TechPrufer
Get started
Atlassian
Atlassian logoAtlassian · Feature trail

Multi-Region Bitbucket Cloud Architecture

5 posts · Aug 2021 – Mar 2026

What this trail covers

Bitbucket Cloud is evolving into a multi-region platform to enhance scalability, resiliency, and enable data residency. This involves restructuring core services to run independently in multiple regions, improving customer isolation and reducing the impact of noisy neighbors or regional issues. The platform will support data residency for EU and India-based customers by storing source code and other Bitbucket data within those regions. Key architectural changes include dropping support for cross-region replication for certain data types and a focus on regional self-sufficiency. This post details the migration of AWS CodeCommit repositories to Bitbucket Cloud, including cloning, adding remotes, pushing code, and migrating pull requests using a Python script and Bitbucket APIs. It also covers verification steps and updating remote URLs.

All Atlassian trails
  1. Building a more resilient, multi-region Bitbucket CloudThis post details the architectural changes required to move Bitbucket Cloud to a multi-region platform, enabling data residency and improving scalability and resiliency. Key technical decisions include restructuring core services to run independently in multiple regions, improving customer isolation, and dropping support for cross-workspace API requests and forking to ensure data is scoped to a single region. This lays the groundwork for data residency in the EU and India.
  2. How Bitbucket powers compliance and code quality at scaleThis post details Bitbucket Cloud's ongoing evolution towards a multi-region architecture for improved scalability, resiliency, and data residency. It highlights investments in sharding infrastructure and deploying to multiple regions globally. Specific technical aspects discussed include: granular access controls at branch, repository, and deployment environment levels; the use of Dynamic Pipelines for flexible and compliant CI/CD, allowing runtime modifications to pipelines for security scans, pre-approved Docker images, self-hosted runners, selective test execution, and cost attribution; customizable merge checks and approvals, including enforcing signed commits via GPG or SSH keys; seamless integration with Jira Service Management for automated change requests, policy-driven approvals, and audit-ready traceability; and connected workflows between Bitbucket and Jira to link code changes with work items. The post also announces upcoming features like hybrid licenses for Bitbucket Data Center customers and data residency options for Bitbucket Cloud, starting with the EU region in 2026.
  3. Migrating Your AWS CodeCommit Repository to Bitbucket CloudThis post details the technical steps for migrating Git repositories from AWS CodeCommit to Bitbucket Cloud. It outlines the use of `git clone`, `git remote add`, and `git push --mirror` for repository migration. It also provides a Python script leveraging `boto3` and `requests` to migrate open pull requests by interacting with AWS CodeCommit and Bitbucket Cloud APIs, demonstrating API usage for creating pull requests with specific data payloads and headers. The post also touches upon reconfiguring repository permissions and webhooks post-migration.
  4. Bitbucket Cloud has landed in AWSThis post announces the completion of Bitbucket Cloud's migration from on-premises data centers to AWS, operating on Atlassian's internal cloud platform, Micros. It highlights the benefits of this migration, including improved reliability (zero major incidents, 93% reduction in support cases), enhanced security (at-rest encryption, platform security best practices), and better performance (55% faster web response times). The scale of the migration is emphasized with stats on repository and query volume. The post also mentions a forthcoming in-depth engineering blog post detailing the technical aspects, challenges, and lessons learned.
  5. How we build Data Residency for Atlassian CloudThis post details the initial steps in Atlassian's evolution towards a multi-region architecture for its cloud products, driven by the need for data residency and latency optimization. It outlines the problems encountered (latency, data storage restrictions, cost efficiency), defines guiding principles (realm definition, service sharding, canonical shard selection, realm migration), and introduces key centralized systems (Cloud Provisioner, Catalogue Service, Tenant Context Service) that orchestrate data plane and control plane operations for multi-region deployments and data migration. The post also discusses the initial migration of Jira and Confluence to a new AWS region and the performance improvements observed.