Merge branch 'docs-add-50k-hybrid' into 'master'

Add Cloud Native Hybrid instructions on 50k users RA page

See merge request gitlab-org/gitlab!64711

doc/administration/reference_architectures/10k_users.md

@@ -2535,7 +2535,7 @@ For further information on resource usage, see the [Webservice resources](https:
 Sidekiq pods should generally have 1 vCPU and 2 GB of memory.
 
 [The provided starting point](#cluster-topology) allows the deployment of up to
-16 Sidekiq pods. Expand available resources using the 1 vCPU to 2GB memory
+14 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).

doc/administration/reference_architectures/50k_users.md

@@ -2381,6 +2381,188 @@ Read:
 - 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).
 
+## 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
+Kubernetes, you can reap certain cloud native workload management benefits while
+the others are deployed in compute VMs with Omnibus as described above in this
+page.
+
+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 will assume this.
+
+### Cluster topology
+
+The following tables and diagram details the hybrid environment using the same formats
+as the normal environment above.
+
+First starting with the components that run in Kubernetes. The recommendations at this
+time 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(1) | Configuration           | GCP              | Allocatable CPUs and Memory |
+|-------------------------------------------------------|----------|-------------------------|------------------|-----------------------------|
+| Webservice                                            | 16       | 32 vCPU, 28.8 GB memory | `n1-highcpu-32`  | 510 vCPU, 472 GB memory   |
+| Sidekiq                                               | 4        | 4 vCPU, 15 GB memory    | `n1-standard-4`  | 15.5 vCPU, 50 GB memory     |
+| Supporting services such as NGINX, Prometheus, etc.   | 2        | 4 vCPU, 15 GB memory    | `n1-standard-4`  | 7.75 vCPU, 25 GB 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
+services where applicable):
+
+| Service                                    | Nodes | Configuration           | GCP              |
+|--------------------------------------------|-------|-------------------------|------------------|
+| Consul(1)                                  | 3     | 2 vCPU, 1.8 GB memory   | `n1-highcpu-2`   |
+| PostgreSQL(1)                              | 3     | 32 vCPU, 120 GB memory  | `n1-standard-32` |
+| PgBouncer(1)                               | 3     | 2 vCPU, 1.8 GB memory   | `n1-highcpu-2`   |
+| Internal load balancing node(3)            | 1     | 8 vCPU, 7.2 GB memory   | `n1-highcpu-8`   |
+| Redis - Cache(2)                           | 3     | 4 vCPU, 15 GB memory    | `n1-standard-4`  |
+| Redis - Queues / Shared State(2)           | 3     | 4 vCPU, 15 GB memory    | `n1-standard-4`  |
+| Redis Sentinel - Cache(2)                  | 3     | 1 vCPU, 3.75 GB memory  | `n1-standard-1`  |
+| Redis Sentinel - Queues / Shared State(2)  | 3     | 1 vCPU, 3.75 GB memory  | `n1-standard-1`  |
+| Gitaly                                     | 3     | 64 vCPU, 240 GB memory  | `n1-standard-64` |
+| Praefect                                   | 3     | 4 vCPU, 3.6 GB memory   | `n1-highcpu-4`   |
+| Praefect PostgreSQL(1)                     | 1+    | 2 vCPU, 1.8 GB memory   | `n1-highcpu-2`   |
+| Object storage(4)                          | n/a   | n/a                     | n/a              |
+
+<!-- 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. Can be optionally run on reputable third-party load balancing services (LB PaaS). AWS ELB is known to work.
+4. 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 50k
+
+card "Kubernetes via Helm Charts" as kubernetes {
+  card "**External Load Balancer**" as elb #6a9be7
+
+  together {
+    collections "**Webservice** x16" as gitlab #32CD32
+    collections "**Sidekiq** x4" as sidekiq #ff8dd1
+  }
+
+  card "**Prometheus + Grafana**" as monitor #7FFFD4
+  card "**Supporting Services**" as support
+}
+
+card "**Internal Load Balancer**" as ilb #9370DB
+collections "**Consul** x3" as consul #e76a9b
+
+card "Gitaly Cluster" as gitaly_cluster {
+  collections "**Praefect** x3" as praefect #FF8C00
+  collections "**Gitaly** x3" as gitaly #FF8C00
+  card "**Praefect PostgreSQL***\n//Non fault-tolerant//" as praefect_postgres #FF8C00
+
+  praefect -[#FF8C00]-> gitaly
+  praefect -[#FF8C00]> praefect_postgres
+}
+
+card "Database" as database {
+  collections "**PGBouncer** x3" as pgbouncer #4EA7FF
+  card "**PostgreSQL** (Primary)" as postgres_primary #4EA7FF
+  collections "**PostgreSQL** (Secondary) x2" as postgres_secondary #4EA7FF
+
+  pgbouncer -[#4EA7FF]-> postgres_primary
+  postgres_primary .[#4EA7FF]> postgres_secondary
+}
+
+card "redis" as redis {
+  collections "**Redis Persistent** x3" as redis_persistent #FF6347
+  collections "**Redis Cache** x3" as redis_cache #FF6347
+  collections "**Redis Persistent Sentinel** x3" as redis_persistent_sentinel #FF6347
+  collections "**Redis Cache Sentinel** x3"as redis_cache_sentinel #FF6347
+
+  redis_persistent <.[#FF6347]- redis_persistent_sentinel
+  redis_cache <.[#FF6347]- redis_cache_sentinel
+}
+
+cloud "**Object Storage**" as object_storage #white
+
+elb -[#6a9be7]-> gitlab
+elb -[#6a9be7]-> monitor
+elb -[hidden]-> support
+
+gitlab -[#32CD32]> sidekiq
+gitlab -[#32CD32]--> ilb
+gitlab -[#32CD32]-> object_storage
+gitlab -[#32CD32]---> redis
+gitlab -[hidden]--> consul
+
+sidekiq -[#ff8dd1]--> ilb
+sidekiq -[#ff8dd1]-> object_storage
+sidekiq -[#ff8dd1]---> redis
+sidekiq -[hidden]--> consul
+
+ilb -[#9370DB]-> gitaly_cluster
+ilb -[#9370DB]-> database
+
+consul .[#e76a9b]-> database
+consul .[#e76a9b]-> gitaly_cluster
+consul .[#e76a9b,norank]--> redis
+
+monitor .[#7FFFD4]> consul
+monitor .[#7FFFD4]-> database
+monitor .[#7FFFD4]-> gitaly_cluster
+monitor .[#7FFFD4,norank]--> redis
+monitor .[#7FFFD4]> ilb
+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 [50k reference architecture example values file](https://gitlab.com/gitlab-org/charts/gitlab/-/blob/master/examples/ref/50k.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 will consume roughly 4 vCPUs and 5 GB of memory using
+the [recommended topology](#cluster-topology) because four worker processes
+are created by default and each pod has other small processes running.
+
+For 50k users we recommend a total Puma worker count of around 320.
+With the [provided recommendations](#cluster-topology) this allows the deployment of up to 80
+Webservice pods with 4 workers per pod and 5 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
+14 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).
+
 <div align="right">
   <a type="button" class="btn btn-default" href="#setup-components">
     Back to setup components <i class="fa fa-angle-double-up" aria-hidden="true"></i>

doc/administration/reference_architectures/index.md

@@ -72,6 +72,7 @@ The following reference architectures are available:
 The following Cloud Native Hybrid reference architectures, where select recommended components can be run in Kubernetes, are available:
 
 - [Up to 10,000 users](10k_users.md#cloud-native-hybrid-reference-architecture-with-helm-charts-alternative)
+- [Up to 50,000 users](50k_users.md#cloud-native-hybrid-reference-architecture-with-helm-charts-alternative)
 
 A GitLab [Premium or Ultimate](https://about.gitlab.com/pricing/#self-managed) license is required
 to get assistance from Support with troubleshooting the [2,000 users](2k_users.md)