Redbird AI syncs pipeline artifacts, build logs, and dataset metadata from Google Cloud Storage directly into Jira issues and releases. Stop manually downloading files from buckets to attach to tickets or copy-pasting error logs from storage into bug reports.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Monitor Cloud Storage buckets for failed pipeline markers or incomplete dataset uploads. Automatically create Jira bugs with bucket paths, file metadata, and error context. Route issues to the right engineering team based on bucket naming conventions.
When release builds are uploaded to Cloud Storage, automatically attach them to corresponding Jira release issues. Include artifact metadata, version tags, and bucket locations. Keep deployment history synchronized between storage and project tracking.
Automatically move large files attached to closed Jira issues into Cloud Storage buckets with cost-optimized lifecycle rules. Maintain references in Jira with bucket paths. Reduce Atlassian storage costs while preserving compliance archives.
When new model versions are saved to Cloud Storage, find and update related Jira feature tickets with artifact paths, performance metrics, and training dataset references. Create audit trails linking models to the features that depend on them.
Pull deployment history from Cloud Storage bucket activity and cross-reference with Jira sprint data. Create comprehensive reports showing which features shipped with which artifacts. Surface artifact size trends and deployment frequency per team.
Monitor test output buckets and automatically attach relevant logs, screenshots, and test artifacts to Jira tickets marked as failed tests. Parse log files to extract error summaries and stack traces. Keep test evidence synchronized with issue status.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Google Cloud Storage and Jira with OAuth or API credentials. Redbird never stores your data — it just passes through.
Tell Redbird what to do in plain language — no SQL, no code, no configuration files required.
Redbird shows you exactly what it will do before running anything. Approve the workflow, set a schedule, and switch it on.
Workflows run on your schedule or on triggers. Every run is logged. Adjust with natural language at any time.
Redbird AI understands Cloud Storage bucket structures, object metadata, and lifecycle events alongside Jira's issue schemas, custom fields, and project hierarchies.
Redbird's AI interprets Cloud Storage bucket naming conventions, object metadata tags, and file hierarchies to understand what each artifact represents. It maps these to Jira issue types, custom fields, and project structures without rigid configuration. Whether it's linking deployment packages to release tickets or attaching pipeline logs to bug reports, Redbird understands the context in both your storage layer and your issue tracker. The AI parses log formats, extracts error patterns, and enriches Jira tickets with the exact storage references engineers need.
faster than scripting Cloud Functions to parse bucket events and update Jira via REST API
Redbird can pull from Google Cloud Storage and Jira simultaneously, merge the results, and format a polished report — sent on a schedule or on demand.
Set conditions in natural language. Get notified in Slack or email the moment a threshold is crossed in either Google Cloud Storage or Jira.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from Google Cloud Storage into Jira, or from Jira back into Google Cloud Storage. Resolve conflicts with configurable merge rules.
Every workflow run is logged — what ran, what changed, and why. Replay or revert any individual step at any time.
Start workflows from any bucket event in Cloud Storage or any issue update in Jira, then take action across both systems.
Trigger when new files are added to specific Cloud Storage buckets or paths.
Trigger when files are removed or moved to archive storage classes.
Trigger when bucket labels, lifecycle policies, or IAM permissions change.
Write generated reports, logs, or artifacts to specific Cloud Storage locations.
Move or duplicate files across buckets based on workflow logic.
Add or modify custom metadata tags on stored objects.
Trigger when new Jira issues are created or existing issues change status or fields.
Trigger when issues move to specific workflow states like 'Done' or 'Failed'.
Trigger when team members add comments to issues or mention specific keywords.
Create new Jira issues or update existing ones with storage references and metadata.
Attach files from Cloud Storage directly to Jira issues with context.
Add comments to issues with bucket paths, download links, and file metadata.
Connect Google Cloud Storage and Jira with Redbird AI to automate artifact tracking, issue enrichment, and deployment workflows. Stop manually bridging your storage layer and issue tracker.