI/CD pipelines on Bitbucket Cloud. Create, fork, and configure repositories within workspaces and projects. Create, review, approve, merge, and decline pull requests with inline code comments. Browse source code, list commits, and manage branches and tags. Track issues with the built-in issue tracker. Trigger, monitor, and manage Bitbucket Pipelines. List workspace members, configure repository default reviewers and branch restrictions, create and manage repository webhooks, and search code across repositories.

View Bitbucket

Integration

Microsoft Teams

Send, read, update, and delete messages in channels and chats. Create and manage teams, channels, and memberships. Schedule and manage online meetings, access call recordings and transcripts. Monitor user presence status in real time. Manage shifts, schedules, and time-off requests for frontline workers. Install and configure apps and tabs within teams. Send activity feed notifications to users. Subscribe to change notifications (webhooks) for messages, chats, teams, channels, memberships, presence, and meeting events. Create and manage tags for @mentioning user groups. Generate usage reports and import historical message data from other platforms.

View Microsoft Teams

Expected outcomes

Outcome 1

Pipeline failures are triaged and tracked within minutes of detection

Metorial keeps the workflow connected, governed, and traceable across the systems involved.

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Outcome 2

The responsible developer is notified directly rather than relying on manual monitoring

Metorial keeps the workflow connected, governed, and traceable across the systems involved.

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Outcome 3

Failure context including commit history and source inspection is captured in the issue

Metorial keeps the workflow connected, governed, and traceable across the systems involved.

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Outcome 4

Engineering teams have a clear record of CI/CD failures for retrospective analysis

Metorial keeps the workflow connected, governed, and traceable across the systems involved.

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How Metorial powers this scenario

Metorial is the governed connection layer between your AI agents and the tools your company runs on. It turns workflows like bitbucket pipeline failure triage and issue creation into something you can deploy quickly, safely, and at scale.

Fast

Ready for your entire team

Connect 1000+ verified integrations through one Magic MCP URL instead of building and maintaining bespoke connectors for each system in this workflow.

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Secure

Guardrails on every action

Protoguard inspects every message and tool call for prompt injection and policy violations before an agent touches your systems.

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Enterprise

SSO, policies, and audit trails

Agents act on real identity under company SSO, with per-user and per-group access policies and a complete, searchable record of everything that happens.

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Team ready

Reusable across your org

Package this workflow as a skill, attach the tools it needs, and let teammates run it through Portals — governed by admins, owned by the people who do the work.

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Products behind this workflow

The Metorial products that connect, govern, and observe this scenario.

Connectivity

Integrations

Start from 1000+ verified integrations or bring your own, and give every one a governed path to your agents under existing SSO and access policies.

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Connectivity

Magic MCP

A single URL your AI client connects to. Sign in with the login you already use and your agent reaches every integration and tool you allow — no per-app setup.

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Identity

Access Control

Sign in with company SSO, set policies per user and group, and let agents act on real identity across every connected system in this workflow.

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Governance

Protoguard

Metorial’s security layer reviews every message and tool request before an agent acts — catching prompt injection and blocking anything outside your policies.

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Observability

Tracing

A complete, searchable record of everything your agents, team, and machines do across these integrations, so you can trust the workflow in production.

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Governance

Portals

Let teammates connect agents to the integrations and skills your company already uses, with admins deciding who gets access to what.

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Built for your whole team

However you adopt AI, Metorial has a path for connecting it safely.

Solution

For Agents

Give the agents behind this scenario governed access to every tool and integration they need, with one connection layer instead of bespoke glue code.

Agents solution

Solution

For Enterprise

SSO, granular access control, security review, and full audit trails so this workflow meets enterprise governance and compliance requirements.

Enterprise solution

Solution

For your Workforce

Let the people who do this work connect their own AI agents to approved integrations and reusable skills — safely, without waiting on engineering.

Workforce solution

Build this workflow with your own tools

Metorial gives teams one governed layer for connecting integrations to real production work.