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☁️🚀 Migrating to Confluence Cloud: What Unexpected Change Surprised You Most?

Sweetlana Portnaya_Seibert

Hi Atlassian Community 👋

Many teams approach a move from Confluence Data Center to Cloud thinking it’s mostly a technical migration — move pages, migrate spaces, done. But in reality, Cloud migration often comes with hidden changes that only surface after go-live.

Based on a recent deep dive published on the Seibert Products blog about Confluence Cloud Migration: What Changes (Pricing, Features & Apps), one thing became very clear:
👉 the biggest surprises are rarely about moving content, but about how people experience Confluence afterward.

Some common “wait… what?” moments teams run into:

Custom CSS, UI tweaks, or user macros no longer behaving the same (or not existing at all)
Marketplace apps working differently — or requiring manual reconfiguration
A faster release cadence introducing new features (and UI changes) more frequently than expected
Shifts in governance, permissions, and how navigation or hubs are structured
Discovering that Cloud offers powerful new features (automation, analytics, AI search), but requires rethinking old workflows

So I’m curious 👇

**What was the most surprising “hidden” change you encountered after moving to Confluence Cloud — good or bad?**
Was it apps, customization, user adoption, pricing, governance, or something else entirely?

Looking forward to learning from your experiences! 😊

Comments

Anahit Sukiasyan

Thanks for sharing it here as well, @Sweetlana Portnaya_Seibert! Really enjoyed putting it together with you and looking forward to seeing the community’s thoughts and experiences. 😊

Calogero Bonasia

Atlassian has been promoting Jira Cloud migration for years as a natural evolution for organizations using Data Center, promising continuous innovation, reduced infrastructure costs, and simplified management.

However, the operational reality emerging from concrete experiences reveals a significantly more problematic picture, characterized by critical issues that compromise users' daily efficiency.
The first critical aspect concerns system performance. Numerous users document systematic slowdowns with loading times regularly reaching 13-30 seconds for ordinary operations, 100% CPU consumption during normal use, and frequent timeouts.

These problems have persisted from 2019 to 2025, independent of client configuration, and affect organizations of varying sizes, suggesting structural limitations of the Cloud architecture rather than isolated anomalies.

Particularly problematic is the loading of issues (4-30 seconds), board updates, and simple navigation between screens—operations that in Data Center environments required fractions of a second.
Custom field management represents a second significant criticality. The Migration Assistant tends to duplicate custom fields even when they possess identical properties, generating multiple entities marked with progressive suffixes ("migrated", "migrated 2", "migrated 3").

This proliferation causes malfunctions in automation rules, user confusion, and requires complex post-migration cleanup interventions through dedicated scripts. Documented cases report fields that lose their context during transfer, becoming inaccessible via API and invalidating existing JQL queries.

The identical naming of previously distinct fields (such as "Start date" and "Start Date") generates additional operational problems, making it impossible to distinguish them in configurations.
Functional limitations complete the critical picture. Jira Cloud imposes an insurmountable limit of 32,767 characters for descriptions and comments, non-modifiable as in Data Center, causing errors during migration when content exceeds this threshold.

Since December 2024, Atlassian has also introduced a limit of 10,000 worklogs per issue, forcing organizations using Tempo Timesheets to implement aggregation solutions or continuously create new issues for recurring activities, complicating reporting and traceability.
BigPicture users report specific synchronization issues in Cloud environments: updates that require minutes or even days to propagate, changes that disappear after refresh, the need to manually rebuild structures to make changes persistent.

The bidirectional synchronization between BigPicture and Jira proves particularly unstable, requiring frequent manual re-sync interventions or cache clearing that temporarily blocks the application.

Custom workflows that don't migrate automatically, Marketplace applications requiring manual reconfiguration despite the existence of Cloud versions, and insufficient database connection pools during migration complete a concerning panorama.
After several years of commercial push toward Cloud, structurally disconnected elements persist that compromise daily operational experience, raising legitimate questions about the platform's actual maturity compared to the expectations generated by the vendor.

Anahit Sukiasyan

@Calogero Bonasia Thank you for sharing such a detailed and experience-based perspective, many of these points are valid and reflect real challenges teams have faced, especially in complex, long-lived Data Center environments.

Cloud migration is often positioned as a “natural evolution,” but in practice it’s rarely neutral or one-size-fits-all. Performance variability, app reconfiguration, and functional differences are very real considerations that need to be evaluated honestly before any move. For organizations with heavy customization, large historical datasets, or advanced app dependencies, these issues can significantly impact daily operations if not carefully planned for.

That said, where Cloud does deliver value is in areas like continuous feature delivery, reduced infrastructure and upgrade overhead, built-in security, and easier scalability for growing or distributed teams. For some organizations, especially those with simpler configurations or a willingness to rethink legacy setups, these advantages outweigh the trade-offs.

Ultimately, Cloud is becoming the default path forward. The focus now is on navigating the transition responsibly, with a clear understanding of its constraints as well as its long-term benefits.

Calogero Bonasia

@Anahit Sukiasyan, thank you for acknowledging the validity of these operational concerns. Your balanced perspective is valuable, and I agree that Cloud delivers specific advantages in certain contexts.

However, I believe it's important to clarify the perspective from which I'm speaking. I adopted Jira in 2004, when it represented the "least problematic" tool among available alternatives—not excellence, but the most practicable option.

Over two decades of use, spanning roles both as a consultant for Atlassian partners and as an end user, I've observed an evolution that systematically privileges monetization over substantive product improvement: escalating consultancy requirements, progressively mandatory partner certifications, architectural complexity that generates dependency rather than operational autonomy.

When you ask the community "what surprised you most" about Cloud migration, you're inviting honest operational feedback. Now that I'm no longer an Atlassian consultant but simply a customer, I can respond without needing to mitigate criticism to protect commercial relationships.

Continuous feature delivery and reduced infrastructure overhead are genuine advantages. But they coexist with performance degradation persisting for six years, arbitrary functional limitations introduced without migration paths, and architectural constraints forcing organizations to redesign established workflows.

The concern isn't that Cloud has trade-offs—every platform does. The concern is that Atlassian systematically understates these constraints while accelerating migrations through end-of-life announcements and pricing pressure.

You're right: Cloud is the default path forward. That's precisely why the community needs frank discussions about its current state. When you ask what surprised us most, the honest answer for many practitioners is the systematic gap between what was promised and what was actually delivered—not as an edge case, but as a recurring pattern across diverse organizational contexts.

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