Connect Amazon S3 and
Jira with AI

Redbird AI automates the flow between your data lake and engineering workflows. Stop manually creating tickets when pipelines fail, hunting for log files in S3 buckets, or copying deployment artifact URLs into issue comments.

No code required
Live in minutes
SOC 2 Type II

What you can automate today

Redbird gives your team ready-to-run workflows — just connect your accounts and go.

Auto-create Jira tickets when data pipeline failures are written to S3

Monitor specific S3 buckets for error logs or failed pipeline outputs. Automatically create Jira issues with failure details, attach relevant log files, and assign to the right team based on pipeline stage or error type.

Link build artifacts and deployment packages to Jira release tickets

When new build artifacts land in S3, automatically attach their URLs and metadata to corresponding Jira release issues. Engineers get instant access to deployment packages without hunting through buckets or deployment logs.

Upload test results and coverage reports from S3 to Jira story comments

Parse test output files stored in S3 and post formatted summaries as Jira comments on the related stories or epics. Include coverage percentages, failure counts, and direct links to full reports in S3.

Archive completed sprint attachments and documentation to S3 buckets

When sprints close in Jira, automatically export all issue attachments, release notes, and documentation to organized S3 folders. Maintain a searchable archive of sprint deliverables without bloating Jira storage.

Generate release reports from Jira tickets and store in S3 data lake

Aggregate completed issues, deployment metrics, and bug counts from Jira releases. Generate structured JSON or CSV reports and write them to S3 for downstream analytics, compliance audits, or executive dashboards.

Create data quality issues in Jira when anomaly reports appear in S3

Monitor S3 for data quality check outputs from dbt, Great Expectations, or custom validation scripts. When anomalies are detected, automatically create prioritized Jira tickets for data engineering teams with issue details and affected datasets.

Live in four steps

No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.

01

Connect your accounts

Authorize Amazon S3 and Jira with OAuth or API credentials. Redbird never stores your data — it just passes through.

02

Describe what you want

Tell Redbird what to do in plain language — no SQL, no code, no configuration files required.

03

Review and activate

Redbird shows you exactly what it will do before running anything. Approve the workflow, set a schedule, and switch it on.

04

Let it run — and iterate

Workflows run on your schedule or on triggers. Every run is logged. Adjust with natural language at any time.

Built for data-driven teams

Redbird understands S3 bucket structures, object metadata, and event patterns alongside Jira's issue hierarchies, custom fields, and project workflows.

AI that speaks both cloud storage and issue tracking

Redbird's AI interprets S3 object keys, prefixes, and tags to understand your data organization patterns. It maps bucket events to Jira issue types, parses log files and artifacts to extract relevant metadata, and knows how to structure attachments and comments engineers actually need. Whether you're tracking pipeline artifacts by environment, organizing logs by service, or archiving sprint deliverables by release version, Redbird handles the schema translation automatically.

S3 event patterns & prefixes
Jira issue hierarchies & workflows
Log parsing & metadata extraction
Custom field mapping
10×

faster than scripting Lambda functions to sync S3 events with Jira tickets

No boto3 scripts, webhook handlers, or custom integrations to maintain

Auto-generated reports

Redbird can pull from Amazon S3 and Jira simultaneously, merge the results, and format a polished report — sent on a schedule or on demand.

Trigger-based alerts

Set conditions in natural language. Get notified in Slack or email the moment a threshold is crossed in either Amazon S3 or Jira.

Enterprise-grade security

SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.

Bidirectional sync

Push data from Amazon S3 into Jira, or from Jira back into Amazon S3. Resolve conflicts with configurable merge rules.

Full audit trail

Every workflow run is logged — what ran, what changed, and why. Replay or revert any individual step at any time.

Triggers & actions for every team

Start automations from any S3 event or Jira issue change, then take action across both systems.

Amazon S3
Triggers & Actions
Trigger

New object uploaded to bucket

Trigger when files are added to specific S3 buckets or prefix paths.

Trigger

Object metadata updated

Detect when object tags, storage class, or metadata fields change.

Trigger

Object matches pattern or naming convention

Monitor for files matching specific naming patterns or file extensions.

Action

Upload file to bucket

Write new objects to S3 with custom metadata and tags.

Action

Copy object between buckets

Duplicate or move objects across buckets or prefixes.

Action

Update object tags or metadata

Modify storage class, tags, or custom metadata fields on existing objects.

Jira
Triggers & Actions
Trigger

Issue created or updated

Trigger on new issues or when fields like status, priority, or assignee change.

Trigger

Sprint started or completed

Detect sprint lifecycle events for reporting or archival workflows.

Trigger

Release version published

Monitor when releases are marked as shipped or deployed.

Action

Create issue with attachments

Generate new tickets with descriptions, labels, and linked S3 files.

Action

Add comment with artifact links

Post formatted comments containing S3 URLs and metadata to existing issues.

Action

Update issue fields or status

Modify assignee, priority, custom fields, or transition issues through workflows.

Amazon S3
+
Jira

Ready to connect your stack?

Stop manually bridging your data lake and engineering workflows. Redbird AI connects Amazon S3 and Jira so your pipelines, artifacts, and issue tracking work as one system.

Get started → Book a demo