![]() Understanding Bitbucket Server's resource usage See Scaling Bitbucket Server for Continuous Integration performance for some additional information about how Bitbucket Server's SCM cache can help the system scale. If your instance is Large or XLarge, take a look at our infrastructure recommendations for Bitbucket Data Center AWS deployments. If you’re running Bitbucket Data Center, check your size using the Bitbucket Data Center load profiles. Estimate or calculate the average repository size and allocate 1.5 x number of concurrent clone operations x min(repository size, 700MB) of memory.Add one CPU for every 2 concurrent clone operations. Estimate the number of concurrent clones that are expected to happen regularly (look at continuous integration).Here are some rough guidelines for choosing your hardware: Potential performance impact of embedded Crowd directory ordering.Scaling Bitbucket Server for Continuous Integration performance.Bitbucket Server production server data.Furthermore, huge Git repositories (larger than a few GBs) are likely to impact the performance of Git clients as well as Bitbucket Server. There are many operations in Bitbucket Server that require more CPU, memory and I/O when working with very large repositories. When your CI builds involve multiple parallel stages, Bitbucket Server will be asked to perform multiple clones concurrently, putting significant load on your system. One major source of clone operations is continuous integration. The count and concurrency of clone operations, which are the most resource-intensive operation Bitbucket Server performs.The type of hardware you require to run Bitbucket Server depends on a number of factors: Note that Bitbucket Data Center resources, not discussed on this page, uses a cluster of Bitbucket Server nodes to provide Active/Active failover, and is the deployment option of choice for larger enterprises that require high availability and performance at scale. This page discusses performance and hardware considerations when using Bitbucket Server. ![]() Automatically decline inactive pull requests.Setting a system-wide default branch name.Use a CDN with Atlassian Data Center applications.Improving instance stability with rate limiting.Configuring Project links across Applications.Adding additional storage for your repository data.Enabling JMX counters for performance monitoring.Export and import projects and repositories.Disable HTTP(S) access to Git repositories.Migrate Bitbucket Server from Windows to Linux.Migrating Bitbucket Server to another server.Connect Bitbucket to an external database.Administer Bitbucket Data Center and Server
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