Skip to content
Storage ⇄ Business productivity

Amazon S3 to Atlassian integration — real-time, two-way sync

Keep Amazon S3 and Atlassian in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

  • SOC 2 and 6 other compliance frameworks
  • POC with real engineers in minutes

Adopted by fast-scaling companies moving mission-critical data in real time

Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Amazon S3 and Atlassian

Land the records and documents that build up in Atlassian into Amazon S3 as they are created, and surface Amazon S3's file details on the Atlassian records that point to them, without an export job to maintain.

Atlassian and Amazon S3 hold different kinds of data. Atlassian carries records and the activity around them — the tickets, messages, orders, or issues a team works through, often with documents attached. Amazon S3 holds files and the metadata that describes them. Where the two meet is narrow but real: much of what Atlassian produces has to be kept somewhere durable, and many of the files Amazon S3 stores are the very documents Atlassian's records point to.

Stacksync syncs Issue Comments, Attachments, Custom Fields, Workflows and Statuses in Atlassian with Buckets, Objects, Object metadata, Object tags in Amazon S3 in real time. Records and attachments created in Atlassian are written into Amazon S3 as objects or files within seconds of being created. In the other direction, the metadata Amazon S3 keeps about those files — name, location, owner, modified date — flows back onto the matching record in Atlassian, so people see the current document without leaving the tool. Field-level mapping controls exactly what crosses over and in which direction, so you keep a durable copy of what matters without an extract to schedule or a nightly dump that leaves the copy a day behind.

Common use cases

  • 01 Create Jira issues from records in other systems, such as onboarding tasks generated from a closed-won CRM deal.
  • 02 Keep Jira and a second tracker (for example a customer's Jira instance) aligned during co-delivery projects.
  • 03 Index every new Object's key, size, LastModified, and user metadata into a Postgres catalog table so applications query S3 contents in SQL instead of paging ListObjectsV2.
  • 04 Two-way sync Object tags with a database so retention or classification labels set in an internal app write back onto S3 objects via the tagging API without rewriting the files.

Common sync patterns

Where Amazon S3 holds the source documents: file details on the record

A file's name, location, owner, and modified date from Amazon S3 sync onto the matching record in Atlassian, so whoever is working there sees the current version without switching tools.

A copy that outlives the tool

A continuously synced copy in Amazon S3 preserves records and documents even as they age out of Atlassian or get changed inside it, so history stays intact and reachable.

Feed a data lake or downstream pipeline

Structured records from Atlassian land in Amazon S3 as objects a data lake, search index, or processing pipeline can read, without a custom extract to build and babysit.

What you can sync between Amazon S3 and Atlassian

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

Amazon S3 objects Atlassian objects How this pairing syncs
Prefixes (folders) Logical path segments in object keys used to scope a sync and to parallelize throughput, since S3 rate limits partition by prefix. Jira Issues The central work item, synced two-way with CRMs, support desks, and other trackers. Prefixes (folders) is specific to Amazon S3 and Jira Issues to Atlassian — each maps to any object or custom field on the other side.
Multipart uploads In-progress large-object uploads assembled from parts; objects above ~100 MB (required above 5 GB) are written this way, and incomplete uploads persist until completed or aborted. Jira Projects Containers that scope issues, workflows, and permissions for a sync. Multipart uploads is specific to Amazon S3 and Jira Projects to Atlassian — each maps to any object or custom field on the other side.
Buckets Top-level, region-scoped containers that hold objects; enumerated to discover the namespaces and prefixes a sync should cover. Boards and Sprints Agile structures read to report on sprint contents and status. Buckets is specific to Amazon S3 and Boards and Sprints to Atlassian — each maps to any object or custom field on the other side.
Objects Files stored under a key; content is read with GET and written with PUT, and each object's key/size/ETag/LastModified is the unit indexed into a database. Issue Comments Threaded discussion synced into linked tickets in external systems. Objects is specific to Amazon S3 and Issue Comments to Atlassian — each maps to any object or custom field on the other side.
Object metadata System metadata (Content-Type, size, ETag, LastModified) plus user-defined x-amz-meta-* headers; user metadata is fixed at write time and only changeable by rewriting the object. Attachments Files on issues mirrored to paired records where needed. Object metadata is specific to Amazon S3 and Attachments to Atlassian — each maps to any object or custom field on the other side.
Object tags Up to 10 key-value tags per object, mutable in place via the tagging API independent of content, so classification and retention labels sync two-way without rewriting files. Custom Fields Instance-specific fields (customfield IDs) that carry most business-specific data in syncs. Object tags is specific to Amazon S3 and Custom Fields to Atlassian — each maps to any object or custom field on the other side.

How changes propagate between Amazon S3 and Atlassian

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

Amazon S3 Atlassian Sub-second propagation

DetectionAmazon S3 notifies Stacksync of record changes through webhook events. S3 Event Notifications push object-created, object-removed, and object-tagging events to SNS, SQS, Lambda, or EventBridge.

DeliveryEach detected change is written to Atlassian through its API, with automatic retries and rate-limit backoff.

Atlassian Amazon S3 Sub-second propagation

DetectionAtlassian notifies Stacksync of record changes through webhook events. Webhooks on issue and page events, plus JQL polling on the updated timestamp for backfill.

DeliveryEach detected change is written to Amazon S3 through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Amazon S3: S3 sustains at least 3,500 PUT/COPY/POST/DELETE and 5,500 GET/HEAD requests per second per partitioned prefix and scales higher automatically; bursts can return HTTP 503 SlowDown while it repartitions.
What ships with Amazon S3 ⇄ Atlassian

Connect Amazon S3 and Atlassian for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon S3–Atlassian connection.

Real-time

Two-way sync

Changes in Amazon S3 or Atlassian instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon S3 or Atlassian data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single Amazon S3 or Atlassian record.

Observability

Monitoring

Track your Amazon S3 ⇄ Atlassian sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Amazon S3 and Atlassian.

How the Amazon S3 and Atlassian connectors work

Amazon S3

Integration surface
S3 REST API (also via AWS SDKs and the S3-compatible endpoint)
Authentication
AWS IAM credentials — an access key ID and secret access key signed with AWS Signature Version 4; supports temporary STS credentials and cross-account IAM roles
Change detection
S3 Event Notifications push object-created, object-removed, and object-tagging events to SNS, SQS, Lambda, or EventBridge; there is no modified-since query, so polling relies on each object's LastModified from ListObjectsV2
Capabilities
read · write · webhooks
Rate limits
S3 sustains at least 3,500 PUT/COPY/POST/DELETE and 5,500 GET/HEAD requests per second per partitioned prefix and scales higher automatically; bursts can return HTTP 503 SlowDown while it repartitions.

Atlassian

Integration surface
REST APIs per product (Jira Cloud and Confluence Cloud)
Authentication
OAuth 2.0 (3LO) for apps or API tokens with basic auth for scripts
Change detection
Webhooks on issue and page events, plus JQL polling on the updated timestamp for backfill
Capabilities
read · write · webhooks
How it works

How to connect Amazon S3 to Atlassian — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate Amazon S3 and Atlassian with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Amazon S3 connected
    Atlassian connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Amazon S3 and Atlassian objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Amazon S3 ⇄ Atlassian
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Amazon S3 Atlassian
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
Try interactive demo
FAQ

Amazon S3 and Atlassian integration FAQ

SECURITY

Security teams trust Stacksync

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

Learn more about security
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS

SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 435 integrations available for Amazon S3 and Atlassian.

Popular · 7 of 435
All Amazon S3 integrations All Atlassian integrations Browse all integrations
Coworkers laughing in front of a laptop in a casual office setting

Your last integration took months.
Your next one takes a prompt.

Book a demo Tour the platform on your own