83 lines
5 KiB
Markdown
83 lines
5 KiB
Markdown
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# Reference architecture: up to 1,000 users
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This page describes GitLab reference architecture for up to 1,000 users.
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For a full list of reference architectures, see
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[Available reference architectures](index.md#available-reference-architectures).
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> - **Supported users (approximate):** 1,000
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> - **High Availability:** False
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| Users | Configuration([8](#footnotes)) | GCP | AWS([9](#footnotes)) | Azure([9](#footnotes)) |
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|-------|--------------------------------|---------------|----------------------|------------------------|
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| 100 | 2 vCPU, 7.2GB Memory | n1-standard-2 | m5.large | D2s v3 |
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| 500 | 4 vCPU, 15GB Memory | n1-standard-4 | m5.xlarge | D4s v3 |
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| 1000 | 8 vCPU, 30GB Memory | n1-standard-8 | m5.2xlarge | D8s v3 |
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For situations where you need to serve up to 1,000 users, a single-node
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solution with [frequent backups](index.md#automated-backups-core-only) is appropriate
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for many organizations. With automatic backup of the GitLab repositories,
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configuration, and the database, if you don't have strict availability
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requirements, this is the ideal solution.
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## Setup instructions
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- For this default reference architecture, use the standard [installation instructions](../../install/README.md) to install GitLab.
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NOTE: **Note:**
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You can also optionally configure GitLab to use an
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[external PostgreSQL service](../external_database.md) or an
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[external object storage service](../high_availability/object_storage.md) for
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added performance and reliability at a reduced complexity cost.
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## Footnotes
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1. In our architectures we run each GitLab Rails node using the Puma webserver
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and have its number of workers set to 90% of available CPUs along with four threads. For
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nodes that are running Rails with other components the worker value should be reduced
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accordingly where we've found 50% achieves a good balance but this is dependent
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on workload.
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1. Gitaly node requirements are dependent on customer data, specifically the number of
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projects and their sizes. We recommend two nodes as an absolute minimum for HA environments
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and at least four nodes should be used when supporting 50,000 or more users.
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We also recommend that each Gitaly node should store no more than 5TB of data
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and have the number of [`gitaly-ruby` workers](../gitaly/index.md#gitaly-ruby)
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set to 20% of available CPUs. Additional nodes should be considered in conjunction
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with a review of expected data size and spread based on the recommendations above.
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1. Recommended Redis setup differs depending on the size of the architecture.
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For smaller architectures (less than 3,000 users) a single instance should suffice.
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For medium sized installs (3,000 - 5,000) we suggest one Redis cluster for all
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classes and that Redis Sentinel is hosted alongside Consul.
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For larger architectures (10,000 users or more) we suggest running a separate
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[Redis Cluster](../high_availability/redis.md#running-multiple-redis-clusters) for the Cache class
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and another for the Queues and Shared State classes respectively. We also recommend
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that you run the Redis Sentinel clusters separately for each Redis Cluster.
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1. For data objects such as LFS, Uploads, Artifacts, etc. We recommend an [Object Storage service](../object_storage.md)
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over NFS where possible, due to better performance and availability.
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1. NFS can be used as an alternative for both repository data (replacing Gitaly) and
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object storage but this isn't typically recommended for performance reasons. Note however it is required for
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[GitLab Pages](https://gitlab.com/gitlab-org/gitlab-pages/issues/196).
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1. Our architectures have been tested and validated with [HAProxy](https://www.haproxy.org/)
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as the load balancer. Although other load balancers with similar feature sets
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could also be used, those load balancers have not been validated.
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1. We strongly recommend that any Gitaly or NFS nodes be set up with SSD disks over
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HDD with a throughput of at least 8,000 IOPS for read operations and 2,000 IOPS for write
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as these components have heavy I/O. These IOPS values are recommended only as a starter
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as with time they may be adjusted higher or lower depending on the scale of your
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environment's workload. If you're running the environment on a Cloud provider
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you may need to refer to their documentation on how configure IOPS correctly.
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1. The architectures were built and tested with the [Intel Xeon E5 v3 (Haswell)](https://cloud.google.com/compute/docs/cpu-platforms)
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CPU platform on GCP. On different hardware you may find that adjustments, either lower
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or higher, are required for your CPU or Node counts accordingly. For more information, a
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[Sysbench](https://github.com/akopytov/sysbench) benchmark of the CPU can be found
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[here](https://gitlab.com/gitlab-org/quality/performance/-/wikis/Reference-Architectures/GCP-CPU-Benchmarks).
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1. AWS-equivalent and Azure-equivalent configurations are rough suggestions
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and may change in the future. They have not yet been tested and validated.
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