If you recently migrated to Atlassian Cloud, you likely breathed a sigh of relief. No more server maintenance, no more midnight patches. But while moving to the cloud shifts the responsibility of infrastructure availability to the vendor, it leaves the responsibility of data integrity squarely on you.

This is the "Shared Responsibility Model," and it creates a critical misunderstanding regarding two acronyms that determine whether you keep your job during a disaster: RTO and RPO.

Here is the reality check: Atlassian guarantees the platform will be up. They do not guarantee the restoration of customer data lost due to human error, malicious deletion, or bad automation scripts on the customer side. If you are relying solely on native tools, your recovery time isn't "instant" it could be days or hours depending on the scenario.

However, the game has changed. While the physics of cloud restoration haven't changed, the ability to access your data by the end users in a form close to the native application view has. 

Let’s break down why "native" isn't enough, and how "instant" is no longer a myth.

The Two Metrics That Matter

In a SaaS environment, we have to bifurcate these metrics into "Platform" (Atlassian's job) and "Data" (Your job).

1. Recovery Point Objective (RPO)

Definition: The maximum amount of data (measured in time) you are willing to lose.

• Atlassian’s Commitment: They target an infrastructure RPO of 1 hour. Keep in mind, this covers mistakes they make at the infrastructure level, not the bad script you ran on Friday at 5 PM.
• Your Reality (Native): Since native backups with attachments usually run once every 48 hours, your effective RPO is 48 hours. If a crash happens 24 hours after your last backup, that data is gone. Furthermore, native tooling has a flaw regarding attachments—often providing only pointers rather than the files themselves.
• The Better Way: Third-party tools such as Revyz that backup data and also utilize webhooks to listen for deletions can shrink this window to minutes.

2. Recovery Time Objective (RTO)

Definition: The maximum amount of time your business can tolerate being offline.

• Atlassian’s Commitment: They target an infrastructure RTO of 6 hours.
• Your Reality (Native): Native restore requires overwriting the site or spinning up a sandbox, importing a massive file, and manually extracting data. This results in an RTO of Hours to Days irrespective of the volume of data you have lost.
• The New Reality: While granular restoration via API can reduce this to minutes or hours depending on data volume, there is now an alternate method: Instantaneous "Read-Only" Access. By providing users a portal to view their data immediately the functional RTO drops to near zero—something unheard of in the traditional on-premises world.
  
  

The Physics of "Cloud" Restoration: It's Not Magic

Why does it take time to restore data natively? In on-premise data centers, speed was dictated by disk I/O. In Atlassian Cloud, restoration speed is dictated by two bottlenecks:

1. Native Tooling: This is essentially a database restore. The time depends on the total volume of the site because native tools only support an "all or nothing" approach—you cannot granularly restore a single project.
2. API Rate Limits: When utilizing granular restore tools, you aren't writing directly to a database; you are sending HTTP requests. Atlassian generally throttles this to roughly 1,000 requests per minute.

The Math of Restoration: Restoring a single complex Jira issue is not one API call. It requires:

• Create Issue (1 call)
• Add Comments (1 call per comment)
• Upload Attachments (1 call per file)
• Transition Status (1 call per transition)

Result: A project with 10,000 issues might require 100,000+ API calls. At 1,000 calls/minute, the theoretical minimum RTO is 100 minutes, but throttling often makes this longer.

The "Fat Finger" Scenario

Imagine a script accidentally updates the "Description" field of 50,000 issues to "NULL".

• The Native Nightmare: You have to roll back the entire site to yesterday's backup, wiping out everyone else's work for the last 24 hours.
• The Granular Fix: A proper tool identifies the specific field change and rolls back only that field for those 50,000 issues.

To maintain acceptable recovery times, organizations must move away from "Full Site Restore" strategies and adopt solutions that allow for Granular Injection of data.

Frequently Asked Questions (FAQ): RTO & RPO in Atlassian Cloud

What is the difference between RTO and RPO in the context of Atlassian Cloud?

RPO (Recovery Point Objective) is how much data you lose. While Atlassian targets 1 hour for infrastructure, your data RPO is determined by backup frequency, typically 24 hours natively. 

RTO (Recovery Time Objective) is how long you are offline. Native restoration can take days due to "all or nothing" processes. API-based granular restoration can take minutes or hours depending on volume. 

Note: An alternate mechanism now exists to provide instantaneous access to data in a “Read-Only” manner, effectively eliminating the wait time for users to view critical information, something which is uniquely offered only by Revyz.

Why can't I just use the free Atlassian Backup Manager?

The Native Backup Manager is designed for migration, not disaster recovery. It has several critical limitations :

• Destructive Restore: You cannot restore a single project without overwriting the whole site or using a sandbox.
• Frequency Limits: Backups with attachments are often limited to every 48 hours, causing high data loss (RPO).
• Retention: Backups are only kept for 14 days.
• Reliability: Restores over 50GB often require engineering support, drastically increasing downtime.

What are the different types of disasters I should plan for?

An Atlassian Admin should plan for four main categories :

1. Global Network Disaster: Internet outages where the app is unreachable. Requires offline access to data.
2. Data Center Disaster: Atlassian infrastructure is down. Requires an alternate "read-only" portal to access data.
3. Full Site Disaster: Your specific site (e.g., company.atlassian.net) is corrupted. Requires a full site restore.
4. Human Error / Malicious Deletion: The most common scenario. A user deletes a project or a script corrupts fields. Requires granular restore capabilities.

Contact the Revyz team on how they can help you in any of the above scenarios.

How does API Rate Limiting affect my Recovery Time (RTO)?

Restoration in the cloud relies on HTTP requests which are throttled by Atlassian (approx. 1,000 requests/minute). Because a single Jira issue may require 10+ API calls to fully restore, the process is heavily dependent on data volume. Solution: An alternative to waiting for full restoration into the application is instant viewing of the data in a “Read-Only” portal. This reduces the RTO for data access to seconds. To learn more about this unique option contact the Revyz team.

How can Revyz help with these Disaster Scenarios?

Revyz addresses the gaps in native tools through :

• Granular Restore: Restore specific issues or configurations without rolling back the entire site, fixing "fat finger" errors.
• Incremental Backups + Webhooks: In addition to performing incremental backups, the Revyz solution also utilizes Webhooks to listen for deletions, shrinking data RPO from days to minutes.
• Online User Consumable Data: Provides an instantaneously accessible read-only portal so users can access critical data even if the Atlassian application is down. This mechanism is a game changer in the disaster recovery world, uniquely supported by only the Revyz application.
• Offline Access: Converts critical data into static formats stored in your own cloud for access during global network outages.

Is your backup strategy ready for a real-world disaster? Don't wait for a "fat finger" error to find out your RTO is 3 days. [Audit your current RPO and RTO capabilities today]. Contact the Revyz team today!