gitlab-org--gitlab-foss/doc/administration/reference_architectures/1k_users.md

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