# Azure DevOps + GitHub integration > Keep work items, pull requests, and CI/CD pipelines in sync between Azure DevOps and GitHub — so your team ships without the manual busywork. **Canonical page:** https://tray.ai/connectors/azure-devops-github-integrations/ **Azure DevOps connector:** https://tray.ai/connectors/azure-devops-integrations/ **Azure DevOps documentation:** https://tray.ai/documentation/connectors/service/azure-devops **GitHub connector:** https://tray.ai/connectors/github-integrations/ **GitHub documentation:** https://tray.ai/documentation/connectors/service/github ## Overview Azure DevOps and GitHub are both excellent at what they do, which is exactly the problem. Teams that rely on both end up manually bridging gaps between work item tracking, source control, and release pipelines. It's a common split: Azure DevOps for project management, boards, and pipelines; GitHub for code. Without automation, those two worlds drift apart. tray.ai connects them in real time, so developers stop duplicating status updates, project managers stop chasing down accurate burn-down charts, and the whole team works from the same picture of what's actually happening. When a developer opens a pull request in GitHub, the linked Azure DevOps work item should update automatically — and vice versa. Without that, project managers are reconciling boards by hand, engineers are pasting the same status update in two places, and release pipelines fall out of step with the actual state of the code. Connecting the two platforms means commits, branches, PRs, and work items stay in lockstep. Leadership gets accurate reporting. Engineers get clear task context inside their IDE. QA gets confidence that what's deployed matches what was planned. tray.ai makes the connection bidirectional and flexible, with conditional logic that fits your actual workflow rather than forcing you into a rigid template. ## Use cases ### Sync GitHub Pull Requests to Azure DevOps Work Items When a developer opens, updates, or merges a pull request in GitHub, tray.ai automatically reflects that status change on the linked Azure DevOps work item. Teams no longer need to manually move work items across Azure Boards columns — the board updates itself based on real code activity. - Eliminates manual work item status updates across platforms - Keeps Azure Boards accurate in real time without developer overhead - Gives project managers live visibility into code-level progress ### Automatically Create GitHub Issues from Azure DevOps Bugs When a bug is logged in Azure DevOps — from a test run, customer report, or internal triage — tray.ai creates a corresponding GitHub Issue and links it back to the source work item. Engineers working primarily in GitHub won't miss defects raised upstream in Azure DevOps. - Bridges the gap between project management and developer workflows - Prevents bugs from getting lost between platforms - Maintains traceability from Azure DevOps bug to GitHub resolution ### Trigger Azure Pipelines from GitHub Repository Events When code is pushed to a specific branch or a pull request is merged into main in GitHub, tray.ai can trigger Azure Pipelines builds or release deployments automatically. Teams with hybrid CI/CD setups get Azure's enterprise pipeline features without abandoning GitHub as their source of truth. - Eliminates manual pipeline kicks after GitHub merges - Supports hybrid CI/CD architectures without sacrificing automation - Cuts deployment lag between code merge and release execution ### Mirror Azure DevOps Sprint Updates to GitHub Project Boards As sprints progress in Azure DevOps — stories being added, reassigned, or completed — tray.ai mirrors those updates to a corresponding GitHub Project board. Teams that plan in Azure DevOps but collaborate in GitHub stay in sync without duplicating effort across both tools. - Keeps GitHub contributors informed of sprint progress without leaving GitHub - Removes dual data entry between Azure Boards and GitHub Projects - Improves visibility for teams split across both platforms ### Sync Repository Creation and Branch Policies Across Platforms When a new repository is created in GitHub, tray.ai automatically registers it in the corresponding Azure DevOps project and applies standardized branch policies, so governance and compliance requirements are consistently enforced across all repositories. - Enforces consistent branch protection rules at scale - Reduces the risk of non-compliant repositories going undetected - Saves DevOps engineers hours of manual repo configuration ### Escalate Failed Azure Pipeline Runs as GitHub Issues When an Azure DevOps pipeline build fails, tray.ai opens a GitHub Issue tagged with relevant metadata — build ID, failing stage, error logs — and assigns it to the last committer. No one needs to monitor the Azure portal for CI failures to surface where developers are already working. - Surfaces CI/CD failures directly in the developer's primary workspace - Speeds up mean time to resolution for broken builds - Delivers structured, actionable issue data rather than raw pipeline logs ### Aggregate GitHub Commit Activity into Azure DevOps Dashboards tray.ai pulls GitHub commit and PR merge data on a scheduled basis and pushes it into Azure DevOps analytics or custom dashboard widgets, giving engineering leaders a unified view of team velocity, code throughput, and deployment frequency without logging into multiple systems. - Centralizes engineering metrics for leadership reporting in Azure DevOps - Eliminates manual data pulls from GitHub for sprint retrospectives - Enables DORA metric tracking across a hybrid toolchain ## Templates ### GitHub PR Merged → Update Azure DevOps Work Item Status This template listens for pull request merge events in GitHub and automatically transitions the linked Azure DevOps work item to 'Resolved' or 'Done', updates the assignee, adds a comment with the PR URL, and logs the merge timestamp. Connectors used: GitHub, Azure DevOps ### Azure DevOps Bug Created → Open GitHub Issue When a new bug work item is created in Azure DevOps, this template automatically creates a matching GitHub Issue in the appropriate repository, populated with the bug title, description, severity label, and a back-link to the Azure DevOps item. Connectors used: Azure DevOps, GitHub ### GitHub Release Published → Create Azure DevOps Release Note When a new release is published in GitHub, this template captures the release notes and tag version, then creates a corresponding entry in Azure DevOps — as a wiki page, work item, or release artifact note — so stakeholders tracking deployments in Azure DevOps stay informed. Connectors used: GitHub, Azure DevOps ### Nightly GitHub Commit Sync to Azure DevOps Analytics On a nightly schedule, this template queries the GitHub API for commits made during the day across specified repositories, then pushes aggregated data — author, file count, commit message, timestamp — into an Azure DevOps custom dashboard or external data store for reporting. Connectors used: GitHub, Azure DevOps ### Azure Pipeline Failure → GitHub Issue + Slack Alert When an Azure DevOps pipeline build fails, this template opens a GitHub Issue with structured failure details and sends a Slack notification to the on-call engineering channel, so the right people are notified immediately and a trackable record exists from the start. Connectors used: Azure DevOps, GitHub ### New GitHub Repository → Provision Azure DevOps Project Resources When a new repository is created in GitHub, this template creates a linked Azure DevOps project or team area, sets up initial board columns, and applies standard branch policies — so every new repo starts with consistent governance from day one. Connectors used: GitHub, Azure DevOps ## Challenges Tray.ai solves ### Preventing Infinite Loops in Bidirectional Sync When both Azure DevOps and GitHub are configured to sync updates to each other, a change in one system triggers an update in the other, which can fire another webhook back — creating an infinite loop that pollutes both platforms with duplicate data. **How Tray.ai helps:** tray.ai's workflow logic lets teams build loop-prevention guards, such as checking whether an update was system-generated before triggering downstream actions. Conditional branching and custom field flags can mark records as 'synced' so automated updates don't re-trigger the integration workflow. ### Mapping Mismatched Work Item and Issue Schemas Azure DevOps work items have a highly customizable schema — story points, iteration paths, area paths, acceptance criteria — that doesn't map neatly to GitHub Issues, which use a simpler title-label-body structure. Keeping these mappings by hand is tedious and breaks easily. **How Tray.ai helps:** tray.ai's data transformation tools let teams define precise field mappings with custom logic, including conditional formatting, default value injection, and multi-field concatenation. When schemas change, mappings can be updated centrally in tray.ai without touching individual workflows. ### Authenticating Securely Across Both Enterprise Platforms Azure DevOps often operates behind enterprise SSO, IP allowlists, and PAT rotation policies, while GitHub may use OAuth apps, GitHub Apps, or fine-grained PATs. Keeping credentials valid and secure across both platforms is an ongoing operational headache. **How Tray.ai helps:** tray.ai centralizes credential management with encrypted secret storage and supports multiple authentication methods for both Azure DevOps (PAT, OAuth) and GitHub (OAuth, GitHub App tokens). When tokens expire or rotate, they can be updated in one place without modifying individual workflows. ### Handling High-Volume Webhook Events Without Data Loss Large engineering organizations can generate hundreds of GitHub events per hour — commits, PR comments, status checks — and Azure DevOps pipelines can fire dozens of webhooks per build. Without proper queue management, bursts of events can overwhelm integration workflows and cause missed updates. **How Tray.ai helps:** tray.ai's event-driven architecture handles high-throughput webhook ingestion with automatic retry logic, event queuing, and error alerting. Workflows can batch-process events, filter out noise, and prioritize high-priority signals so critical updates aren't dropped. ### Tracing End-to-End Audit Trails Across Both Systems Compliance-driven teams need a complete audit trail showing how a requirement in Azure DevOps moved through GitHub code review, passed Azure pipelines, and was deployed. Piecing that together manually from two separate activity logs is slow and usually incomplete. **How Tray.ai helps:** tray.ai can append structured comments and timestamps to work items and issues at every stage of the integration workflow, building a chronological audit trail that links the Azure DevOps work item ID, GitHub PR URL, pipeline run ID, and deployment timestamp in a single traceable chain. ## Learn more - Intelligent Integration: https://tray.ai/platform/intelligent-ipaas/ - Merlin Agent Builder: https://tray.ai/platform/merlin-agent-builder/ - Agent Gateway for MCP: https://tray.ai/platform/agent-gateway/ - Book a demo: https://tray.ai/contact/