Commit a834f421 authored by Nailia Iskhakova's avatar Nailia Iskhakova Committed by Achilleas Pipinellis

Add Cloud Native Hybrid instructions on 50k users RA page

parent 645c5647
......@@ -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).
......
......@@ -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>
......
......@@ -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)
......
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