Facing the challenges of an open and diverse data platform widely adopted within the company, Atlassian has implemented a novel deployment capability inspired by Kubernetes and its internal Platform-as-a-Service, Micros, aiming to provide a unified experience while maintaining flexibility and supporting ongoing user needs.
- New deployment capability modeled on Kubernetes and Micros.
- Balances open platform flexibility with governance needs.
- Focuses on user workflows for streamlined data operations.
What happened
Atlassian’s internal data platform, initially built as an open, un-opinionated system, underwent a significant evolution with the introduction of a new deployment capability. Drawing inspiration from Kubernetes and the company’s internal Platform-as-a-Service called Micros, this capability adapts these models specifically to the unique demands of data operations. The platform processes large daily data volumes—over 85 terabytes—and is regularly used by more than half of Atlassian’s employees for both internal and customer-facing functions.
Initially, users had freedom to select their own tooling, data modeling, metadata capture, and how they ran their data pipelines, which helped adoption and innovation. However, the varying implementations created challenges in platform support, inconsistent data documentation, and governance gaps. The newly introduced deployment capability aims to address these issues by standardizing key processes while allowing flexibility where it matters most.
Why it matters
The open nature of Atlassian’s data platform encouraged rapid adoption and diverse innovation but led to inconsistencies that made governance and support increasingly difficult as data volumes and regulatory requirements grew. Without standards, the platform saw fragmentation in data quality checks, metadata, lineage, and observability capabilities, increasing operational complexity for the platform team.
The deployment capability introduces a more opinionated layer that aligns with natural user workflows such as data discovery and transformation. By focusing on integrating these workflows into a seamless deployment process, users can manage pipelines, quality checks, and observability in a unified manner. This evolution supports the company’s scaling needs and positions the platform to better meet evolving governance standards while still empowering user innovation.
What to watch next
Future developments to monitor include how effectively Atlassian balances continued user-driven innovation with the governance and operational consistency introduced by the new deployment capability. The success of the platform will depend on how well it supports a unified, user-centric experience that simplifies deployment without reintroducing barriers to adoption.
Additionally, how the platform team manages evolving data regulations and integrates emerging data tooling into this new structured environment will be critical. Observers should look for further enhancements that expand integration and automation across the data lifecycle, especially in areas such as data discovery, lineage tracking, and automated quality controls.