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---
type: reference, concepts
---
# High Availability
GitLab offers high availability options for organizations that require
the fault tolerance and redundancy necessary to maintain high-uptime operations.
Please consult our [scaling documentation](../scaling) if you want to resolve
performance bottlenecks you encounter in individual GitLab components without
incurring the additional complexity costs associated with maintaining a
highly-available architecture.
On this page, we present examples of self-managed instances which demonstrate
how GitLab can be scaled out and made highly available. These examples progress
from simple to complex as scaling or highly-available components are added.
For larger setups serving 2,000 or more users, we provide
[reference architectures](#reference-architectures) based on GitLab's
experience with GitLab.com and internal scale testing that aim to achieve the
right balance of scalability and availability.
For detailed insight into how GitLab scales and configures GitLab.com, you can
watch [this 1 hour Q&A](https://www.youtube.com/watch?v=uCU8jdYzpac)
with [John Northrup](https://gitlab.com/northrup), and live questions coming
in from some of our customers.
## Examples
### Omnibus installation with automatic database failover
By adding automatic failover for database systems, we can enable higher uptime with an additional layer of complexity.
- For PostgreSQL, we provide repmgr for server cluster management and failover
and a combination of [PgBouncer](pgbouncer.md) and [Consul](consul.md) for
database client cutover.
- For Redis, we use [Redis Sentinel](redis.md) for server failover and client cutover.
You can also optionally run [additional Sidekiq processes on dedicated hardware](sidekiq.md)
and configure individual Sidekiq processes to
[process specific background job queues](../operations/extra_sidekiq_processes.md)
if you need to scale out background job processing.
### GitLab Geo
GitLab Geo allows you to replicate your GitLab instance to other geographical locations as a read-only fully operational instance that can also be promoted in case of disaster.
This configuration is supported in [GitLab Premium and Ultimate](https://about.gitlab.com/pricing/).
References:
- [Geo Documentation](../geo/replication/index.md)
- [GitLab Geo with a highly available configuration](../geo/replication/high_availability.md)
## GitLab components and configuration instructions
The GitLab application depends on the following [components](../../development/architecture.md#component-diagram).
It can also depend on several third party services depending on
your environment setup. Here we'll detail both in the order in which
you would typically configure them along with our recommendations for
their use and configuration.
### Third party services
Here's some details of several third party services a typical environment
will depend on. The services can be provided by numerous applications
or providers and further advice can be given on how best to select.
These should be configured first, before the [GitLab components](#gitlab-components).
| Component | Description | Configuration instructions |
|--------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------|
| [Load Balancer(s)](load_balancer.md)[^6] | Handles load balancing for the GitLab nodes where required | [Load balancer HA configuration](load_balancer.md) |
| [Cloud Object Storage service](object_storage.md)[^4] | Recommended store for shared data objects | [Cloud Object Storage configuration](object_storage.md) |
| [NFS](nfs.md)[^5] [^7] | Shared disk storage service. Can be used as an alternative for Gitaly or Object Storage. Required for GitLab Pages | [NFS configuration](nfs.md) |
### GitLab components
Next are all of the components provided directly by GitLab. As mentioned
earlier, they are presented in the typical order you would configure
them.
| Component | Description | Configuration instructions |
|---------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------|---------------------------------------------------------------|
| [Consul](../../development/architecture.md#consul)[^3] | Service discovery and health checks/failover | [Consul HA configuration](consul.md) **(PREMIUM ONLY)** |
| [PostgreSQL](../../development/architecture.md#postgresql) | Database | [Database HA configuration](database.md) |
| [PgBouncer](../../development/architecture.md#pgbouncer) | Database Pool Manager | [PgBouncer HA configuration](pgbouncer.md) **(PREMIUM ONLY)** |
| [Redis](../../development/architecture.md#redis)[^3] with Redis Sentinel | Key/Value store for shared data with HA watcher service | [Redis HA configuration](redis.md) |
| [Gitaly](../../development/architecture.md#gitaly)[^2] [^5] [^7] | Recommended high-level storage for Git repository data | [Gitaly HA configuration](gitaly.md) |
| [Sidekiq](../../development/architecture.md#sidekiq) | Asynchronous/Background jobs | [Sidekiq configuration](sidekiq.md) |
| [GitLab application nodes](../../development/architecture.md#unicorn)[^1] | (Unicorn / Puma, Workhorse) - Web-requests (UI, API, Git over HTTP) | [GitLab app HA/scaling configuration](gitlab.md) |
| [Prometheus](../../development/architecture.md#prometheus) and [Grafana](../../development/architecture.md#grafana) | GitLab environment monitoring | [Monitoring node for scaling/HA](monitoring_node.md) |
In some cases, components can be combined on the same nodes to reduce complexity as well.
## Recommended setups based on number of users
- 1 - 1000 Users: A single-node [Omnibus](https://docs.gitlab.com/omnibus/) setup with frequent backups. Refer to the [requirements page](../../install/requirements.md) for further details of the specs you will require.
- 1000 - 10000 Users: A scaled environment based on one of our [Reference Architectures](#reference-architectures), without the HA components applied. This can be a reasonable step towards a fully HA environment.
- 2000 - 50000+ Users: A scaled HA environment based on one of our [Reference Architectures](#reference-architectures) below.
## Reference architectures
In this section we'll detail the Reference Architectures that can support large numbers
of users. These were built, tested and verified by our Quality and Support teams.
Testing was done with our GitLab Performance Tool at specific coded workloads, and the
throughputs used for testing were calculated based on sample customer data. We
test each endpoint type with the following number of requests per second (RPS)
per 1000 users:
- API: 20 RPS
- Web: 2 RPS
- Git: 2 RPS
NOTE: **Note:** Note that depending on your workflow the below recommended
reference architectures may need to be adapted accordingly. Your workload
is influenced by factors such as - but not limited to - how active your users are,
how much automation you use, mirroring, and repo/change size. Additionally the
shown memory values are given directly by [GCP machine types](https://cloud.google.com/compute/docs/machine-types).
On different cloud vendors a best effort like for like can be used.
### 2,000 user configuration
- **Supported users (approximate):** 2,000
- **Test RPS rates:** API: 40 RPS, Web: 4 RPS, Git: 4 RPS
- **Known issues:** [List of known performance issues](https://gitlab.com/gitlab-org/gitlab/issues?label_name%5B%5D=Quality%3Aperformance-issues)
| Service | Nodes | Configuration[^8] | GCP type | AWS type[^9] |
| ----------------------------|-------|-----------------------|---------------|--------------|
| GitLab Rails[^1] | 3 | 8 vCPU, 7.2GB Memory | n1-highcpu-8 | c5.2xlarge |
| PostgreSQL | 3 | 2 vCPU, 7.5GB Memory | n1-standard-2 | m5.large |
| PgBouncer | 3 | 2 vCPU, 1.8GB Memory | n1-highcpu-2 | c5.large |
| Gitaly[^2] [^5] [^7] | X | 4 vCPU, 15GB Memory | n1-standard-4 | m5.xlarge |
| Redis[^3] | 3 | 2 vCPU, 7.5GB Memory | n1-standard-2 | m5.large |
| Consul + Sentinel[^3] | 3 | 2 vCPU, 1.8GB Memory | n1-highcpu-2 | c5.large |
| Sidekiq | 4 | 2 vCPU, 7.5GB Memory | n1-standard-2 | m5.large |
| Cloud Object Storage[^4] | - | - | - | - |
| NFS Server[^5] [^7] | 1 | 4 vCPU, 3.6GB Memory | n1-highcpu-4 | c5.xlarge |
| Monitoring node | 1 | 2 vCPU, 1.8GB Memory | n1-highcpu-2 | c5.large |
| External load balancing node[^6] | 1 | 2 vCPU, 1.8GB Memory | n1-highcpu-2 | c5.large |
| Internal load balancing node[^6] | 1 | 2 vCPU, 1.8GB Memory | n1-highcpu-2 | c5.large |
### 5,000 user configuration
- **Supported users (approximate):** 5,000
- **Test RPS rates:** API: 100 RPS, Web: 10 RPS, Git: 10 RPS
- **Known issues:** [List of known performance issues](https://gitlab.com/gitlab-org/gitlab/issues?label_name%5B%5D=Quality%3Aperformance-issues)
| Service | Nodes | Configuration[^8] | GCP type | AWS type[^9] |
| ----------------------------|-------|------------------------|---------------|--------------|
| GitLab Rails[^1] | 3 | 16 vCPU, 14.4GB Memory | n1-highcpu-16 | c5.4xlarge |
| PostgreSQL | 3 | 2 vCPU, 7.5GB Memory | n1-standard-2 | m5.large |
| PgBouncer | 3 | 2 vCPU, 1.8GB Memory | n1-highcpu-2 | c5.large |
| Gitaly[^2] [^5] [^7] | X | 8 vCPU, 30GB Memory | n1-standard-8 | m5.2xlarge |
| Redis[^3] | 3 | 2 vCPU, 7.5GB Memory | n1-standard-2 | m5.large |
| Consul + Sentinel[^3] | 3 | 2 vCPU, 1.8GB Memory | n1-highcpu-2 | c5.large |
| Sidekiq | 4 | 2 vCPU, 7.5GB Memory | n1-standard-2 | m5.large |
| Cloud Object Storage[^4] | - | - | - | - |
| NFS Server[^5] [^7] | 1 | 4 vCPU, 3.6GB Memory | n1-highcpu-4 | c5.xlarge |
| Monitoring node | 1 | 2 vCPU, 1.8GB Memory | n1-highcpu-2 | c5.large |
| External load balancing node[^6] | 1 | 2 vCPU, 1.8GB Memory | n1-highcpu-2 | c5.large |
| Internal load balancing node[^6] | 1 | 2 vCPU, 1.8GB Memory | n1-highcpu-2 | c5.large |
### 10,000 user configuration
- **Supported users (approximate):** 10,000
- **Test RPS rates:** API: 200 RPS, Web: 20 RPS, Git: 20 RPS
- **Known issues:** [List of known performance issues](https://gitlab.com/gitlab-org/gitlab/issues?label_name%5B%5D=Quality%3Aperformance-issues)
| Service | Nodes | GCP Configuration[^8] | GCP type | AWS type[^9] |
| ----------------------------|-------|------------------------|----------------|--------------|
| GitLab Rails[^1] | 3 | 32 vCPU, 28.8GB Memory | n1-highcpu-32 | c5.9xlarge |
| PostgreSQL | 3 | 4 vCPU, 15GB Memory | n1-standard-4 | m5.xlarge |
| PgBouncer | 3 | 2 vCPU, 1.8GB Memory | n1-highcpu-2 | c5.large |
| Gitaly[^2] [^5] [^7] | X | 16 vCPU, 60GB Memory | n1-standard-16 | m5.4xlarge |
| Redis[^3] - Cache | 3 | 4 vCPU, 15GB Memory | n1-standard-4 | m5.xlarge |
| Redis[^3] - Queues / Shared State | 3 | 4 vCPU, 15GB Memory | n1-standard-4 | m5.xlarge |
| Redis Sentinel[^3] - Cache | 3 | 1 vCPU, 1.7GB Memory | g1-small | t2.small |
| Redis Sentinel[^3] - Queues / Shared State | 3 | 1 vCPU, 1.7GB Memory | g1-small | t2.small |
| Consul | 3 | 2 vCPU, 1.8GB Memory | n1-highcpu-2 | c5.large |
| Sidekiq | 4 | 4 vCPU, 15GB Memory | n1-standard-4 | m5.xlarge |
| Cloud Object Storage[^4] | - | - | - | - |
| NFS Server[^5] [^7] | 1 | 4 vCPU, 3.6GB Memory | n1-highcpu-4 | c5.xlarge |
| Monitoring node | 1 | 4 vCPU, 3.6GB Memory | n1-highcpu-4 | c5.xlarge |
| External load balancing node[^6] | 1 | 2 vCPU, 1.8GB Memory | n1-highcpu-2 | c5.large |
| Internal load balancing node[^6] | 1 | 2 vCPU, 1.8GB Memory | n1-highcpu-2 | c5.large |
### 25,000 user configuration
- **Supported users (approximate):** 25,000
- **Test RPS rates:** API: 500 RPS, Web: 50 RPS, Git: 50 RPS
- **Known issues:** [List of known performance issues](https://gitlab.com/gitlab-org/gitlab/issues?label_name%5B%5D=Quality%3Aperformance-issues)
| Service | Nodes | Configuration[^8] | GCP type | AWS type[^9] |
| ----------------------------|-------|------------------------|----------------|--------------|
| GitLab Rails[^1] | 5 | 32 vCPU, 28.8GB Memory | n1-highcpu-32 | c5.9xlarge |
| PostgreSQL | 3 | 8 vCPU, 30GB Memory | n1-standard-8 | m5.2xlarge |
| PgBouncer | 3 | 2 vCPU, 1.8GB Memory | n1-highcpu-2 | c5.large |
| Gitaly[^2] [^5] [^7] | X | 32 vCPU, 120GB Memory | n1-standard-32 | m5.8xlarge |
| Redis[^3] - Cache | 3 | 4 vCPU, 15GB Memory | n1-standard-4 | m5.xlarge |
| Redis[^3] - Queues / Shared State | 3 | 4 vCPU, 15GB Memory | n1-standard-4 | m5.xlarge |
| Redis Sentinel[^3] - Cache | 3 | 1 vCPU, 1.7GB Memory | g1-small | t2.small |
| Redis Sentinel[^3] - Queues / Shared State | 3 | 1 vCPU, 1.7GB Memory | g1-small | t2.small |
| Consul | 3 | 2 vCPU, 1.8GB Memory | n1-highcpu-2 | c5.large |
| Sidekiq | 4 | 4 vCPU, 15GB Memory | n1-standard-4 | m5.xlarge |
| Cloud Object Storage[^4] | - | - | - | - |
| NFS Server[^5] [^7] | 1 | 4 vCPU, 3.6GB Memory | n1-highcpu-4 | c5.xlarge |
| Monitoring node | 1 | 4 vCPU, 3.6GB Memory | n1-highcpu-4 | c5.xlarge |
| External load balancing node[^6] | 1 | 2 vCPU, 1.8GB Memory | n1-highcpu-2 | c5.large |
| Internal load balancing node[^6] | 1 | 4 vCPU, 3.6GB Memory | n1-highcpu-4 | c5.xlarge |
### 50,000 user configuration
- **Supported users (approximate):** 50,000
- **Test RPS rates:** API: 1000 RPS, Web: 100 RPS, Git: 100 RPS
- **Known issues:** [List of known performance issues](https://gitlab.com/gitlab-org/gitlab/issues?label_name%5B%5D=Quality%3Aperformance-issues)
| Service | Nodes | Configuration[^8] | GCP type | AWS type[^9] |
| ----------------------------|-------|------------------------|----------------|--------------|
| GitLab Rails[^1] | 12 | 32 vCPU, 28.8GB Memory | n1-highcpu-32 | c5.9xlarge |
| PostgreSQL | 3 | 16 vCPU, 60GB Memory | n1-standard-16 | m5.4xlarge |
| PgBouncer | 3 | 2 vCPU, 1.8GB Memory | n1-highcpu-2 | c5.large |
| Gitaly[^2] [^5] [^7] | X | 64 vCPU, 240GB Memory | n1-standard-64 | m5.16xlarge |
| Redis[^3] - Cache | 3 | 4 vCPU, 15GB Memory | n1-standard-4 | m5.xlarge |
| Redis[^3] - Queues / Shared State | 3 | 4 vCPU, 15GB Memory | n1-standard-4 | m5.xlarge |
| Redis Sentinel[^3] - Cache | 3 | 1 vCPU, 1.7GB Memory | g1-small | t2.small |
| Redis Sentinel[^3] - Queues / Shared State | 3 | 1 vCPU, 1.7GB Memory | g1-small | t2.small |
| Consul | 3 | 2 vCPU, 1.8GB Memory | n1-highcpu-2 | c5.large |
| Sidekiq | 4 | 4 vCPU, 15GB Memory | n1-standard-4 | m5.xlarge |
| NFS Server[^5] [^7] | 1 | 4 vCPU, 3.6GB Memory | n1-highcpu-4 | c5.xlarge |
| Cloud Object Storage[^4] | - | - | - | - |
| Monitoring node | 1 | 4 vCPU, 3.6GB Memory | n1-highcpu-4 | c5.xlarge |
| External load balancing node[^6] | 1 | 2 vCPU, 1.8GB Memory | n1-highcpu-2 | c5.large |
| Internal load balancing node[^6] | 1 | 8 vCPU, 7.2GB Memory | n1-highcpu-8 | c5.2xlarge |
[^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 4 threads.
[^2]: Gitaly node requirements are dependent on customer data, specifically the number of
projects and their sizes. We recommend 2 nodes as an absolute minimum for HA environments
and at least 4 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.
[^3]: Recommended Redis setup differs depending on the size of the architecture.
For smaller architectures (up to 5,000 users) 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](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 as well for each Redis Cluster.
[^4]: For data objects such as LFS, Uploads, Artifacts, etc. We recommend a [Cloud Object Storage service](object_storage.md)
over NFS where possible, due to better performance and availability.
[^5]: 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).
[^6]: Our architectures have been tested and validated with [HAProxy](https://www.haproxy.org/)
as the load balancer. However other reputable load balancers with similar feature sets
should also work instead but be aware these aren't validated.
[^7]: We strongly recommend that any Gitaly and / or NFS nodes are 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.
[^8]: 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 info 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).
[^9]: AWS-equivalent configurations are rough suggestions and may change in the
future. They have not yet been tested and validated.
|
