When Automation for Confluence fails at scale - nCino's story

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Atlassian creates some of the best tools for teams to collaborate efficiently. Confluence, in particular, has become the backbone of knowledgebase and documentation for companies of all sizes.

To make content management even smoother, Atlassian introduced Automation for Confluence—a promising solution for automating repetitive tasks, reducing manual work, and improving workflows.

But is Automation for Confluence the right tool for enterprise-scale content lifecycle management as Atlassian promotes it?

As more and more large teams adopt Confluence Cloud (many of them coming from Data Center), it turns out that it's a stretch.

We at Midori advocate for solutions that are purpose-built, designed to handle enterprise-size instances, and empower teams to implement their custom Confluence content lifecycle management strategies.

While Automation for Confluence and Smart Buttons are useful tools for lighter repetitive tasks and standardizing processes, they were not designed for automated content lifecycle management. nCino's story is a testament to this.

"We attempted utilizing Confluence Automation. In the end, that effort was ultimately a waste of time." - Gary Spross, Atlassian Cloud Administrator

nCino's story shows how Automation for Confluence struggles when teams try to implement an advanced content lifecycle management strategy.

Automation for Confluence: a scalable solution… or not?

Atlassian promotes Automation for Confluence, or at least some features like auto-archiving as a scalable enterprise-grade solution. The reality? An increasing number of large organizations, including nCino, have found that when applied to enterprise-sized Confluence instances, Automation for Confluence struggles to keep up.

The plural is justified, not an exaggeration. At Midori, we talk to these enterprise teams, though they are rarely willing to share their findings publicly.

Gary Spross, Principal Atlassian Cloud Administrator at nCino was one of the few who had already shared his opinion in a Community post.

"We built several automation rules that would label pages based on last view and last updated criteria, notify users, and ultimately archive the pages." - remembers Gary.

At first, this seemed like a promising workaround. However, they soon encountered critical limitations that rendered Automation for Confluence ineffective:

1. Last viewed date limitation: Atlassian only stores this data for a maximum of one year, which was insufficient for nCino’s multi-year lifecycle requirements.
2. Automation rule limits: The system does not handle branching on more than around 100 pages, making it impossible to scale for a high-volume Confluence instance like nCino’s.

There were other limitations, but these were enough to stop trying. Ultimately, Confluence Automation failed to meet their needs.

"I worked with Atlassian support on these issues, and even they admitted that the capabilities within Confluence Automation weren't going to allow me to implement what I was trying to implement." - Gary explained.

When Atlassian support couldn’t offer a viable workaround, nCino made the tough call: it was time to find a real enterprise-ready content lifecycle management solution.

The right move: a dedicated content lifecycle management solution

For nCino, Better Content Archiving and Analytics emerged as the right solution. Instead of fragmented automation rules, they gained a purpose-built system that could automate archiving, compliance workflows, and provide Premium-quality Confluence analytics on any tier.

Listen to Gary about how they transformed their Confluence content management and start your journey with the right solution today!

Have you encountered similar challenges with Automation for Confluence? Let’s discuss in the comments!