- The [Gitaly and NFS deprecation notice](../gitaly/index.md#nfs-deprecation-notice).
- The [Gitaly and NFS deprecation notice](../gitaly/index.md#nfs-deprecation-notice).
- About the [correct mount options to use](../nfs.md#upgrade-to-gitaly-cluster-or-disable-caching-if-experiencing-data-loss).
- About the [correct mount options to use](../nfs.md#upgrade-to-gitaly-cluster-or-disable-caching-if-experiencing-data-loss).
## Cloud Native Hybrid reference architecture with Helm Charts (alternative)
As an alternative approach, you can also run select components of GitLab as Cloud Native
in Kubernetes via our official [Helm Charts](https://docs.gitlab.com/charts/).
In this setup, we support running the equivalent of GitLab Rails and Sidekiq nodes
in a Kubernetes cluster, named Webservice and Sidekiq respectively. In addition,
the following other supporting services are supported: NGINX, Task Runner, Migrations,
Prometheus, and Grafana.
Hybrid installations leverage the benefits of both cloud native and traditional
compute deployments. With this, _stateless_ components can benefit from cloud native
workload management benefits while _stateful_ components are deployed in compute VMs
with Omnibus to benefit from increased permanence.
The 2,000 reference architecture is not a highly-available setup. To achieve HA, you can follow a modified [3K reference architecture](3k_users.md#cloud-native-hybrid-reference-architecture-with-helm-charts-alternative).
NOTE:
This is an **advanced** setup. Running services in Kubernetes is well known
to be complex. **This setup is only recommended** if you have strong working
knowledge and experience in Kubernetes. The rest of this
section assumes this.
### Cluster topology
The following tables and diagram detail the hybrid environment using the same formats
as the normal environment above.
First are the components that run in Kubernetes. The recommendation at this time is to
use Google Cloud’s Kubernetes Engine (GKE) and associated machine types, but the memory
and CPU requirements should translate to most other providers. We hope to update this in the
future with further specific cloud provider details.
| Service | Nodes<sup>1</sup> | Configuration | GCP | Allocatable CPUs and Memory |
<!-- Disable ordered list rule https://github.com/DavidAnson/markdownlint/blob/main/doc/Rules.md#md029---ordered-list-item-prefix -->
<!-- markdownlint-disable MD029 -->
1. Nodes configuration is shown as it is forced to ensure pod vcpu / memory ratios and avoid scaling during **performance testing**.
In production deployments there is no need to assign pods to nodes. A minimum of three nodes in three different availability zones is strongly recommended to align with resilient cloud architecture practices.
<!-- markdownlint-enable MD029 -->
Next are the backend components that run on static compute VMs via Omnibus (or External PaaS
<!-- Disable ordered list rule https://github.com/DavidAnson/markdownlint/blob/main/doc/Rules.md#md029---ordered-list-item-prefix -->
<!-- markdownlint-disable MD029 -->
1. Can be optionally run on reputable third-party external PaaS PostgreSQL solutions. Google Cloud SQL and AWS RDS are known to work, however Azure Database for PostgreSQL is [not recommended](https://gitlab.com/gitlab-org/quality/reference-architectures/-/issues/61) due to performance issues. Consul is primarily used for PostgreSQL high availability so can be ignored when using a PostgreSQL PaaS setup. However it is also used optionally by Prometheus for Omnibus auto host discovery.
2. Can be optionally run on reputable third-party external PaaS Redis solutions. Google Memorystore and AWS Elasticache are known to work.
3. Should be run on reputable third-party object storage (storage PaaS) for cloud implementations. Google Cloud Storage and AWS S3 are known to work.
<!-- markdownlint-enable MD029 -->
NOTE:
For all PaaS solutions that involve configuring instances, it is strongly recommended to implement a minimum of three nodes in three different availability zones to align with resilient cloud architecture practices.
```plantuml
@startuml 2k
card "Kubernetes via Helm Charts" as kubernetes {
card "**External Load Balancer**" as elb #6a9be7
together {
collections "**Webservice** x3" as gitlab #32CD32
collections "**Sidekiq** x2" as sidekiq #ff8dd1
}
card "**Prometheus + Grafana**" as monitor #7FFFD4
card "**Supporting Services**" as support
}
card "**Gitaly**" as gitaly #FF8C00
card "**PostgreSQL**" as postgres #4EA7FF
card "**Redis**" as redis #FF6347
cloud "**Object Storage**" as object_storage #white
elb -[#6a9be7]-> gitlab
elb -[#6a9be7]--> monitor
gitlab -[#32CD32]--> gitaly
gitlab -[#32CD32]--> postgres
gitlab -[#32CD32]-> object_storage
gitlab -[#32CD32]--> redis
sidekiq -[#ff8dd1]--> gitaly
sidekiq -[#ff8dd1]-> object_storage
sidekiq -[#ff8dd1]---> postgres
sidekiq -[#ff8dd1]---> redis
monitor .[#7FFFD4]u-> gitlab
monitor .[#7FFFD4]-> gitaly
monitor .[#7FFFD4]-> postgres
monitor .[#7FFFD4,norank]--> redis
monitor .[#7FFFD4,norank]u--> elb
@enduml
```
### Resource usage settings
The following formulas help when calculating how many pods may be deployed within resource constraints.
The [2k reference architecture example values file](https://gitlab.com/gitlab-org/charts/gitlab/-/blob/master/examples/ref/2k.yaml)
documents how to apply the calculated configuration to the Helm Chart.
#### Webservice
Webservice pods typically need about 1 vCPU and 1.25 GB of memory _per worker_.
Each Webservice pod consumes roughly 2 vCPUs and 2.5 GB of memory using
the [recommended topology](#cluster-topology) because two worker processes
are created by default and each pod has other small processes running.
For 2,000 users we recommend a total Puma worker count of around 12.
With the [provided recommendations](#cluster-topology) this allows the deployment of up to 6
Webservice pods with 2 workers per pod and 2 pods per node. Expand available resources using
the ratio of 1 vCPU to 1.25 GB of memory _per each worker process_ for each additional
Webservice pod.
For further information on resource usage, see the [Webservice resources](https://docs.gitlab.com/charts/charts/gitlab/webservice/#resources).
#### Sidekiq
Sidekiq pods should generally have 1 vCPU and 2 GB of memory.
[The provided starting point](#cluster-topology) allows the deployment of up to
2 Sidekiq pods. Expand available resources using the 1 vCPU to 2GB memory
ratio for each additional pod.
For further information on resource usage, see the [Sidekiq resources](https://docs.gitlab.com/charts/charts/gitlab/sidekiq/#resources).
